Describe The Main Functions Of Each Layer In The Osi Model...

Describe The Main Functions Of Each Layer In The Osi Model...
Assignment 1: Data Transmission Sai Ram Bharadwaj Godasi 1. Describe the main functions of
each layer in the OSI model? (10 points) Ans. The main functions of each layer in the OSI model
are: Application Layer. The network services, made available by this layer, are utilized by users and
application programs. It basically acts as a window between network services and users &
application processes. This layer also handles functions like – Resource sharing and device
redirection, Remote file access, Remote printer access, Inter – process communication, Network
management, Directory services, Electronic messaging and Network virtual terminals. Presentation
Layer. Identification of the data format, providing data interfaces and data compression and
translation of data format to be presentable to the user are the functions performed in this layer. It
acts as a translator for the network by translating application layer data format to common format at
the sending station and back to application layer format at the receiving station. This layer also
provides: Character code translation, Data encryption (to secure the information). Session Layer.
Initiation, maintenance and termination of logical sessions between sender and receiver are handled
in this layer. Initiation of session is done at the sender's end and termination is handled at the
receiver's end. This layer also provides session support – performs functions that enable the
processes to communicate over
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Unit 1 Assignment 1 Essay example
Section 1–1
1. Define modulation.
In electronics and telecommunications, modulation is the process of varying one or more properties
of a periodic waveform, called the carrier signal, with a modulating signal that typically contains
information to be transmitted.
*2. What is carrier frequency?
The frequency generated by an unmodulated radio, radar, carrier communication, or other
transmitter, or the average frequency of the emitted wave when modulated by a symmetrical signal.
Also known as center frequency; resting frequency. 3. Describe the two reasons that modulation is
used for communications trans– missions.
1) Signal integrity 2) Power savings
4. List the three parameters of a high–frequency carrier that may be varied by ... Show more content
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Noise generated by electronic devices varies greatly, as it can be produced by several different
effects. Thermal noise is unavoidable at non–zero temperature, while other types depend mostly on
device type or manufacturing quality and semiconductor defects, such as conductance fluctuations,
including 1/f noise. 16. Explain the difference between external and internal noise.
Internal Noise is that which a system generates on its own. For example in MicroProcessor,
Inductance of lines connecting different gates or coupling capacitance between different lines may
produce noise. In some systems, thermal excitation and deexcitation of Electrons may produce
Noise. In Most Cases, such Noise is unavoidable. For example, if we are amplifying a signal by
normal Amplifier, which has certain internal Noise, and if We make gain large to improve signal to
Noise ratio, Noise gain will also increase!!! External Noise on the other hand comes from some
external source. For example, in Microprocessor system, ripple voltage from power supply or
voltage spikes may produce noise. This noise can often be reduced easily and may even be
suppressed.
Section 1–4
23. Calculate the S/N ratio for a receiver output of 4 V signal and 0.48 V noise both as a ratio and in
decibel form. (69.44, 18.42 dB)
27. A two–stage amplifier has a 3–dB bandwidth of 150 kHz determined by an LC circuit at its input
and operates at 27°C. The

Energy Detection Based Spectrum Sensing Method
In energy detector, the received signal is first filtered with a band pass filter in bandwidth to
normalize the noise variance and to limit the noise power. The output signal is then squared and
integrated as follows: for each in–phase or quadrature component, a number of samples over a time
interval are squared and summed. The conventional energy detection method assumes that the
primary user signal is either absent or present and the performance degrades when the primary user
is absent and then suddenly appears during the sensing time. An adaptive method to improve the
performance of Energy detection based spectrum sensing method is proposed .In this proposal, a
side detector is used which continuously monitor the spectrum so as to improve the probability of
detection. The Primary user uses a QPSK signal with a 200 kHz band–pass bandwidth (BW). The
sampling frequency is 8 times the signal BW. A 1024–point FFT is used to calculate the received
signal energy. Simulation results showed that when primary users appear during the sensing time,
the conventional energy detector has lower probability of detection as compared to the proposed
detector. The performance of energy detector is characterized by Receiver Operating curves usually.
AOC (Area under the Receiver Operating curves) is used to analyze the performance of the energy
detector method over Nakagami fading channels. Results showed that a higher value of fading
parameter leads to larger average AUC, and

Taguchi's Design Of Experiments Analysis
In the present study two types of methodologies have been effectively utilized to conduct the
experiments in a scientific manner, one is Taguchi's Design of Experiments (DOE) and other method
of design of experiments were based on randomly selected combination of cutting process
parameters is shown below figure. Previous literature a chapter has involved that Azmi and Lin et al.
investigated the machinability of uni–directional glass fiber reinforced (GFRP) composites [42, 60].
Recently, some of investigators have stated experimental results based on parametric studies to
evaluate the surface quality characteristics such as machining force, surface roughness and
delamination damage [31,34,38 112,113,114,115,116,117,118,119,120,121, and ... Show more
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4.2. Design of Experiments (DOE) Over 60 to 70 % of machined products have been rejected due to
lack of attention in machinability evaluation before machining. This may be lead to indirect affect
on cost–effective escalation in production industries. Therefore, predicting the outcome by
introducing a change of the preconditions and this will be reflected on the results. Taguchi's DOE
would be more effective and acceptable tool for technical investigations. The desirable
machinability evaluation thoroughly obtained by statistical design of experiments (DOE). Reliable
results also would be obtained by full factorial or partial factorial technique. 4.2.1 Taguchi method
Taguchi methods have been widely used in scientific and engineering design. This technique is
focusing to formulating the performance characteristics of parametric settings with deviation [127,
128]. In this methodology, the experimental settings (DOE) are arranged systematic as per
orthogonal array (OA) that can be reduced wastage of time and minimize the number of experiments
[129]. The effect of different factors on the performance characteristics in a given combination runs
can be examined by using the orthogonal array (OA). Simultaneously OA experimental design will
also provides a number of input factors to permit the study of their effects and interconnections with
the experimental output. Taguchi optimization technique involves to

Optimization Of Processing Parameters By Using Taguchi Method
An Overview of Optimization of Processing Parameters by Using Taguchi Method
Iqra Najib (2013–PE–16)
Mommna Munawar (2013–PE–––)
Email: usmannajib942@gmail.com
Department of Polymer and process Engineering
University of Engineering and Technology Abstract
Taguchi method is used to find best process parameters and improved quality results. Taguchi
technique/method investigates the variation in experiments and generally approach of system,
acceptance aims and parameters have been significant in improving product quality worldwide.
Highest possible performance in this method is obtained by determining the optimum combination
of design factors. The present work focused by using orthogonal arrays (OA) and analysis of
variance (ANOVA). Orthogonal arrays are used to get optimal values with the effect of graphs and
analysis of variance was employed to investigate the characteristics and experimental results
provided the effectiveness of this approach. This technique has improved quality of design and
shorten the design cycle.
Keywords: Taguchi method, orthogonal array, Analysis of variance, S/N ratio, warpage and sink
marks.
Introduction
Taguchi method is the statistical technique used to study the or developed to enhance the quality of
manufacturing goods and more recently applied to many fields like biotechnology, advertising,
marketing and engineering. Professional statisticians have welcomed the goals and improvements
bought by this method and also we can study variations in

Essay On Multi Diversity Techniques
The combining diversity techniques are used to increase the performance of wireless or wired
communication system by collected all the uncorrelated faded signal from different diversity
branches and combine them all in such a way that improve the communication system and in results
gives the optimize received signal power and signal to noise ratio (SNR). Depending on the
sophistication of the system, the signals can be added directly (equal gain combining) or weighted
and added coherently (maximal–ratio combining). Such a system provides the greatest resistance to
fading but since all the receive paths must remain energized, it is also consumes the most power.
5.1 MAXIMAL RATIO COMBINING (MRC)
Maximum ratio combining technique requires ... Show more content on Helpwriting.net ...
In the normal process of equal gain combining each individual signal branch is coherently combined
but some noise component added non–coherently. As compare to the other combining diversity
techniques maximum ratio combining is the expensive technique to use because it needs a very
expensive design at the receiver to adjust the gain in every branch. However equal gain combining
uses a simple phase lock summing circuit which is very easy to implement.EGC can engage in the
reception of diversity with coherent modulation. As in EGC the diversity branches are combined
with equal gain but they have conjugate phase. The structure of equal gain combining is shown as
below:
5.3 SELECTION COMBINING:
Selection combining is used fir very high frequency and ultra high frequency as maximum ratio
combing and equal gain combing is not suitable to work under these high frequencies because
tracking performance is not easy in a frequency changing or multipath fading. A simple
implementation procedure is used in selection combining and is more beneficial then maximum
ratio combining and equal gain combining. In this technique the highest signal level branch is
selected. In short selection combining is used to look after all the diversity branches and

The Channel Satellite And Mobile Communications Arm
Abstract The characteristics of the channel satellite and mobile communications arm is an important
and fast–growing wireless communications and play an important role in the transfer of information
through the media of spread from the transmitter to the receiver with the minimum error rate.
Information transmitted from mobiles using satellite space channel suffers from attenuation in
amplitude and phase difference caused by multipath which is affected by the environment. These
disabilities are described in the channel usually by the phenomena that characterize signal
propagation in different environments such as urban areas. A different factor which take into
consideration to evaluate performance represented additive white Gaussian ... Show more content on
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Why is this renaissance happening now? What exactly will the systems do for customers? Why are
so many smart people and companies throwing such enormous amounts of capital into the sky? And
what do these systems mean for terrestrial operators? These are some of the questions we aim to
answer. The renaissance of satellite communications: Satellites have been used in
telecommunications since the mid–1960s. For a decade or so, they carried the bulk of international
telephone calls, which they still do on routes to small and developing countries. In addition, VSAT
(very small aperture terminal) networks provide essential communications for large companies, big
ships, and disaster relief. But the use of satellites on any wider scale has been ruled out by their
traditional disadvantages (high cost, expensive and bulky terminal equipment, and annoying delays
in voice transmission), and by advances in competing media such as undersea fiber–optic cable. The
signs now, however, are that satellites are about to emerge as a powerful force in communications,
as they have already done in television broadcasting. Three factors explain why: Technological
advances are improving the price/performance ratio of

Telephone Channels Have A Signal-To-Noise Ratio Analysis
Lienphuong Nguyen
Professor: Laura Ingraham
Dec 6, 2014
Assignment 2 (Chap 6, Thought Question #2)
Telephone channels have a band–width of about 3.1kHz
Television Channel 's signal–to–noise ratio is 1000
The signal strength is 1000 times larger than the noise strengths.
Telephone modems operate at about 30kbps.
C= B[log2 (1 + S/N)]
a)
B 3.1 (kHz) S/N 1000 log2 (1 + S/N) 9.97 C 30.90 (kbps)
b)
B 3.1 (kHz) S/N 10000 log2 (1 + S/N) 13.29 C 41.19 (kbps)
c)
B 4 (kHz) S/N 1000 log2 (1 + S/N) 9.97 C 39.87 (kbps) d) We can increase the Maximum possible
speed by increasing Signal–to–noise ratio or increasing channel's bandwidth. However, increasing
the channel's band–width is more efficient in ... Show more content on Helpwriting.net ...
Finally "Rogue Access Points" are the access points which are set up by a department or an
individual for some reasons. These Rogue access points are unsecured, so the "drive–by–hacker"
can have an entry points to the network. This is really dangerous because only one Rogue access
point can make the network in threat of hacker although you protect all of your official access point
very well.
Although there are many threat of WLAN, you still can reduce those threats by applying some
technology in your network. For example, you can use a Core Security Standard. It provides
protection, which are confidentiality, authentication and message integrity, between the wireless
access point and the wireless host. Furthermore, you also can use Wired equivalent privacy (WEP)
security. In WEP, everyone shares the same access point, which requires the same key, and WEP's
key is not automated mechanism for changing. On the other hand, Wireless Protected Access (WPA)
is also an option for you. WPA is developed by using the concept of Core security standard, so it
could be used on older wireless access points and it is stronger than WEP. Finally, 802.11i is another
solution for your concerns about the network security. 802.11i is considered as WAP2, and it uses
extremely strong AES–CCMP encryption, which has 129–bits keys and a key management method
for automatically changing keys. That's all about the

This optical amplification is started from some emission...
This optical amplification is started from some emission but it is not exposed yet until Albert
Einstein proposed in 1916. After that, the things became more seriously after 1954 when Townes
and Arthur Schawlow also with Gordon Gould proposed laser action, then not long after 4 years, in
1960, first laser was build by Theodore Maiman. Besides that, Gordon also derived the word laser
from "light amplification by the stimulated emission of radiation". The laser developer look
amplification is very important as a step to build a laser, so these people make one advance to
develop amplifiers from semiconductor laser to be used as light sources. This is because of
semiconductor have high gain. Laser made up with high gain and low noise is ... Show more content
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This is because maybe due to this erbium doped fiber amplifiers can amplify signals at the low loss.
This type also is suitable to be use in long–haul and have low noise. Besides that, it also have wide
spectral band amplification and it is manly useful for WDM application and it's have relative flat
gain (> 20 dB). In contrast, there are some disadvantage using this type which is includes it is not
easily integrated with other devices because it is relatively large device (km length of fiber).
Diagram 3 : A Erbium doped fiber Amplifier
The Optical gain in Optical amplifier can be defined as the ratio of the optical signal power at the
input to the optical signal power at the output. This can de also shown by the formula ;,
G = Pin Pout
The gain is basically measured in dB and exist in the range of the 10 until 30 dB.
Noise figure is the measure of the signal–to– noise ratio between input and output of the component.
In other words, Noise Figure (NF) . It is a measure of how much a devices such as amplifier
degrades the signal to noise ratio (SNR). During amplification process, noise exist, so the output
signal is always noisier from input signal. So, in order to get better performance of optical amplifier,
Noise figure should be kept as low as possible.
Noise Figure , [dB] = 10 log10 (SNRin

Tone Injection Essay
This technique increases the constellation size so that each of the point in the original basic
constellation can be mapped into several equivalent points in the expanded constellation. Since
substituting a point in the basic constellation for a new point in the larger constellation is equivalent
to injecting a tone of the appropriate frequency and phase in the multicarrier signal, therefore, this
technique is called tone injection. The extra degrees of freedom, which is generated as each symbol
in the data block can be mapped into one of the several equivalent constellation points, can be
utilized for peak to average power ratio reduction. The distance between the original and extended
points is D. The receiver remains unaltered. D is ... Show more content on Helpwriting.net ...
Various works are available in literature mainly focusing on complexity reduction of optimization
problem. A gradient algorithm is proposed where the gradient of clipping noise mean square error is
calculated and optimization of signal to clipping noise ratio is done in place of peak to average
power ratio and order of complexity is O(N). A truncated IDFT algorithm is proposed where in place
of calculating entire IDFT values, it calculates on maximal IDFT element thus reducing complexity
of optimization process. The basic idea is to divide the group in two halves of N/2 and leave the half
with lesser energy and move in similar way till we reach the maximum energy element, however
this scheme may not always give correct maximal IDFT element, it also costs in lower peak to
average power ratio reduction. For designing the peak cancelling signal clipping noise is analysed
and several iterations of clipping and filtering are used till desired peak cancellation signal is
generated. References also proposed an adaptive–scaling algorithm and constant–scaling algorithm
for tone reservation. LSA–TR method with fast convergence is proposed which is based on least
square approximation and used to find the peak cancelling signal faster than clipping control TR
method. References used genetic algorithm to find the optimal PRC set, it also discussed an adaptive
amplitude clipping tone reservation algorithm (AAC–TR) to solve the optimization

Types Of Sigma Delta Modulators
Abstract This thesis investigates several types of Sigma–Delta modulators in different conditions as
a possible solution to the all–digital audio and wifi signal receivers. In this research, two main
approaches are under consideration. Oversampling is a technique to design a sigma–delta
modulators. Undersampling(or subsampling) is an interesting technique which allows the sigma–
delta modulators to sample high frequency signals such as WIFI and GNSS signals. Time–
interleaving modulation is another way to implement  modulators in high frequency domains.
Acknowledgement I would like to thank to Professor Izzet Kale for his support and help throughout
my study. I am really grateful to Professor Andrej for being such a nice course leader and full
support for my study. I am also thankful to several professors who taught me at Pyongyang
University of Science and Technology, especially Professor Chon Y.T. and Professor Eigenbarth
who no longer teaches but gave a great help understanding DSP and project research experience. I
appreciated all my colleagues for being such a help to my project. Table of Contents Abstract
Acknowledgement List of Figures List of Tables List of Abbreviations Chapter 1. Introduction Aims
and motivations 1.2 Contributions 1.3 Scope of research Chapter 2. Principles of Sigma Delta
Modulation 2.1 Key parameters for performance evaluation 2.2 Sigma delta modulators for audio
frequency 2.3 Undersampled Sigma Delta Modulators for high frequency

Design Of Continuous Time Second Order Sigma
Design of Continuous Time Second Order Sigma–Delta Modulator Using Feedback Element Mr.
Ravinder Choudhary University Institute of Engineering and Technology Kurukshetra University
Kurukshetra, India E–mail– erravindera@gmail.com
Abstract: This paper discuss the continuous time second order Sigma–Modulator with the feedback
element having negative feedback. The modulator is of second order that decreases the complexity
of the circuit and also decreases the power consumption of the circuit. The circuit works on the
analog input signal in the form of jitter sine wave. The feedback element generates the feedback
pulse. An efficient
Sigma–Delta modulator is designed with the bandwidth of 10 MHz and sampling frequency of 350
MHz. The modulator is designed using a Matlab code and the circuit is then designed on
SIMULINK. The evaluation indicates that the second order modulator achieves 73.5 dB peak SNDR
and 73 dB of peak SNR.
Keywords: Delta–Sigma Modulator, SNR, SNDR, Dynamic Range
1.INTRODUCTION
In electronics and telecommunications, modulation is the process of varying one or more properties
of a periodic waveform, called the career signal, with a modulating signal that typically contains
information to be transmitted. In telecommunications, modulation is the process of conveying a
message

Intermediate Precision Lab Report
4.7 a – Intermediate Precision In practice the laboratory is usually interested in the extent of
variability that occurs over time when it operates the method. This is called intermediate precision
and describes the variability when the method is deployed in the same laboratory, perhaps on
different pieces of equipment, and using different analysts on the staff. It is predictable that this will
give a value between repeatability and reproducibility. Sample Preparations Stock solution of
Trazodone hydrochloride raw material (10,000 ppm): Weigh and Transfer 250 mg of Trazodone
hydrochloride into 25mL volumetric flask. Add a small portion of diluting solvent (25/75% v/v
ACN/Water). Complete the volume mark with the diluting solvent (25% ACN) ... Show more
Add a small portion of diluting solvent (25/75% v/v ACN/Water). Complete the volume mark with
the diluting solvent (25% ACN) and mix thoroughly. Sonicate for half an hour and see that it is
completely dissolved. Standard solution of Trazodone hydrochloride raw material at 100 ppm:
Transfer 0.1 mL of 10,000 ppm Trazodone hydrochloride stock solution to a 10 mL volumetric flask.
Complete to volume mark with the diluting solvent and invert flask at least three times to make sure
a proper mix. Standard solution of Trazodone hydrochloride raw material at 5 ppm: Transfer 0.5 mL
of 100 ppm Trazodone hydrochloride stock solution to a 10 mL volumetric flask. Complete to
volume mark with the diluting solvent and invert flask at least three times to ensure a proper mix.
Standard solutions of Trazodone hydrochloride at 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0 ppm:
Accurately transfer the corresponding volume of Trazodone hydrochloride standard solutions
specified in TABLE XXXX, into a 10 mL volumetric flask. Complete to volume mark with the
diluting solvent and invert flask at least three times to ensure a proper

The Importance Of Seismic Data
The reliability of seismic data may influenced by different factors in the acquisition process. For
ensuring and better understanding of the reservoir characteristics, these factors should be avoided
from the seismic data. Seismic data are superposed and in the case of low signal–to–noise ratio
(SNR) sometimes completely masked by noise. To prepare these seismic data for further application,
processing, maximize the potential benefit, and contribution of the seismic data in exploration and
development, we need to improve the SNR by attenuating noise and preserving important features
of seismic data. Different methods have been proposed for denoising and preserving different
features of seismic data depending on the nature and assumptions ... Show more content on
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In NLM denoising algorithm the image is divided in to different repeated small patches. The noise
can be removed and important features of the data preserved by taking advantages of the redundant
information of patches. It achieves a promising result by averaging local neighborhood pixels with
the similarities of the redundant patches. Each pixel of the image adjusted with a weighted average
of other pixels whose neighborhoods has similar geometrical configuration. During noise
attenuation method NLM algorithm also retain some important features of seismic data.
Different methods have been proposed in the field of natural image and seismic data processing for
better noise attenuation of original NLM algorithm in terms of patch size, smoothing parameter,
developing new weight function, and computational complexity. For the task of patch similarity
measure, different weight functions have been proposed. To measure the patch similarities of noisy
data based on the statistical distribution of noise, the NLM depends on Bayesian frame work
proposed citep{Kervrann et al.}. citep{Tasdizen et al.} also proposed a new method to measure the
patch similarity in the domain of principal component analysis which depends on transform domain
method. Adaptive NLM algorithm citep{Shang et al., Jing and Yu, Dinesh and Ramya} have been
proposed to

Description Of The Hpge Gamma Ray Spectrometer
) Description of the HPGe gamma–ray spectrometer
A high resolution gamma detection system was used for gamma analysis. This system consist of an
ORTEC hyper pure germanium detector (HPGe), model number GEM– 15190, coaxial type detector
with a serial number 27–P–1876A recommended operating bias, negative 3 Kv. The detector used
has crystal diameter 49.3 mm, and crystal length 47.1 mm. The HPGe detector has a full width at
half maximum (FWHM) 0.9 keV at the 122 keV gamma transition of Co–57 and 1.9 keV at the
1332.5 keV of Co–60 gamma transition (Knoll, 2000). The detector has peak to Compton ratio
about 44 keV. Compton ratio is the number of net counts in the 1.33 MeV peak channels divided by
the average number of net counts in the channels representing the range from l.040 through 1.096
MeV which is part of the Compton region associated with the 1.33 MeV peak. Figure (2.5) show the
block diagram of gamma ray spectrometer.
The range of the multi channels analyzer (MCA) was adjusted to include the peak channel and the
range of interest in the Compton plateau (Madelung, 1991), (EML, 1990). High purity germanium
(HPGe) coaxial detector uses p–type material with lithium diffused outer contact. The inner contact
is ion implanted for the ultimate in reliability. Because of the small band gap (0.7eV) room
temperature operation of germanium detector of any type is impossible because of the large
thermally induced impossible because of the large thermally induced leakage current

The Concept Of Perpendicularity
Perpendicularity Perpendicularity is a member of the orientation family. It can be used to control the
orientation of surface, axes and center– planes. If used on features of size, it is often used as a
refinement of, or to augment a positional control. It is also often used to orient secondary datum
features of size to primary plane datum. Perpendicularity is a characteristics of orientation applied to
a feature or feature of size wherein that considered feature surface, line element, median plane or
axis is being controlled (to within a specified tolerance) 90° to a datum plane or datum axis.
Perpendicularity is a common symbol that requires the referenced surface or line to b perpendicular
or 90° from a datum surface or line.
Taguchi method ... Show more content on Helpwriting.net ...
This method is a unique and powerful statistical experimental technique, which greatly improves the
engineering productivity. For present study, identifying the product the product parameter values
under the optimal process parameter values and the objective of the parameter design is to optimize
the settings of the process parameter values for improving performance characteristics. Therefore
the parameter design is the key step in the Taguchi method to achieving high quality without
increasing cost. Traditional Design of Experiments focused on how different design factors affect
the average result level. In Taguchi's DOE (robust design), variation is more interesting to study than
the average.
Robust design: An experimental method to achieve product and process quality through designing in
an insensitivity to noise based on statistical principles. A statistical / engineering methodology that
aim at reducing the performance "variation" of a system.
The input variables are divided into two board

ADC Lab Analysis
The INL shown in figure 3.4 describes the overall shape of an ADC transfer characteristic from the
straight line drawn between end points after both the offset error and the gain error are nullified. The
INL is mathematically given [36] as ; ........................................(3.5)
3.1.1.4 Resolution
The resolution is defined as the number of output bits of an ADC. The resolution of n–bit ADC
defines how many parts the maximum signal can be divided into. The resolution is calculated by the
formula 2n. The flash ADC is used for low resolution applications.
3.1.1.5 Conversion speed
The amount of analog input converted by an ADC in one second is known as the conversion speed.
3.1.1.6 Quantization error
After sampling of the signal the conversion of the ... Show more content on Helpwriting.net ...
Effective number of bits (ENOB)
[4]. Total harmonic distortion (THD)
[5]. Spurious–free dynamic range (SFDR)
3.1.2.1 Signal–to–noise Ratio (SNR)
The ratio of signal power to noise power is known as the signal–to–noise ratio (SNR). It is also
known as signal to quantization ratio (SQNR). The signal–to–noise ratio determines how much
noise in an ADC. Mathematically the SNR is given [34] as ;
Mean square value of quantization error = ∆2/12
If the input signal is (A. Sinωt), then signal power = A2/2
Full scale range for an n–bit ADC = 2n∆
Amax = 2n–1 ∆
Maximum signal power = ((2n–1 ∆)2) / 2
Noise Power = ∆2/12
Peak SNR = (((2n–1 ∆)2) / (2* ∆2/12)) = 3. 22n–1
SNR = 20 log10 (ARMS,signal / ARMS,noise)
SNR in decible = 10 log10(3. 22n–1)
= (6.02n + 1.76) dB .............................................................(3.7)
Where, ARMS,signal = Root mean square (RMS) amplitude for the signal. ARMS,noise = Root
mean square (RMS) amplitude for the noise.
3.1.2.2 Signal–to–noise and Distortion ratio (SINAD)
The signal–to–noise and distortion ratio (SINAD) [40] is defined as the ratio of the signal power and
to noise power including the significant harmonics. Since the signal–to–noise ratio (SNR) does not

include the significant harmonics, the SNR is usually larger than the SINAD. SINAD is
mathematically given as ;
SINAD = 20 . log10 ( ARMS,signal / ARMS,noise + harmonics ) dB ..................(3.8)
3.1.2.3 Total Harmonic Distortion (THD)
The ratio of noise power ( only the

Comparative Analysis Of Adaptive Threshold Based Spectrum...
Comparative Analysis of Adaptive Threshold Based Spectrum Sensing Techniques in Cognitive
Radio Networks
Abstract:–In the last two decades, the number of wireless communication users and its applications
increasing rapidly. With this rapid growth there exists spectrum scarcity. One of the best solutions to
avoid spectrum scarcity is cognitive radio with its dynamic spectrum sensing. Cognitive radio is a
promising technology, which is used to sense the unused spectrum in an appropriate manner. Various
methods have been proposed in the past, such as energy detection, matched filter and so on [1 6 7].
Different techniques serve different purpose based on their advantages and disadvantages.
In this paper, the author suggests an approach of dynamic threshold to increase the probability
detection of spectrum sensing. Spectrum sensing using energy detection, matched filter detectors
based on fixed threshold and dynamic threshold are simulated using MATLAB. The performance of
energy detection, matched filter detector is compared by plotting probability detection versus
signal–to–noise ratio graph.
Keywords:–Spectrum Sensing, Cognitive Radio, Wireless Communication, Energy Detection,
Matched Filter, Probability Detection and Threshold.
I. Introduction:–The recent trend in cognitive radio–related research has altered s great of deal of
interest in spectrum sensing and detection of radio users in the environment [5]. In general, the
spectrum user signals are categorized into primary

Nt1310 Unit 5 Application Of Research Paper In Mis
MULTIPLE INPUT MULTIPLE OUTPUT (MIMO)
In MIMO system there is multiple antennas is provided at the transmitter side as well as receiver
side. Using multiple antennas at the transmitter and the receiver side could able to increase spectral
efficiency, produces higher capacity and provides more data rates for wireless communication. In
MIMO system there is SU–MIMO that is called single user MIMO in which when there is data rates
need to be increased for single user then it is known as SU–MIMO, and if there is individual stream
is allocated to multiple users; then it is called multiuser MIMO (MU–MIMO).
In MIMO system, let's consider there is Mt transmitting antenna and Mr receive antennas where s=
[S1, S2......SM] t is the transmitted data vector, ... Show more content on Helpwriting.net ...
Functions of MIMO
The main function of MIMO system includes precoding, spatial multiplexing and diversity coding.
Precoding is the process of multi–stream beamforming which process at the transmitter. The main
advantage of multi stream beamforming is to increase the received signal input, by making signals
emitted from different antennas add up constructively and it is also able to mitigate the multipath
fading effect. Precoding requires channel state information at the transmitter. When there is multiple
antennas at the receiver, the transmit beamforming cannot simultaneously maximize the signal level
at all the receive antennas, and precoding with multiple stream is used. MIMO antenna
configuration is requires in spatial multiplexing. In spatial multiplexing the high rate signal is divide
into low rate signals and each individual stream is transmitted from different transmit antenna which
is having the same frequency channel. Spatial multiplexing is technique which is capable of
increasing channel capacity at higher signal to noise

Controversy About Having A HDTV Antenna
There has been a lot of hype lately about having a HDTV antenna. Is it just hype or should you
really get it?
First, what is the hype about having a HDTV antenna? The hype is that with the antenna, you can
watch 1080i resolution broadcasts and will get better quality than satellite TV. The truth is going to
hurt if you already have bought a HDTV antenna. There is really no such as a HDTV antenna.
HOW AN ANTENNA WORKS
All an antenna does is pick up frequencies. The frequencies that you pick up for your TV are Ultra
High Frequencies (UHF) and Very High Frequencies (VHF). All TV broadcasts take place in the
VHF and UHF bands. High definition can be part of these frequencies and you do not need a special
HDTV antenna to pick them up. Your regular antenna could do the job just as well. ... Show more
They must have directivity, high front–to–back (F/B) ratio and low–noise amplification when the
antenna has an amplifier. If they have the same properties, why pay more to get something that is the
same?
People have this perception that they need a more powerful HDTV antenna because of directivity
and amplification. This is not true. HDTV is actually more noise immune than analog television and
will be able to produce high quality video at significantly lower signal–to–noise ratios. Digital TV
needs less antenna gain and can tolerate higher noise levels. A HDTV antenna and a regular antenna
have similar directivity/gain properties so you should receive analog or digital broadcasts with the
same good quality.
GHOST

Limitations Of Wireless Communication
INTRODUCTION
There are lots of challenges occurs for reliable wireless communication which occurs due to
physical limitations of the wireless medium. There has been massive growth occurs in wireless
communication which is due to the techniques that improves spectral efficiency and mitigate various
channel impairments such as fading and interference. Moreover there is always demand for high
speed wireless internet and technologies which are capable of providing higher capacities and link
reliabilities. Multiple–input–multiple–output (MIMO) is based on communication system which is
able to fulfil these objectives. MIMO is an expansion of smart antennas systems. There were
traditional smart antennas which occupy multiple antennas at receiver, whereas In MIMO system
multiple antennas are engaged at both sides at transmitter as well as receiver side. The multiple
antennas at the transmitter and the receiver side provide a major advantage over traditional smart
antenna systems–in terms of capacity and diversity advantage. The multipath propagation by MIMO
system is a remarkably advantage over other antennas system. Moreover it is able to provide
independent fading channels between every pair of transmitter and receiver antennas.
The rapid improvement in communication system with high data rates and improved channel
capacity has pondered towards the study of both theoretical and practical in wireless communication
systems. Wireless communication system has made great effort to

Signal to Noise Interference Ratio
A measure of quality of service in a wireless connection is made using SINR (Signal to noise
interference ratio).For the performance evaluation let us consider a an overall network t to be
composed of two–tier 19 macrocells, with many femtocells randomly deployed over the macrocells.
Then the macro user would be interfered from neighbouring macro cell's (18) and all of the adjacent
femtocells. Due to small transmit power, only femtocells which would be located in the 1–tier
macrocell area gives interference to macro user. The estimation of the received SINR of a macro
user m on subcarrier k, when the macro user is interfered from neighboring macrocells and all the
adjacent Femtocells [12] would be given by
where P_(M,K) and P_(M^1,K) is transmit power of serving macro–cell M and neighbouring
macrocell
M' on subcarrier k, respectively. G_(M,m,K) is channel gain between macro user m and serving
macrocell M on subcarrier k. Channel gain from neighbouring macro cells are denoted by
G_(M1,m,K) Similarly, P_(F,K) is transmit power of neighbouring femtocell F on subcarrier k. .
G_(M,F,K) is channel gain between macro user m and neighbouring femtocell F on subcarrier k. N0
is white noise power spectral density, and f is subcarrier spacing [12].
Following the above description in the case of femto users, they would be interfered by all 19
macrocell users and also from the adjacent femtocells, this case is similar of a femto user f on
subcarrier k interfered by all

Clinical Characteristics Of MRI Data
All MRI data were processed blind to the order of scan acquisition (baseline or week 10), treatment
assignment, and participant clinical characteristics. Anatomical MRI We applied automated tools to
correct for large–scale variations in image intensities30 and to remove extracerebral tissue31. We
then removed connecting dura manually on each slice in the sagittal, axial, and coronal views. We
first coregistered all participant brains to an initial template using a similarity transform that
maximized mutual information32 and then applied a high–dimensional, nonrigid fluid–flow
algorithm33 to warp each brain to the exact size and shape of the template brain. Brain tissue was
segmented as gray and white matter with a semi–automated method ... Show more content on
Helpwriting.net ...
We applied spectral fitting to the frequency–domain signal to identify peaks for N–acetyl–aspartate
(NAA), creatine+phosphocreatine (Cr), choline–containing compounds (Ch), and
glutamate+glutamine (Glx). We modeled the spectrum for those peaks with Gaussian–Lorentzian
curves, which were fitted to the data using a least–squares curve–fitting routine. The areas under the
fitted curves estimated concentrations of the metabolites in each voxel of the brain. We performed
quality control of the data by visually assessing the spectrum in each MRS voxel and rejected data
from voxels with strong lipid contamination, insufficient suppression of residual water, unresolved
Cr and Ch peaks, or full width at half maximum > 12 Hz for the peaks. We then computed
background noise for the MR spectrum as the standard deviation of the real part of the complex
spectrum free from the metabolite signal, and then computed the signal–to–noise ratio (SNR) for
each metabolite level. The average SNR for NAA was greater than 280, an excellent SNR
attributable to use of the 8–channel head coil. We then generated a spectroscopic image (SI) for each
metabolite as the ratio of peak area to background noise for each MRS voxel in the brain. Taking the
ratio of the peak area to the background noise accounted for variations in receiver and transmitter
gain across scans. We subsequently processed the spectroscopic images to correct for both partial
volume effects within each MRS voxel and the dispersion

Smart Antenna System Essay
INTRODUCTION
1.1 Antenna Systems:
Depending on the number of antennas used in the transmitting and receiving sections, the systems
are divided into 4 types.
1.1.1 SINGLE INPUT SINGLE OUTPUT (SISO): Fig 1.1.1: SISO
In SISO, there will be only single transmitter and a single receiver. This is the general system which
we use. The simplest antenna technology is SISO. In some environments, this system is vulnerable
to problems caused by multipath effects. When an electromagnetic field (EM field) is met with
obstructions such as hills, buildings, utility wires, and canyons the wavefronts are scattered, and thus
it take multi paths to reach the destination. Fading, cut–out (cliff effect), and intermittent reception
(picket fencing) are the problems caused by late arrival of scattered portion of signals. In a digital
communications system, it cause a reduction of data speed and number of errors is increased.
In order to eliminate or minimize problems caused by multipath wave propagation, a new
technology has been introduced and it is Smart Antenna Technology. There are three forms of smart
antenna, known as SIMO (single input, multiple output), MISO (multiple input, single output), and
MIMO (multiple input, multiple output).
1.1.2 SINGLE INPUT MULTIPLE OUTPUT (SIMO) : Fig 1.1.2 : SIMO
In SIMO, there will be only single transmitter and many receivers.
1.1.3. MULTIPLE INPUT MULTIPLE OUTPUT ( MISO): Fig. 1.1.3 : MISO
In MISO there will be multiple transmitters and a

Essay On Second Time Slot
Y2 1= h11 (–X2*) + h12(X1*) + n21 (second time slot receive data in RX1) (9) Y2 2= h21 (–X2*)
+ h22(X1*) + n22 (second time slot receive data in RX2) (10) Equation (7), (8), (, 9) and (10) can
also be written as matrix form the received vector in first time slot is [■(Y_11@Y_12 )]=
[■(h_11&h_12@h_21&h_22 )] [■(X_1@X_2 )]+[■(n_11@n_12 )] (11) The received vector in
second time slot is [■(Y_21@Y_22 )]=[■(h_11&h_12@h_21&h_22 )][■(〖〖–X〗_2^*〗_ @
〖X_1^*〗_ )]+ [■(n_21@n_22 )] ... Show more content on Helpwriting.net ...
MRC is as method of diversity combining. MRC multiplied the all branches signal. MRC amplified
higher amplitude signal but shrink the low amplitude signals. It is also add the signal from each
channel and gain of each channel is made directly proportional to the RMS signal value and
inversely proportional to the mean square noise value in that channel. Each channel is different. It is
known as RSC (ratio–squared–combining) and PC (prediction combining). MRC is also known as
optimum combiner and it is independent of AWGN channels. It can achieved high bit error rate
when MRC is used in multi input multi output receiver. The least square solution in this case is also
known as maximal ratio combining. In the case of two antennas the least square solution can be
written as equation (14) X ̂= (h_1^**Y_1+h_2^* Y_2)/(〖|h〗_1^2 |+|h_2^2 |) (14) IV.
MODULATION If the digital modulation modulates the incoming data BPSK (Binary phase shift
keying) modulation is used. Encoding of M massage bits single pulse transmit 2M possible time
shifts. Transmit bit rate M/T (bit per second) is replicate after every T second. This paper BPSK
modulation scheme is used. V. COMMUNICATION CHANNEL Communication channel is
medium to transmit the

Tamba Performance Evaluation
I produced a mix of Summertime as performed by the band Tamba as part of the second module.
There were a number of issues during the recording, such as self noise from the right overhead
microphone, a substantial amount of bleed being picked up from each microphone, the balance of
the ensemble, in particular the relative lack of signal of the piano, and the harshness of the singers
last note. In order to keep my project in a logical order, I placed the vocals at the top of my
arrangement, and the drums at the bottom. I ensured that I colour coded each track according to the
instrument, for example each of the drum tracks were the same colour. I also sent each track through
a bus, which gave ensured that if the entire mix needed the gain adjusting, ... Show more content on
Helpwriting.net ...
On these tracks, I set the makeup gain to approximately +5.0 dB in order to give certain instruments
more presence in the recording. There was also considerable distortion in the last note of the chorus,
so the use of the threshold of compressor also minimised this. A compressor diminishes the dynamic
range of a signal and allows you to increase the overall volume. There are six major components of
a compressor: the threshold, ratio, attack, release, gain and hard or soft knee. The threshold refers to
the level in which the compressor begins to act upon the signal, and the ratio is the amount that the
compressor affects the signal. The ratio is portrayed as a proportion such as 3:1, which means that if
the input level is 3 dB over the threshold, the output signal will be reduced to 1 dB. The highest ratio
is ∞:1, which is known as a limiter, which is also efficiently done at a ratio of 60:1. A limiter brings
any signal over the threshold to be brought done to the threshold level, with the exception of sudden
increases in the input loudness. The attack controls how soon the compressor kicks in, the release
controls how long the compressor continues affecting the signal after it has dropped back below the
threshold, and the gain allows you to adjust the level of the signal going out of the compressor. Hard
or soft knee are both angles of compression and its desired

Simulated Results And Analysis Of A Ver Of The System
All rotated symbols are fed into a decision circuit and the squared distance |dk,b|2 to the closest
constellation point is calculated in the complex plane:
|d_(k,b) |^2=|Z_k e^(jφ_b )–X ^_(k,b) |^2 (4.12)
Where Xk,b is the decision of Zkejφb. After the DSP compensation for the optical fiber linearities
the signal is passed through the threshold detector (Decision) and at the QAM decoder to decode the
original signal transmitted. The two QAM decoder for the X–polarization and the Y–polarization bit
sequences are finally passed through the parallel to serial converter and the BERT (Bit Error Rate
Test) to calculate the average BER of the system. The average BER calculated is used for the
analysis of noise i.e the phase noise and ... Show more content on Helpwriting.net ...
Further analysis of DP 16–QAM has been done in terms of average Bit error rate(BER) and optical
signal to noise ratio(OSNR) in order to analyse the Phase noise and Gaussian noise.
In the proposed design sweep iterations has been used in the optical signal to noise ratio (OSNR)
component and the BER TEST SET component. On using the feature of the simulator in order to
make nested parameters, and thus obtaining the required average BER. With the higher order 16–
QAM it is not easy to decide the filter to be used having minimum noise so graph have drawn
between Average BER versus OSNR.
The graph is taken before carrier phase estimation (CPE) in order to analyse the Phase Noise. The
required graph for phase noise in terms of average BER for different filter types with varying filter
order are drawn in Figure 4.7(a)–(d). The graph is drawn between the average BER and OSNR
which shows that with the increase in OSNR the BER decreases. In another way with the increase in
noise the average bit error rate increases. There is a value fixed theoretically for each modulation
technique above which OSNR cannot be permitted in the system. Figure 4.7(a) Butterworth filter
4th order before CPE Figure 4.7(b) Chebyshev filter 3rd order before CPE Figure 4.7(c) Bessel filter
3rd order before CPE Figure 4.7(d) Gaussian filter 3rd order before CPE Figure 4.7(a)–(d) shows
the graph drawn between average bit error rate and the

Ntx10 Unit 4
Question 1: Given an amplifier with an effective noise temperature of 10,000 K and a 10– MHz
bandwidth, what thermal noise level, in dBW, may we expect at its output? Answer: Noise =
kTemprature X Bandwidth , n= kT X B k = 1.38x10^ –23 J/Kelvin, T = 10,000 degrees Kelvin B =
10 MHz = 10X10^6 Hz, After calculating we get N = 1.38X10–12 Watts From the formula, we
know that Ndb = 10 log (KTB) NdBW = 10 log N = –118.6 dBW Or NdBmW = 10 log N*1000 = –
88.6 dBmW = NdBmW = NdBW + 30 Question 2: What is the channel capacity for a teleprinter
channel with a 300– Hz bandwidth and a signal– to– noise ratio of 3 dB, where the noise is white
thermal noise? Answer:

Spectrum Scarcity Problem Of Wide Band
Abstract– Spectrum scarcity problems happen due to the spread of various wireless devices and
technologies engaging static frequency access and to cope up with this demand, Cognitive Radio is a
solution of enormous outlook. This article discusses spectrum scarcity problem in wide band. To
solve high sampling rate problems in wide band, compressive sensing is done here.A wide band
signal is passed through fading channels and then it is estimated using ℓ1 magic technique. Then
receiver–operating characteristic curve of the evaluated signal is estimated.
Keywords: Fading channel,ℓ1 magic technique, receiver–operating characteristic curve.
I.INTRODUCTION The expanding demand for wireless affinity and current congestion of
unlicensed spectra has pushed the authoritative agencies to be more hopeful in providing new paths
to adopt spectra [1]. The reason behind this is the increasing interest of consumers in wireless
services which in turn is driving the evolution of wireless networks toward high–speed data
networks [2]. The traditional path to spectrum management is very immutable because each operator
is acknowledged an exclusive license to operate in a certain frequency band. Though, with most of
the useful radio spectrum already designated, it is becoming enormously tough to find unfilled
bands to either utilize new services or strengthen existing ones [3].
Main theme of the complete operation of Cognitive Radio (CR) systems

The Effect Of Detector Voltages
Finally, the detector voltages were optimized to obtain the best sensitivity for target compounds.
Here, the S/N value was used to measure the effect of detector voltage on the sensitivity, because
both the peak signal and noise signal increase with detector voltage. The effect of detector voltages
(1.65, 1.70, and 1.75 kV) on several representative compounds is shown in Figure 5. With
increasing voltage, the trends of S/N values for different compounds are different, but that of each
class is basically the same. Overall, the sensitivity of nearly all the compounds decreases with
increasing voltages, and with the fact that higher voltage accelerates the aging of the detector, 1.70
kV was chosen in this study.
Screening of potential risk ... Show more content on Helpwriting.net ...
The group classification of components was then performed by the facilities of ChromaTOF
software to draw borderlines in the contour plot, better assisting overview and comparison of
different samples. The analytes in Sample #1 were roughly classified into six different groups
(Figure 6): 1. PAHs, 2. PAEs, 3. Phenolic compounds, 4. Hydrocarbons, 5. Benzene derivatives, 6.
Aliphatic acids. The outsiders are some compounds such as nitrogen–containing compounds, which
do not belong to the specified groups. It is worth noting that in several cases, some compounds
belonging to different groups elute in the neighboring retention times, and thus the borderlines are
not exactly correct, especially when hundreds of components are present in the chromatogram. The
peak density of each of the assigned areas allows for a primary evaluation of the composition of
each soil sample. It appears that Sample #1 has a diverse composition with higher concentration of
hydrocarbons, aliphatic acids, PAHs and PAEs, whereas Sample #2 almost exclusively contains
benzene derivatives, phenolic compounds, and PAHs. This example confirms that the group
classification is helpful to recognize the compound classes present in the sample in greater
proportion and concentration.
Based on the overview of the sample's constituents, another filter condition was added to pick out
the most abundant compounds in the soil samples. According to the

Essay On Noise Reduction
Signal Enhancing and Noise Reducing Experimental Design to Increase Quality Design and analysis
of a research study are necessary to an answer to the research problem and can be a simple two
group design or multiple variables and variable level design to collect the necessary data to derive a
supporting or opposing hypothesis (Jackson, 2011). An experiment and its design should 1) reduce
or eliminate influencing factors, 2) randomly assign the treatments and 3) use multi–level design to
increase the quality of the outcome of the research study (Wiley, 2009).
This paper will focus on the factorial and covariance or blocking designs used in complex research
studies to improve the quality of the research and its outcome
Improving quality ... Show more content on Helpwriting.net ...
An example of a factorial design would be an educational study to determine if a particular setting
delivers better test scores. The design would take on a 2x2 structure where the two factors to be
considered are 1) setting where the education takes place and 2) the length of time the education
takes place. The levels of the factors would be 1) setting is in a classroom and 2) setting is online
and time of education would be 1) four hours a week and 2) eight hours a week. The 2x2 structure
then allows for the variables to be measured against one another for outcomes. The study would
consist of four groups; 1) in a classroom for 4 hours a week, 2) in a classroom for 8 hours a week, 3)
online for 4 hours a week and 4) online for 8 hours a week. The test scores collected for each of the
four groups measure for main and interaction effects. Main effects measure at the level of the
variable, and the interaction effects measure at the factor (Jackson, 2011; Trochim, Donnelly &
Arora, 2016). In other words, the main effect would be graphically represented with the mean results
of the four groups visually showing the impact of the results in each of the groups (Jackson, 2011;
Trochim, Donnelly & Arora, 2016). The interaction effect measures the impact of the time and
setting at the factor level (Jackson, 2011; Trochim, Donnelly & Arora, 2016).
Reducing

Noise In Digital Communication
Digital communication is popular way how many people in the word communicate. Even being one
of the most popular modes of communication, digital communication still has many problems.
Digital communication is defined as communication that is transfer electrically. Digital technology
makes, stores and processes data. This data is transfer into bits. Digital communication is a very
broad field. There are different types of noises in communication and digital systems. Noise is
"variations that interface with the desired signals and inhibit communication". Professor Niknejad
stated "noise is an ever present part of all systems". Noise comes from the channels and in the
communication equipment (Brown). Most of the noise is consider undesired in most cases (Brown).
The noise is usually random (Brown). An example of unwanted noise that humans hear can be sight
hissing and humming when having a telephone conversation (Rouse). In digital communication
noise cannot be avoided entirely (Brown). Professor Niknejad wrote that "noise degrades the
throughput because it requires retransmission of data packets or extra coding to recover the data in
the presence of errors". There are three ways that noise can be reduce in communication and digital
systems (Brown). The first way is to reduce the signal bandwidth. Another way is to increase the
transmitter power. The final way to reduce noise in communication and digital systems is to use
low–noise amplifiers for weak signals.
External

The Effect Of Musical Noise Pro Duced By Ibm
verberant mixture. In 16 a minimum mean–square error (MMSE) based technique is planned to
estimate the ideal multi–threshold mask (IMM) that has been utilized in the realm of monaural
speech improvement. It contains 2 stages, specifically training stage and enhancement stage. Within
the training stage, a man–made neural network is trained by exploitation the SNR of every T–F unit
of training information. Second stage uses the calculated SNR to estimate IMM and to separate the
target speech from clamant signal.
This analysis work proposes a method to scale back the impact of musical noise pro–duced by IBM,
by planning a soft mask which might be utilized in speech separation applications. Genetic
algorithmic rule (GA) is employed during this work to search out the optimum soft mask weights
between 0 and 1. the objective measures like S/N improvement and perceptual evaluation of speech
quality (PESQ) are used to measure the performance of planned optimum soft mask with the
prevailing IBM 22 and IMM16 based speech separation systems. Rest of the paper is organized in
the following manner. Section two provides an outline of computational auditory scene analysis
(CASA). Section three presents the proposed optimum soft mask based speech separation system.
Section four provides the experimental results of IBM, IMM and also the planned soft mask. Section
five deals with the conclusion and future work.
2. Computational Auditory Scene Analysis (CASA)
CASA can be defined as the

Taguchi Method
Campus Monterrey Design and Analysis of Experiments Research TAGUCHI METHOD Fernando
de Castro Palomino Siller – A01191233 Thursday, September 17th, 2015 Professor: Héctor Rincón
CONTENT Introduction ............................................................................ 3 Why to use Taguchi
Method ..................................................... 3–4 Taguchi Method Strategy
.......................................................... 4 P–diagram .............................................................................. 5
Quality Measurement .............................................................. 5–6 Signal To Noise (S/N) Ratios
.................................................... 6–7 Static Versus Dynamic S/N
Ratios............................................... 7 Steps in Robust Parameter Design ............................................
7–8 Conclusions ........................................................................... 8 Bibliography
........................................................................... 9 Introduction ... Show more content on
Helpwriting.net ...
These investments have had great impact on the cost structure and consequently, on the bottom line
of these companies. Because of the fact that many of the companies have reached the maximum
potential of the Six Sigma approach, what would be the next step for productivity improvement?
Studies have shown that the design stage directly influences more than 70% of a product's life cycle
cost. Companies with high product development effectiveness have earnings three times the average
earnings, and have revenue growth two times the average revenue growth. These observations are
persuading more and more companies to adopt improved product development processes under
Taguchi Method. This method's approach is focused on increasing engineering productivity so that
new products can be developed rapidly and at low cost, and value based management. Taguchi
Method Strategy Variation reduction is recognized all around the world as a key to productivity
improvement. There are many approaches to reducing the variability, each one having its place in
the product development cycle. By focusing on variation reduction at the design stage, you can
prevent failures in the following stages of a product's life cycle. The Six Sigma approach has made
fantastic improvements in cost reduction by finding problems that occur in manufacturing
operations and fixing the immediate causes. The Robust

Compare Jitter, Shimmer and Harmonics to Noise Ratio in...
Compare jitter, shimmer and harmonics to noise ratio in terms of the types of information each
provides?
Jitter and shimmer are measures of the cycle–to–cycle variations of fundamental frequency and
amplitude, respectively, which have been largely used for the description of pathological voice
quality. Jitter is also known as frequency perturbation and refers to the minute involuntary variations
in the timing variability between cycles of vibration. In essence, it is a measure of frequency
variability in comparison to the client's fundamental frequency. Research shows that jitter values in
normal voices range from 0.2 to 1 percent. (Ferrand, 2007) Jitter values above this level indicate that
the vocal folds are vibrating in a way that ... Show more content on Helpwriting.net ...
The vocal note produced by the vibrations of the vocal folds is complex and made up of periodic
(regular and repetitive) and aperiodic (irregular and non–repetitive) sound waves. The aperiodic
waves are random noise introduced into the vocal signal owing to irregular or asymmetric adduction
(closing) of the vocal folds. Noise impairs the clarity of the vocal note and too much noise is
perceived as hoarseness. The Harmonics–to–Noise (HNR) ratio is a measure of the proportion of
harmonic sound to noise in the voice measured in decibels. (Ferrand, 2007). HNR quantifies the
relative amount of additive noise (Awen & Frankel, 1994) The lower the HNR, the more noise in the
voice. Laryngeal pathology may lead to poor adduction of the vocal folds and, therefore, increase
the amount of random noise in the vocal note. If a person has some kind of problem in vibrating the
vocal folds, due to a growth, paralysis of one or both vocal folds, or other kind of laryngeal problem,
a larger amount of air escapes during vibration, creating turbulent noise. (Pabon & Plomp, 1988)
The greater the proportion of noise, the greater the perceived hoarseness, breathiness or roughness
and the lower the HNR figure will be, i.e. a low HNR indicates a high level of hoarseness, and a
high HNR indicates a low level of hoarseness. There is a strong relationship between how we
perceive voice quality and the harmonic to noise ratio (Ferrand, 2007).

Simulation And Analysis Of 10 Gbps Optical Communication...
Simulation and analysis of 10 GBPS optical communication system using different pulses Apurv
Anand1, VIkash Kumar2 , Ekta Negi3 Deepak Kumar Ray4
1,2,3 Dept. of EnTC , Bharti VIdyapeeth deemed university , College of Engineering Pune ,
Maharashtra–411043 , India
4 Assistant Professor , Bharti Vidyapeeth deemed university , College of engineering Pune ,
Maharashtra–411043 , India
ABSTRACT : – In this paper we simulatd an optical transmission system in optical fiber using
different pulses .The optical fiber system used in telecommunication system has small size or
dimension, low loss and low interference from outside environment. Optical fiber are of various
configurations , we are using fiber bragg grating as the dispersion compensator in the fiber optic
cable . We are using FBG in the simulation as because it offers more bandwidth .Optisystem
software is used to analyse the optical transmission system . In the simulation of the communication
system appropriate values of the input power , fiber cable length and attenuation coefficient is taken
around the cable section and the output pwer , noise figure , gain is found out at the receiver. The
transmitter frequency and cut off frequency of the receiver is made constant .
Keywords: – Optical communication System, FBG , Optisystem software , parameters I.
INTRODUCTION
Any transmission system consists of three basic components , that are fiber

Activation of Protein Kinases by Means of Stochastic...
Short overview The current technology is based on protein kinase activation by means of stochastic
resonance mediated through pulsed electrical fields of very low signal strength. The mode of action
reveals how even small pulsed electrical fields can have a major influence on cellular function and
physiological consequences. It is well known that biological sensory systems transform analog
quantities such us pressure, temperature, electric fields (E–fields) etc. into trains of information. All
the features of systems exhibiting stochastic resonance were found to be present in cell signaling
systems which are intrinsically noisy, nonlinear threshold systems. We observed the effects of
pulsed electrical fields of intensity near that of ... Show more content on Helpwriting.net ...
We visualize the mechanism as that of a working Brownian ratchet where transitions into a different
activated state can be favored. We observed that changing frequencies of E–fields causes enhanced
activation from 2 to 100 Hz and that higher frequencies cause reduced activation. Thus the system
fulfills the requirements of a stochastic resonance system with a '∩' shaped curve. Introduction:
Stochastic resonance (SR) occurs in a system with a threshold or barrier such as in a protein when a
correct input of information transfer (changes in specific electrical fields effecting charged particles
and signal–to–noise ratio) is maximized in the presence of a specific non–zero level of stochastic
input noise (such as randomly fluctuating electrical fields) thereby lowering the response threshold.
The system will then resonate at a particular noise level. Thus, stochastic resonance is a term which
describes that one time scale is established by the period of the external stimulus and the other by
the position to position switching rate induced by the stochastic process or noise. By this effect a
synchronization of a nonlinear system to a weak periodic signal can be enhanced by the presence of
random fluctuations. A weak periodic signal is one which cannot by itself produce switchin g
between positions in protein subunits. In such systems the essence of the signal enhancing effect of
SR can be understood in following way: In the absence of stimuli there are few and random

Best Portable Music Player Analysis
How to select the best Portable music player
Introduction
Over the decade, the electronic industry dealing with portable systems has seen an extensive growth
(Şener, S., & Sarıdoğan, E. 2011) ; the mass production and mass consumption of such portable
products, be it the Play Station Portable or the Alienware range of portable gaming laptops, has led
to technological advancements escalating tenfold every few years (Luo, J., Olechowski, A. L., &
Magee, C. L. , 2014). Most people have transformed themselves into tech savvy animals who
quench their thirst with the next best product on the market (Swinyard, W. R. and Smith, S. M.,
2003). Assuming you are one among them, and want to determine how to select the best portable
music player, read on! Generally, at some point of our lives, we see ourselves gazing at the
prominent range of portable music players, regardless of whether we use it indoors or outdoors, for
partying or relaxing. Considering that music is a part of everyday life, and owning a portable music
player certainly improves that ordeal (Jeremy J., p20, 2015) and with the advancement in battery
technology and also Bluetooth technology, we can investigate the impulse of selecting a portable
player. In general, a portable music player allows us to connect it to a source and play music.
Basically, a portable music player consists of a battery, a couple of speakers, input ports, feedback
keys or screen, etc.(Yun J., 2002). We will analyse these distinct features of a

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