Sampling is a Simple method to convert analog signal into discrete Signal by using any one of its three methods
if the sampling frequency is twice or greater than twice then sampled signal can be convert back into analog signal easily......
Sampling is a Simple method to convert analog signal into discrete Signal by using any one of its three methods
if the sampling frequency is twice or greater than twice then sampled signal can be convert back into analog signal easily......
Digital Signal Processing[ECEG-3171]-Ch1_L05Rediet Moges
This Digital Signal Processing Lecture material is the property of the author (Rediet M.) . It is not for publication,nor is it to be sold or reproduced.
#Africa#Ethiopia
Digital Signal Processing[ECEG-3171]-Ch1_L05Rediet Moges
This Digital Signal Processing Lecture material is the property of the author (Rediet M.) . It is not for publication,nor is it to be sold or reproduced.
#Africa#Ethiopia
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
6. Sampling Theorem
(For Lowpass Signals)
Let the finite energy signal g(t) is bandlimited to W; i.e., G(f) ≡ 0
for │f│≥ W. Let g(t) be sampled at multiples of some basic
sampling interval Ts , where Ts ≤ 1/2W, to yield the sequence
{g(nTs)} for -∞ ≤ n ≤ ∞. Then it is possible to reconstruct the
original signal g(t) from the sampled values without any
distortion.
Sampling rate fs = 2W is called Nyquist rate
13. Spectrum of analog signal and under-
sampled signal showing aliasing
fmax
Frequency
Amplitude
aliasing
Frequency
Amplitude
Spectral Window
fs/2
fs
(a)
(b)
14.
15. (a) Anti-alias filtered spectrum of signal
(b) Spectrum of instantaneously sampled signal, assuming sampling rate greater
than Nyquist rate
(c) Magnitude response of reconstruction filter
16. (a) Anti-alias filtered spectrum of signal
(b) Spectrum of instantaneously sampled signal, assuming sampling
rate greater than Nyquist rate
(c) Magnitude response of reconstruction filter
17. Sampling Theorem For Bandpass Signals
• Consider a bandpass signal occupying a
frequency band fL to fH. The minimum sampling
frequency fs allowable is 2(fH – fL) provided that
either fH or fL is an integer multiple of fs.
18. Sampling Theorem For Random Process
Consider a WSS random process, X(t),
bandlimited to W Hz {i.e., SX(f)=0 for │f│≥W}.
To reconstruct the process from its samples with
zero mean square error, {E│X(t) – Xꞌ(t)│2}→0,
the minimum sampling rate required will be 2W.
19. Analog Pulse Modulation
• Pulse amplitude modulation (PAM)
• Pulse width modulation (PWM)
• Pulse position modulation (PPM)
32. Sample and Hold Circuit For Signal
Recovery
• The reconstruction can be done by
interpolating between samples.
• Ideal low-pass filter can do interpolation.
• Practical systems use S/H circuits
– Zero-order-hold (ZOH)
– First-order-hold (FOH)
