Line coding
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Line coding is the process of converting digital data to digital signals for transmission. There are several types of line coding including unipolar, polar, bipolar, and multilevel coding. Common line coding schemes include non-return-to-zero (NRZ), return-to-zero (RZ), Manchester, and alternate mark inversion (AMI), with each scheme varying in how bits are represented as signal levels and transitions.
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Line coding
Digital line coding is used to convert digital data into voltage levels that can be transmitted over a communications system. There are several types of line coding including unipolar, polar, and bipolar coding. Unipolar coding represents 1s and 0s using the presence or absence of a voltage pulse. Polar coding uses positive and negative voltage pulses to represent 1s and 0s. Bipolar coding uses three voltage levels to represent data. Line coding is needed to reduce bandwidth usage, use power efficiently, reduce errors, and avoid long runs of the same binary value. Common line coding schemes include unipolar return to zero, polar return to zero, bipolar non-return to zero, and Manchester encoding. Disadvantages
Sonjoy kundu line coding
This document summarizes a seminar presentation on line coding. It discusses the need for line coding to avoid signal dispersion when transmitting discrete digital information over band-limited channels. It then introduces several common line coding techniques, including unipolar NRZ and RZ, polar NRZ and RZ, bipolar AMI, and Manchester coding. It describes the properties, advantages, and disadvantages of each technique. Finally, it derives the power spectral density of polar and bipolar signaling and provides a comparison of line coding methods in terms of transmission of DC components, signaling rate, noise immunity, synchronization capability, bandwidth requirement, and crosstalk.
Koding
The document discusses various techniques for encoding analog signals into digital pulses for transmission, including:
1. Pulse code modulation (PCM) which samples and quantizes an analog signal then assigns a codeword to each quantization level.
2. Common encoding schemes for the digital pulses including unipolar, polar, and bipolar encodings as well as return-to-zero (RZ) and non-return-to-zero (NRZ).
3. Specific encoding methods like alternate mark inversion (AMI) used in telephone systems, and bipolar with eight-zero substitution (B8ZS) used to prevent long runs of zeros in transmission.
Digital Data, Digital Signal | Scrambling Techniques
Digital signal is a sequence of discrete, discontinuous voltage pulses.
Each pulse is a signal element.
Binary data are transmitted by encoding the bit stream into signal elements.
In the simplest case, one bit is represented by one signal element.
- E.g., 1 is represented by a lower voltage level, and 0 is represented by a higher voltage level
Line coding
This document discusses line coding techniques used for digital data transmission. It begins by explaining the need for line coding due to the discrete and band-limited nature of information being transmitted. Then it covers various line coding techniques including unipolar, polar, bipolar, and Manchester coding. It discusses the properties, advantages, disadvantages and power spectral density of each technique. Finally, it provides a comparison of polar RZ, polar NRZ, AMI and Manchester coding in terms of their transmission of DC components, signaling rate, noise immunity, synchronization capability, bandwidth requirement, and crosstalk.
Data Communication & Computer Networks : Unipolar & Polar coding
This document discusses different line coding schemes used for data transmission and conversion. It begins by describing different data conversion techniques such as digital to digital, line coding, block coding, scrambling, analog to digital conversion, and digital to analog conversion. It then discusses the main categories of line coding schemes and focuses on polar encoding techniques including Non-Return to Zero (NRZ), Return to Zero (RZ), and biphase encoding such as Manchester encoding and differential Manchester encoding. Specific details are provided on how each scheme encodes binary data into signals. Common applications of these coding schemes in standards such as Ethernet and token ring networks are also mentioned.
Line coding
The document discusses line coding, which is the process of converting digital data to digital signals for transmission over a communication channel. There are several types of line coding discussed, including unipolar (e.g. NRZ), polar, bipolar, and Manchester coding. The goals of line coding are to increase data rates while decreasing signal rates and bandwidth requirements, provide error detection capabilities, and allow for self-synchronization between the transmitter and receiver clocks. Characteristics of line coding include distinguishing between data elements (bits) and signal elements, and how data and signal rates differ.
Digital data transmission,line coding and pulse shaping
This document discusses digital data transmission, line coding, and pulse shaping. It covers several key topics:
- Digital data transmission involves converting analog signals like voice or images to binary digits for transmission and reconverting them at the receiving end. This allows for clearer, faster transmission using less bandwidth.
- There are two main transmission modes: parallel transmits multiple bits at once for higher speed, while serial transmits one bit at a time to reduce costs. Conversion is needed between parallel and serial interfaces.
- Line coding converts digital bits to voltage levels for transmission. Common schemes include NRZ, RZ, Manchester, AMI, and pseudoternary.
- Pulse shaping filters transmitted pulses to limit
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Line coding
Digital line coding is used to convert digital data into voltage levels that can be transmitted over a communications system. There are several types of line coding including unipolar, polar, and bipolar coding. Unipolar coding represents 1s and 0s using the presence or absence of a voltage pulse. Polar coding uses positive and negative voltage pulses to represent 1s and 0s. Bipolar coding uses three voltage levels to represent data. Line coding is needed to reduce bandwidth usage, use power efficiently, reduce errors, and avoid long runs of the same binary value. Common line coding schemes include unipolar return to zero, polar return to zero, bipolar non-return to zero, and Manchester encoding. Disadvantages
Sonjoy kundu line coding
This document summarizes a seminar presentation on line coding. It discusses the need for line coding to avoid signal dispersion when transmitting discrete digital information over band-limited channels. It then introduces several common line coding techniques, including unipolar NRZ and RZ, polar NRZ and RZ, bipolar AMI, and Manchester coding. It describes the properties, advantages, and disadvantages of each technique. Finally, it derives the power spectral density of polar and bipolar signaling and provides a comparison of line coding methods in terms of transmission of DC components, signaling rate, noise immunity, synchronization capability, bandwidth requirement, and crosstalk.
Koding
The document discusses various techniques for encoding analog signals into digital pulses for transmission, including:
1. Pulse code modulation (PCM) which samples and quantizes an analog signal then assigns a codeword to each quantization level.
2. Common encoding schemes for the digital pulses including unipolar, polar, and bipolar encodings as well as return-to-zero (RZ) and non-return-to-zero (NRZ).
3. Specific encoding methods like alternate mark inversion (AMI) used in telephone systems, and bipolar with eight-zero substitution (B8ZS) used to prevent long runs of zeros in transmission.
Digital Data, Digital Signal | Scrambling Techniques
Digital signal is a sequence of discrete, discontinuous voltage pulses.
Each pulse is a signal element.
Binary data are transmitted by encoding the bit stream into signal elements.
In the simplest case, one bit is represented by one signal element.
- E.g., 1 is represented by a lower voltage level, and 0 is represented by a higher voltage level
Line coding
This document discusses line coding techniques used for digital data transmission. It begins by explaining the need for line coding due to the discrete and band-limited nature of information being transmitted. Then it covers various line coding techniques including unipolar, polar, bipolar, and Manchester coding. It discusses the properties, advantages, disadvantages and power spectral density of each technique. Finally, it provides a comparison of polar RZ, polar NRZ, AMI and Manchester coding in terms of their transmission of DC components, signaling rate, noise immunity, synchronization capability, bandwidth requirement, and crosstalk.
Data Communication & Computer Networks : Unipolar & Polar coding
This document discusses different line coding schemes used for data transmission and conversion. It begins by describing different data conversion techniques such as digital to digital, line coding, block coding, scrambling, analog to digital conversion, and digital to analog conversion. It then discusses the main categories of line coding schemes and focuses on polar encoding techniques including Non-Return to Zero (NRZ), Return to Zero (RZ), and biphase encoding such as Manchester encoding and differential Manchester encoding. Specific details are provided on how each scheme encodes binary data into signals. Common applications of these coding schemes in standards such as Ethernet and token ring networks are also mentioned.
Line coding
The document discusses line coding, which is the process of converting digital data to digital signals for transmission over a communication channel. There are several types of line coding discussed, including unipolar (e.g. NRZ), polar, bipolar, and Manchester coding. The goals of line coding are to increase data rates while decreasing signal rates and bandwidth requirements, provide error detection capabilities, and allow for self-synchronization between the transmitter and receiver clocks. Characteristics of line coding include distinguishing between data elements (bits) and signal elements, and how data and signal rates differ.
Digital data transmission,line coding and pulse shaping
This document discusses digital data transmission, line coding, and pulse shaping. It covers several key topics:
- Digital data transmission involves converting analog signals like voice or images to binary digits for transmission and reconverting them at the receiving end. This allows for clearer, faster transmission using less bandwidth.
- There are two main transmission modes: parallel transmits multiple bits at once for higher speed, while serial transmits one bit at a time to reduce costs. Conversion is needed between parallel and serial interfaces.
- Line coding converts digital bits to voltage levels for transmission. Common schemes include NRZ, RZ, Manchester, AMI, and pseudoternary.
- Pulse shaping filters transmitted pulses to limit
Line Coding in OFC
This document discusses different types of line coding used in optical fiber communication. It describes three basic types of line coding: non-return-to-zero (NRZ), return-to-zero (RZ), and phase encoding (PE). NRZ represents 1s and 0s with different voltage levels but no neutral state, while RZ includes a rest state between bits. RZ signals are self-clocking but use twice the bandwidth of NRZ. The document also discusses mBnB coding, which converts m input bits to n coded bits to add redundancy for error correction while maintaining balance and adequate transitions for timing recovery.
Line coding
Line coding is used in optical fiber communication to encode digital signals for transmission by arranging signal symbols in a particular pattern. It involves converting binary data into an optical signal. The goals of line coding are to transmit binary data like voice, video or financial information over long distances using optical fiber with sufficient bandwidth. There are three main types of line coding: non-return-to-zero (NRZ), return-to-zero (RZ), and phase encoding (PE). NRZ represents 1s and 0s with different voltage levels but no neutral state, while RZ includes a neutral rest state between bits. PE converts blocks of input bits into code bits with added redundancy for error detection and correction.
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These slides cover the fundamentals of data communication & networking. it covers Bipolar codes which are used in communication of data over transmission medium. It is useful for engineering students & also for the candidates who want to master data communication & computer networking.
EEP306: Line coding
The document summarizes an experiment to study line coding encoder and decoder modules. It introduces that line coding is used as an interface between analog and digital signals and serves purposes like spectrum shaping, removing the DC component, and error detection. It then analyzes various line coding schemes like NRZ-L, NRZ-M, UNI-RZ, BIP-RZ, RZ-AMI, Biφ-L, DICODE-NRZ and duo-binary encoding in both encoders and decoders. While most schemes showed the encoded and decoded signals as expected, the decoded signal for UNI-RZ was not observed though the system was checked to have no issues. The conclusion states that line coding schemes convert analog to digital
Data communications 4 1
This document discusses digital transmission techniques for converting digital data into digital signals. It covers line coding, which maps binary data bits to signal levels. Common line coding schemes include NRZ, RZ, Manchester, and AMI. Multilevel coding schemes are also introduced, which encode multiple data bits as a single signal element to increase data rates. Key considerations for line coding include baseline wandering, DC components, self-synchronization, error detection, noise immunity, and complexity. Worked examples calculate baud rates and minimum bandwidths for different schemes.
Line coding
This document discusses digital communication systems and line coding. It covers topics such as multiplexing techniques, line coders for baseband transmission, regenerative repeaters, examples of line coding schemes including NRZ, RZ, Manchester, AMI, and mBnL codes. It also discusses related topics like data rate vs signal rate, self-synchronization, bandwidth requirements, and clock recovery.
Data encoding
Data encoding converts data into a signal form for transmission. There are different encoding methods for digital-to-digital, digital-to-analog, analog-to-analog, and analog-to-digital conversion. Common digital encoding techniques include unipolar, bipolar, and polar encoding, which represent binary data using single or multiple voltage levels. Non-return-to-zero and return-to-zero are examples that represent bits through the signal remaining at a level or returning to zero between bits. Manchester encoding and differential Manchester encoding are biphase techniques that provide clocking through signal transitions.
Manchester Encoding
Manchester encoding is a technique used in the physical layer of the OSI model to encode data for transmission. It works by assigning transitions from 0 to 1 or 1 to 0 in the center of each bit to represent the bit value. This allows the receiver to easily extract the clock signal and correctly decode each bit. While it provides improved clocking and reliability over other encoding schemes, Manchester encoding exhibits poorer bit storage density for storing data on magnetic media.
Line codes
A digital signal is a sequence of discrete, discontinuous voltage pulses. Each pulse is a signal element. Binary data '0' and '1' are transmitted over digital channel by encoding each data bit into signal elements. Encoding scheme is mapping from data bits to signal elements. Line coding is done to prevent DC wandering and loss of synchronisation on long strings of '0' and '1'. It may give some amount of error detection as in AMT.
U N I T I I Baseband Demod V S H
The document discusses various techniques for baseband demodulation and detection. It begins with an introduction to baseband signaling and the problems of intersymbol interference. It then covers topics like data formats, line coding, synchronization, and equalization. Several line coding formats are described in detail, including unipolar NRZ, polar NRZ, Manchester coding, and AMI coding. Their properties like bandwidth, power efficiency, and error detection capability are compared. Finally, the document discusses multiplexing techniques for transmitting multiple signals over a single channel.
Encoding Techniques
1) Information must be encoded into signals before it can be transmitted across communication media. There are several types of encoding including digital-to-digital, analog-to-digital, digital-to-analog, and analog-to-analog.
2) Common digital encoding techniques include unipolar, polar, bipolar, NRZ, RZ, and Manchester encoding. These techniques encode digital data into electrical signals to prepare it for transmission.
3) Analog-to-digital encoding takes an analog signal, samples it, and generates a series of pulses representing the signal amplitude. This includes techniques like PAM, PCM, and quantization.
Line coding adcs
This document provides information about different types of line coding used to transmit binary data over communication channels. It discusses unipolar, polar, bipolar, HDBn, and Manchester line coding. For each type it provides the pulse representation for 1s and 0s, advantages, disadvantages, and power spectral density plots. It explains that line coding choices are made based on factors like bandwidth, error performance, transparency, and suitability for transmission over AC coupled lines.
Coding
This document discusses digital baseband communication systems and line coding techniques. It provides an overview of the key steps in analog-to-digital conversion: sampling, quantization, mapping, and encoding/pulse shaping. It then describes several common line coding schemes used to transmit the digital bit stream over physical channels, including unipolar, polar, and bipolar encoding. The advantages and disadvantages of each scheme are discussed in terms of properties like DC balance, clock recovery, energy, and bandwidth.
Manchester coding
Manchester encoding is a line code technique where each bit is represented by transitions at the midpoint between bit periods, with a '1' represented by a high-to-low transition and a '0' represented by a low-to-high transition. This allows the clock to be recovered from the encoded data and makes synchronization easier. While it requires double the bandwidth of other coding schemes and relies on correct polarity detection, Manchester encoding has found wide use for radio transmission of digital data.
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Chapter4
The document discusses various line coding techniques used in digital communication. It describes 6 main types of line codes:
1) Polar signal - Represents 1 as +A volts and 0 as -A volts. Allows easy generation but requires dual supply voltages.
2) Unipolar signal - Represents 1 as +A volts and 0 as 0 volts. Easy generation from single supply but wastes power.
3) Bipolar signal - Alternates between positive and negative voltages for 1s. Represents 0 as 0 volts. Detects single errors.
4) Manchester coding - Encodes 1 as +A volts for half pulse then -A volts. Encodes 0 as opposite. Ensures
Line coding
This document discusses various line coding techniques used to transmit binary data over communication channels. It begins by defining line coding as the process of mapping binary data into digital signals for transmission. Several line coding schemes are then described, including unipolar NRZ, unipolar RZ, polar NRZ, polar RZ, bipolar NRZ, bipolar RZ, and Manchester coding. Each coding scheme is evaluated based on factors like bandwidth usage, presence of a DC component, error detection capabilities, and suitability for transmission over AC coupled lines. Manchester coding is highlighted as a self-synchronizing scheme that allows clock recovery at the receiver.
Encoding techniques
Encoding is the process of converting data into a digital format for transmission. There are different encoding techniques for analog and digital data. Common digital to digital encoding techniques include NRZ, NRZI, Manchester, and 4B/5B encoding. NRZ assigns a voltage level to represent each bit but can cause issues with long strings of the same bit. NRZI and Manchester encoding add transitions to distinguish bits and allow synchronization. 4B/5B encoding groups bits into blocks and maps them to code words, preventing long runs of the same bit. These encoding techniques allow reliable transmission of digital data over networks.
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What is communication?
Information Transfer Modulation
Communication System
Input/output Device Transmitter Channel
Noise Receiver
Simplex and duplex communication
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Unipolar encoding techniques such as Unipolar-NRZ and Unipolar-RZ are discussed. Unipolar encoding uses only one polarity of voltage level (0 and 1) to represent binary data. Unipolar-NRZ does not return to zero in the middle of a bit while Unipolar-RZ does return to zero, consuming twice the bandwidth of Unipolar-NRZ. Both techniques have advantages and disadvantages related to implementation complexity and error handling. Signal drooping can occur when low frequency components in unipolar signals cause distortion as they pass through AC coupled transmission lines.
Digital differential analyzer
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RGB color stands for RED,GREEN and BLUE. This color model is used in computer monitors, television sets,
and theater. It's an additive color model.
CMYK refers to the four inks used in some color printing: cyan, magenta, yellow and key (black).
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Line Coding in OFC
This document discusses different types of line coding used in optical fiber communication. It describes three basic types of line coding: non-return-to-zero (NRZ), return-to-zero (RZ), and phase encoding (PE). NRZ represents 1s and 0s with different voltage levels but no neutral state, while RZ includes a rest state between bits. RZ signals are self-clocking but use twice the bandwidth of NRZ. The document also discusses mBnB coding, which converts m input bits to n coded bits to add redundancy for error correction while maintaining balance and adequate transitions for timing recovery.
Line coding
Line coding is used in optical fiber communication to encode digital signals for transmission by arranging signal symbols in a particular pattern. It involves converting binary data into an optical signal. The goals of line coding are to transmit binary data like voice, video or financial information over long distances using optical fiber with sufficient bandwidth. There are three main types of line coding: non-return-to-zero (NRZ), return-to-zero (RZ), and phase encoding (PE). NRZ represents 1s and 0s with different voltage levels but no neutral state, while RZ includes a neutral rest state between bits. PE converts blocks of input bits into code bits with added redundancy for error detection and correction.
Data Communication & Computer network: Bipolar codes
These slides cover the fundamentals of data communication & networking. it covers Bipolar codes which are used in communication of data over transmission medium. It is useful for engineering students & also for the candidates who want to master data communication & computer networking.
EEP306: Line coding
The document summarizes an experiment to study line coding encoder and decoder modules. It introduces that line coding is used as an interface between analog and digital signals and serves purposes like spectrum shaping, removing the DC component, and error detection. It then analyzes various line coding schemes like NRZ-L, NRZ-M, UNI-RZ, BIP-RZ, RZ-AMI, Biφ-L, DICODE-NRZ and duo-binary encoding in both encoders and decoders. While most schemes showed the encoded and decoded signals as expected, the decoded signal for UNI-RZ was not observed though the system was checked to have no issues. The conclusion states that line coding schemes convert analog to digital
Data communications 4 1
This document discusses digital transmission techniques for converting digital data into digital signals. It covers line coding, which maps binary data bits to signal levels. Common line coding schemes include NRZ, RZ, Manchester, and AMI. Multilevel coding schemes are also introduced, which encode multiple data bits as a single signal element to increase data rates. Key considerations for line coding include baseline wandering, DC components, self-synchronization, error detection, noise immunity, and complexity. Worked examples calculate baud rates and minimum bandwidths for different schemes.
Line coding
This document discusses digital communication systems and line coding. It covers topics such as multiplexing techniques, line coders for baseband transmission, regenerative repeaters, examples of line coding schemes including NRZ, RZ, Manchester, AMI, and mBnL codes. It also discusses related topics like data rate vs signal rate, self-synchronization, bandwidth requirements, and clock recovery.
Data encoding
Data encoding converts data into a signal form for transmission. There are different encoding methods for digital-to-digital, digital-to-analog, analog-to-analog, and analog-to-digital conversion. Common digital encoding techniques include unipolar, bipolar, and polar encoding, which represent binary data using single or multiple voltage levels. Non-return-to-zero and return-to-zero are examples that represent bits through the signal remaining at a level or returning to zero between bits. Manchester encoding and differential Manchester encoding are biphase techniques that provide clocking through signal transitions.
Manchester Encoding
Manchester encoding is a technique used in the physical layer of the OSI model to encode data for transmission. It works by assigning transitions from 0 to 1 or 1 to 0 in the center of each bit to represent the bit value. This allows the receiver to easily extract the clock signal and correctly decode each bit. While it provides improved clocking and reliability over other encoding schemes, Manchester encoding exhibits poorer bit storage density for storing data on magnetic media.
Line codes
A digital signal is a sequence of discrete, discontinuous voltage pulses. Each pulse is a signal element. Binary data '0' and '1' are transmitted over digital channel by encoding each data bit into signal elements. Encoding scheme is mapping from data bits to signal elements. Line coding is done to prevent DC wandering and loss of synchronisation on long strings of '0' and '1'. It may give some amount of error detection as in AMT.
U N I T I I Baseband Demod V S H
The document discusses various techniques for baseband demodulation and detection. It begins with an introduction to baseband signaling and the problems of intersymbol interference. It then covers topics like data formats, line coding, synchronization, and equalization. Several line coding formats are described in detail, including unipolar NRZ, polar NRZ, Manchester coding, and AMI coding. Their properties like bandwidth, power efficiency, and error detection capability are compared. Finally, the document discusses multiplexing techniques for transmitting multiple signals over a single channel.
Encoding Techniques
1) Information must be encoded into signals before it can be transmitted across communication media. There are several types of encoding including digital-to-digital, analog-to-digital, digital-to-analog, and analog-to-analog.
2) Common digital encoding techniques include unipolar, polar, bipolar, NRZ, RZ, and Manchester encoding. These techniques encode digital data into electrical signals to prepare it for transmission.
3) Analog-to-digital encoding takes an analog signal, samples it, and generates a series of pulses representing the signal amplitude. This includes techniques like PAM, PCM, and quantization.
Line coding adcs
This document provides information about different types of line coding used to transmit binary data over communication channels. It discusses unipolar, polar, bipolar, HDBn, and Manchester line coding. For each type it provides the pulse representation for 1s and 0s, advantages, disadvantages, and power spectral density plots. It explains that line coding choices are made based on factors like bandwidth, error performance, transparency, and suitability for transmission over AC coupled lines.
Coding
This document discusses digital baseband communication systems and line coding techniques. It provides an overview of the key steps in analog-to-digital conversion: sampling, quantization, mapping, and encoding/pulse shaping. It then describes several common line coding schemes used to transmit the digital bit stream over physical channels, including unipolar, polar, and bipolar encoding. The advantages and disadvantages of each scheme are discussed in terms of properties like DC balance, clock recovery, energy, and bandwidth.
Manchester coding
Manchester encoding is a line code technique where each bit is represented by transitions at the midpoint between bit periods, with a '1' represented by a high-to-low transition and a '0' represented by a low-to-high transition. This allows the clock to be recovered from the encoded data and makes synchronization easier. While it requires double the bandwidth of other coding schemes and relies on correct polarity detection, Manchester encoding has found wide use for radio transmission of digital data.
Digital Data to Digital Signal Conversion
Digital to Digital Conversion
Conversion Techniques
Line Coding
Relationship Between Data Rate and Signal Rate
Line Coding Schemes
Unipolar
Polar
Bipolar
Block Coding
Scrambling
Chapter4
The document discusses various line coding techniques used in digital communication. It describes 6 main types of line codes:
1) Polar signal - Represents 1 as +A volts and 0 as -A volts. Allows easy generation but requires dual supply voltages.
2) Unipolar signal - Represents 1 as +A volts and 0 as 0 volts. Easy generation from single supply but wastes power.
3) Bipolar signal - Alternates between positive and negative voltages for 1s. Represents 0 as 0 volts. Detects single errors.
4) Manchester coding - Encodes 1 as +A volts for half pulse then -A volts. Encodes 0 as opposite. Ensures
Line coding
This document discusses various line coding techniques used to transmit binary data over communication channels. It begins by defining line coding as the process of mapping binary data into digital signals for transmission. Several line coding schemes are then described, including unipolar NRZ, unipolar RZ, polar NRZ, polar RZ, bipolar NRZ, bipolar RZ, and Manchester coding. Each coding scheme is evaluated based on factors like bandwidth usage, presence of a DC component, error detection capabilities, and suitability for transmission over AC coupled lines. Manchester coding is highlighted as a self-synchronizing scheme that allows clock recovery at the receiver.
Encoding techniques
Encoding is the process of converting data into a digital format for transmission. There are different encoding techniques for analog and digital data. Common digital to digital encoding techniques include NRZ, NRZI, Manchester, and 4B/5B encoding. NRZ assigns a voltage level to represent each bit but can cause issues with long strings of the same bit. NRZI and Manchester encoding add transitions to distinguish bits and allow synchronization. 4B/5B encoding groups bits into blocks and maps them to code words, preventing long runs of the same bit. These encoding techniques allow reliable transmission of digital data over networks.
communication system lec3
What is communication?
Information Transfer Modulation
Communication System
Input/output Device Transmitter Channel
Noise Receiver
Simplex and duplex communication
Unipolar Encoding Techniques: NRZ & RZ
Unipolar encoding techniques such as Unipolar-NRZ and Unipolar-RZ are discussed. Unipolar encoding uses only one polarity of voltage level (0 and 1) to represent binary data. Unipolar-NRZ does not return to zero in the middle of a bit while Unipolar-RZ does return to zero, consuming twice the bandwidth of Unipolar-NRZ. Both techniques have advantages and disadvantages related to implementation complexity and error handling. Signal drooping can occur when low frequency components in unipolar signals cause distortion as they pass through AC coupled transmission lines.
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Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Design and optimization of ion propulsion drone
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
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22CYT12-Unit-V-E Waste and its Management.ppt
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
AI assisted telemedicine KIOSK for Rural India.pptx
It gives the overall description of SIH problem statement " AI assisted telemedicine KIOSK for Rural India".
Embedded machine learning-based road conditions and driving behavior monitoring
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Mechanical Engineering on AAI Summer Training Report-003.pdf
Mechanical Engineering PROJECT REPORT ON SUMMER VOCATIONAL TRAINING
AT MBB AIRPORT
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
An improved modulation technique suitable for a three level flying capacitor ...
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
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Generative AI leverages algorithms to create various forms of content
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Line coding
- 1. Line Coding
- 2. Line coding: Line coding is the process of converting digital data to digital signals. Line coding converts a sequence of bits to a digital signal.
- 3. Types of line coding: Unipolar Polar Bipolar Multilevel Multitransition Line Coding
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- 8. Bipolar schemes: AMI and pseudoternary
- 9. Multilevel: 2B1Q scheme Next bits Next level Next level 00 +1 -1 01 +3 -3 10 -1 +1 11 -3 +3 Previous level: Previous level: Positive Negative