In this paper, Decimal Matrix Code is developed for RFID passive tag. The proposed DMC uses the decimal algorithm to obtain the maximum error detection and correction capability. The Encoder-Reuse Technique is used to minimize the area overhead of extra circuits without disturbing the complete encoding and decoding processes. ERT uses DMC encoder itself to be part of the decoder. The Simulation results reveals that the Decimal Matrix Code is effective than existing Matrix and Hamming odes in terms of Error Correction Capability. Xilinx ISE 14.7 Software is used for the simulation outputs. The complete design is verified and tested on Spartan-6 FPGA board. The performance of system is measured in terms of power, area and delay. The Synthesis result shows that, the power required for complete design of Decimal Matrix Code is 0.1mW with a delay of 3.109ns.
Design and implementation of single bit error correction linear block code sy...TELKOMNIKA JOURNAL
Linear block code (LBC) is an error detection and correction code that is widely used in
communication systems. In this paper a special type of LBC called Hamming code was implemented and
debugged using FPGA kit with integrated software environments ISE for simulation and tests the results of
the hardware system. The implemented system has the ability to correct single bit error and detect two bits
error. The data segments length was considered to give high reliability to the system and make an
aggregation between the speed of processing and the hardware ability to be implemented. An adaptive
length of input data has been consider, up to 248 bits of information can be handled using Spartan 3E500
with 43% as a maximum slices utilization. Input/output data buses in FPGA have been customized to meet
the requirements where 34% of input/output resources have been used as maximum ratio. The overall
hardware design can be considerable to give an optimum hardware size for the suitable information rate.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IRJET- FPGA Implementation of Orthogonal Codes for Efficient Digital Communic...IRJET Journal
This document describes an FPGA implementation of orthogonal codes for efficient digital communication. Orthogonal codes contain an equal number of 1s and 0s and can detect errors without needing to transmit parity bits. The authors implement an orthogonal code error detection and correction system on an FPGA using VHDL. Simulation results show the technique can detect up to 99.99% of errors and correct up to half the code length minus one bit errors for an n-bit orthogonal code. Compared to other techniques like CRC and Hamming codes, orthogonal codes provide higher error detection and correction capabilities.
Implementation of Designed Encoder and Decoder for Golay CodeIRJET Journal
This document presents the design and implementation of encoders and decoders for Golay codes. It begins with background on Golay codes, which are error-correcting codes used in wireless communication. It then describes an algorithm for Golay code encoding using polynomial long division to generate check bits from message bits. The document proposes optimized FPGA-based architectures for a Golay (23,12,7) encoder and extending it to a Golay (24,12,8) encoder by adding a parity bit. It provides an example of encoding a message and validating the generated codeword. The encoder architectures use priority encoders, shift registers, and controlled subtractors to efficiently perform the cyclic polynomial long division encoding process in hardware.
digital logic circuits, digital component floting and fixed pointRai University
This document discusses different numeric data representations used in computer systems, including fixed-point and floating-point numbers. It describes fixed-point numbers as having a limited range but being fast and inexpensive to implement. Floating-point numbers are explained as having a much wider range of supported values but requiring more storage space. The key aspects of single and double precision floating-point formats are outlined, including the usage of sign, exponent, and significand bits to represent values within different magnitude ranges. Examples of common fixed and floating-point data types used in programming are also provided.
The BINARY to GRAY CODE CONVERTER is a digital circuit that is used to convert the binary input into the corresponding equivalent gray code at its output
EFFICIENT MULTIPLIERS FOR 1-OUT-OF-3 BINARY SIGNED-DIGIT NUMBER SYSTEMelelijjournal
This paper proposes new multipliers based on Binary Signed-Digit (BSD) operands. BSD number system has carry free capability in addition operation which causes high speed multiplication. In order to use the numbering system, BSD operand needs to be encoded into binary bits. 1-out-of-3 BSD encoding has been proposed as a subset of m-out-of-n codes which can be used for error detection and correction. However, a multiplier for 1-out-of-3 encoding has not yet been reported in the literature. In this paper, we propose
three different structures for 1-out-of-3 BSD multiplication for the first time to achieve an appropriate trade-off between area, delay, and power parameters. Our target implementation platform is Application Specific Circuits (ASIC).
Analysis and Implementation of Hard-Decision Viterbi Decoding In Wireless Com...IJERA Editor
Convolutional codes are also known as Turbo codes because of their error correction capability. These codes are
also awarded as Super product codes, because these codes have replaced the backward error correction codes.
Turbo codes are much more efficient than previous backward error correction codes because these are Forward
error correction (FEC) codes and there is no need for a feedback link to request the transmitter for
retransmission of data, when bits are corrupted in the information channel. A Viterbi decoder decodes stream of
digital data bits that has been encoded by Convolutional encoder. In this paper we introduce a RSC (Recursive
Systematic Convolutional) encoder with constraint length of 2 code rate of 1/3. The RSC encoder and Viterbi
decoder both are implemented on paper, as well as in MATLAB. Simulation results are also presented by using
MATLAB.
Design and implementation of single bit error correction linear block code sy...TELKOMNIKA JOURNAL
Linear block code (LBC) is an error detection and correction code that is widely used in
communication systems. In this paper a special type of LBC called Hamming code was implemented and
debugged using FPGA kit with integrated software environments ISE for simulation and tests the results of
the hardware system. The implemented system has the ability to correct single bit error and detect two bits
error. The data segments length was considered to give high reliability to the system and make an
aggregation between the speed of processing and the hardware ability to be implemented. An adaptive
length of input data has been consider, up to 248 bits of information can be handled using Spartan 3E500
with 43% as a maximum slices utilization. Input/output data buses in FPGA have been customized to meet
the requirements where 34% of input/output resources have been used as maximum ratio. The overall
hardware design can be considerable to give an optimum hardware size for the suitable information rate.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IRJET- FPGA Implementation of Orthogonal Codes for Efficient Digital Communic...IRJET Journal
This document describes an FPGA implementation of orthogonal codes for efficient digital communication. Orthogonal codes contain an equal number of 1s and 0s and can detect errors without needing to transmit parity bits. The authors implement an orthogonal code error detection and correction system on an FPGA using VHDL. Simulation results show the technique can detect up to 99.99% of errors and correct up to half the code length minus one bit errors for an n-bit orthogonal code. Compared to other techniques like CRC and Hamming codes, orthogonal codes provide higher error detection and correction capabilities.
Implementation of Designed Encoder and Decoder for Golay CodeIRJET Journal
This document presents the design and implementation of encoders and decoders for Golay codes. It begins with background on Golay codes, which are error-correcting codes used in wireless communication. It then describes an algorithm for Golay code encoding using polynomial long division to generate check bits from message bits. The document proposes optimized FPGA-based architectures for a Golay (23,12,7) encoder and extending it to a Golay (24,12,8) encoder by adding a parity bit. It provides an example of encoding a message and validating the generated codeword. The encoder architectures use priority encoders, shift registers, and controlled subtractors to efficiently perform the cyclic polynomial long division encoding process in hardware.
digital logic circuits, digital component floting and fixed pointRai University
This document discusses different numeric data representations used in computer systems, including fixed-point and floating-point numbers. It describes fixed-point numbers as having a limited range but being fast and inexpensive to implement. Floating-point numbers are explained as having a much wider range of supported values but requiring more storage space. The key aspects of single and double precision floating-point formats are outlined, including the usage of sign, exponent, and significand bits to represent values within different magnitude ranges. Examples of common fixed and floating-point data types used in programming are also provided.
The BINARY to GRAY CODE CONVERTER is a digital circuit that is used to convert the binary input into the corresponding equivalent gray code at its output
EFFICIENT MULTIPLIERS FOR 1-OUT-OF-3 BINARY SIGNED-DIGIT NUMBER SYSTEMelelijjournal
This paper proposes new multipliers based on Binary Signed-Digit (BSD) operands. BSD number system has carry free capability in addition operation which causes high speed multiplication. In order to use the numbering system, BSD operand needs to be encoded into binary bits. 1-out-of-3 BSD encoding has been proposed as a subset of m-out-of-n codes which can be used for error detection and correction. However, a multiplier for 1-out-of-3 encoding has not yet been reported in the literature. In this paper, we propose
three different structures for 1-out-of-3 BSD multiplication for the first time to achieve an appropriate trade-off between area, delay, and power parameters. Our target implementation platform is Application Specific Circuits (ASIC).
Analysis and Implementation of Hard-Decision Viterbi Decoding In Wireless Com...IJERA Editor
Convolutional codes are also known as Turbo codes because of their error correction capability. These codes are
also awarded as Super product codes, because these codes have replaced the backward error correction codes.
Turbo codes are much more efficient than previous backward error correction codes because these are Forward
error correction (FEC) codes and there is no need for a feedback link to request the transmitter for
retransmission of data, when bits are corrupted in the information channel. A Viterbi decoder decodes stream of
digital data bits that has been encoded by Convolutional encoder. In this paper we introduce a RSC (Recursive
Systematic Convolutional) encoder with constraint length of 2 code rate of 1/3. The RSC encoder and Viterbi
decoder both are implemented on paper, as well as in MATLAB. Simulation results are also presented by using
MATLAB.
This document discusses various computer codes used to represent data internally in computers. It describes binary coded decimal (BCD), extended binary coded decimal interchange code (EBCDIC), and American standard code for information interchange (ASCII). BCD uses 6 bits to represent 64 characters, while EBCDIC and ASCII use 8 bits to represent 256 characters. EBCDIC and ASCII codes are presented with examples of encoding letters and numbers. Zoned and packed decimal formats are also discussed for encoding numeric values in EBCDIC. The document provides examples to demonstrate encoding words in BCD, EBCDIC and ASCII codes.
This document describes a 3 credit hour course on digital electronics and logic design with the code DEL-244. It covers various topics in binary codes including weighted and non-weighted systems. Specific codes discussed include binary coded decimal, excess-3 code, gray code, and two's complement representations for negative numbers. Arithmetic operations using two's complement are also demonstrated.
This document describes the design of a bipolar alternate mark inversion (AMI) digital to digital encoding data transmission system. The system uses latch, darlington amplifiers, a solid state relay, a personal computer, and Turbo C++ programming language. Bipolar AMI encoding represents 1s using alternating positive and negative voltages to eliminate DC components. The designed circuit stores input bits, amplifies the signal, and uses the relay to output the encoded signal. The software generates test data and implements the AMI encoding algorithm to control the circuit. The results show the circuit successfully encodes input bits using the bipolar AMI scheme.
An encoder is a circuit that takes a digital input and converts it to a binary code output. It performs the inverse operation of a decoder. There are different types of encoders like priority encoders, decimal to binary coded decimal encoders, and hexadecimal to binary encoders. A priority encoder gives priority to certain input lines such that if multiple lines are high, the output corresponds to the highest priority line. A decimal to BCD encoder takes a 10-bit decimal input and produces a 4-bit binary coded decimal output corresponding to each decimal value. Standard encoder integrated circuits like the 74HC147 implement common encoder functions.
This document discusses different data types and representations used in digital computers. It describes binary, octal, decimal, and hexadecimal number systems. It also discusses fixed point representation with signed-magnitude, 1's complement, and 2's complement methods. Floating point representation is covered along with the IEEE 754 standard. Methods for detecting overflow in arithmetic operations like addition and subtraction are presented.
Digital comparators are combinational logic circuits that compare digital signals at their input terminals and produce an output depending on the condition of the inputs, such as whether input A is greater than, less than, or equal to input B. Digital comparators can compare a variable number against a constant value and produce outputs indicating the three possible conditions. They use exclusive-NOR gates to compare bit pairs and cascade single-bit comparators to compare multi-bit numbers.
- Digital systems operate on discrete elements of information such as numbers, letters, and pictures by quantizing (digitizing) continuous data.
- Numbers in digital systems are represented using strings of digits in different bases, with each digit position having an associated weight. Common number bases include binary, octal, decimal, and hexadecimal.
- Information in digital systems is stored and processed using registers that are groups of binary cells (bits).
Encoders convert decimal input to binary coded decimal (BCD) output, while decoders convert BCD input to decimal output displayed on a 7-segment display. An example encoder converts decimal numbers to their BCD coded form, while an example decoder converts BCD codes into the decimal numbers they represent, which are then shown on a 7-segment LED display. The document provides examples of encodings and decoding between decimal, BCD, and 7-segment display representations and tests the reader with questions about decoding BCD inputs.
This document discusses combinational logic circuits using MSI (Medium Scale Integration) and LSI (Large Scale Integration) components. It covers various MSI components like adders, decoders, encoders, multiplexers that are used as basic building blocks. Specific circuits discussed include 4-bit parallel adder, BCD adder, magnitude comparator, priority encoder, octal to binary encoder, decoder and their applications in implementing Boolean functions using multiplexers.
This document discusses error detection and correction codes. It introduces parity bits which add an extra bit to allow detection of errors in binary data transmission. Hamming codes are described as allowing for both error detection and correction by adding multiple parity bits in specific locations. Finally, the document notes that Hamming codes can be modified to enable single error correction and double error detection.
This document defines and classifies different types of binary codes. It explains that binary codes represent numeric and alphanumeric data as groups of bits. Binary codes are classified as weighted or non-weighted, reflective or non-reflective, and sequential or non-sequential. Common binary codes include ASCII, EBCDIC, Hollerith, BCD, excess-3, and Gray codes. Error detecting and correcting codes are also discussed which add extra bits to detect or correct errors during data transmission. Examples of different binary codes are provided.
The document discusses different types of encoders. It defines an encoder as a device, circuit, transducer, software, algorithm, or person that converts information from one format to another. It provides examples of linear encoders that encode position and digital encoders that convert multiple inputs into a binary coded output. Specifically, it describes an n-bit binary encoder that has 2n inputs and n outputs, and provides truth tables for 8-to-3 and 4-to-2 bit encoders. It also discusses priority encoders that prioritize inputs and output the code of the highest priority active input.
The document discusses computer arithmetic and binary numbers. It begins by explaining why computers use the binary number system instead of decimal. The key reasons are that electronic components can only represent two states, binary is simpler for circuit design, and arithmetic is possible with binary. The document then covers the basic arithmetic operations of addition, subtraction, multiplication, and division in binary. It provides rules for each operation and examples to illustrate how to perform the calculations in binary. Finally, it discusses complementary subtraction and the additive method for multiplication and division.
This document discusses binary codes and their use in digital systems. It begins by defining code as the symbolic representation of discrete information elements. It then discusses various types of binary codes, including binary codes, decimal codes, Gray codes, error detection codes, and alphanumeric codes. It also discusses binary storage in registers and how information is transferred between registers in a computer's memory and processor units.
Dlc{binary to gray code conversion} pptTanish Gupta
BINARY TO GRAY CODE CONVERSION
1- WHAT IS A BINARY CODE ?
-> A binary code represents text or computer processor instructions using the binary number system's two binary digits, 0 and 1. The binary code assigns a bit string to each symbol or instruction.
2- WHAT IS A GRAY CODE ?
-> The reflected binary code(RBC), also known as Gray code after Frank Gray, is a binary numeral system where two successive values differ in only one bit. This code was originally designed to prevent spurious output from electromechanical switches.
THE GRAY CODE{Image in Ppt}
3- Binary-to-Gray code conversion
->
The MSB in the Gray code is the same as corresponding MSB in the binary number.
Going from left to right, add each adjacent pair of binary code bits to get the next Gray code bit. Discard carries.
ex: convert 101102 to Gray code
1 + 0 + 1 + 1 + 0 binary
1 1 1 0 1 Gray
CONVERTING CIRCUIT{Image in Ppt}
LOGIC DIAGRAM OF 4 BIT BINARY TO GRAY CODE CONVERTER{Image in Ppt}
TRUTH TABLE{Image in Ppt}
All images related to topics are in ppt.
THANK YOU
This document discusses various computer arithmetic operations including addition, subtraction, multiplication, and division for signed magnitude and two's complement data representations. It describes the Booth multiplication algorithm, array multipliers for performing multiplication using combinational circuits, and the division algorithm. It also covers detecting divide overflow conditions.
Digital Light Intensity Meter Project
Content:
Introduction
Block diagram
Main components
Schematic Diagram
How do these components work together
Practical Applications of light intensity meter
Test result
More info email Us :
Engineeringgaragevir@gmail.com
Regards
xubair khan
15-bit NOVEL Hamming Codec using HSPICE 22nm CMOS Technology based on GDI Tec...theijes
GDI(Gate Diffusion Input) technique allows low power consumption, low propagation delay and also minimum number of transistor count (low chip area) for the logic design. in this paper 15-bit NOVEL hamming codec has been proposed. This Novel hamming codec has been simulated with HSPICE using 22nm CMOS technology with various design methodologies like TG technology, pass transistor logic and GDI Technique and designs are compared to 15-bit simple hamming codec with each of various design methodologies respectively. GDI technique provide excellent result in terms power consumption, chip area and propagation delay and also novel hamming codec provide less transistor count over general hamming codec.
Error detection and correction codes add additional data bits to transmitted messages to detect and possibly correct errors caused by noise during transmission. Error-detecting codes only detect errors while error-correcting codes can detect and correct errors by determining the location of corrupted bits. Common techniques for error detection include parity checks, which use an extra parity bit to make the total number of 1 bits in a message either even or odd.
This document advertises Indus Tour & Travels' taxi and car rental services between Gurgaon and Jaipur. It provides a phone number, 9717618797, for customers to call 24/7 to book taxi or car rental services for travel between Gurgaon and Jaipur. Indus Tour & Travels offers packages for touring Jaipur from Gurgaon as well as taxi and car rental services.
Benefits of email ! Batra Computer Centrejatin batra
Are you in search Basic Computer Training in Ambala? Now your search is end here BATRA COMPUTER provides best training in C, C++, S.E.O, web designing, web development and So much courses are available .
This document discusses various computer codes used to represent data internally in computers. It describes binary coded decimal (BCD), extended binary coded decimal interchange code (EBCDIC), and American standard code for information interchange (ASCII). BCD uses 6 bits to represent 64 characters, while EBCDIC and ASCII use 8 bits to represent 256 characters. EBCDIC and ASCII codes are presented with examples of encoding letters and numbers. Zoned and packed decimal formats are also discussed for encoding numeric values in EBCDIC. The document provides examples to demonstrate encoding words in BCD, EBCDIC and ASCII codes.
This document describes a 3 credit hour course on digital electronics and logic design with the code DEL-244. It covers various topics in binary codes including weighted and non-weighted systems. Specific codes discussed include binary coded decimal, excess-3 code, gray code, and two's complement representations for negative numbers. Arithmetic operations using two's complement are also demonstrated.
This document describes the design of a bipolar alternate mark inversion (AMI) digital to digital encoding data transmission system. The system uses latch, darlington amplifiers, a solid state relay, a personal computer, and Turbo C++ programming language. Bipolar AMI encoding represents 1s using alternating positive and negative voltages to eliminate DC components. The designed circuit stores input bits, amplifies the signal, and uses the relay to output the encoded signal. The software generates test data and implements the AMI encoding algorithm to control the circuit. The results show the circuit successfully encodes input bits using the bipolar AMI scheme.
An encoder is a circuit that takes a digital input and converts it to a binary code output. It performs the inverse operation of a decoder. There are different types of encoders like priority encoders, decimal to binary coded decimal encoders, and hexadecimal to binary encoders. A priority encoder gives priority to certain input lines such that if multiple lines are high, the output corresponds to the highest priority line. A decimal to BCD encoder takes a 10-bit decimal input and produces a 4-bit binary coded decimal output corresponding to each decimal value. Standard encoder integrated circuits like the 74HC147 implement common encoder functions.
This document discusses different data types and representations used in digital computers. It describes binary, octal, decimal, and hexadecimal number systems. It also discusses fixed point representation with signed-magnitude, 1's complement, and 2's complement methods. Floating point representation is covered along with the IEEE 754 standard. Methods for detecting overflow in arithmetic operations like addition and subtraction are presented.
Digital comparators are combinational logic circuits that compare digital signals at their input terminals and produce an output depending on the condition of the inputs, such as whether input A is greater than, less than, or equal to input B. Digital comparators can compare a variable number against a constant value and produce outputs indicating the three possible conditions. They use exclusive-NOR gates to compare bit pairs and cascade single-bit comparators to compare multi-bit numbers.
- Digital systems operate on discrete elements of information such as numbers, letters, and pictures by quantizing (digitizing) continuous data.
- Numbers in digital systems are represented using strings of digits in different bases, with each digit position having an associated weight. Common number bases include binary, octal, decimal, and hexadecimal.
- Information in digital systems is stored and processed using registers that are groups of binary cells (bits).
Encoders convert decimal input to binary coded decimal (BCD) output, while decoders convert BCD input to decimal output displayed on a 7-segment display. An example encoder converts decimal numbers to their BCD coded form, while an example decoder converts BCD codes into the decimal numbers they represent, which are then shown on a 7-segment LED display. The document provides examples of encodings and decoding between decimal, BCD, and 7-segment display representations and tests the reader with questions about decoding BCD inputs.
This document discusses combinational logic circuits using MSI (Medium Scale Integration) and LSI (Large Scale Integration) components. It covers various MSI components like adders, decoders, encoders, multiplexers that are used as basic building blocks. Specific circuits discussed include 4-bit parallel adder, BCD adder, magnitude comparator, priority encoder, octal to binary encoder, decoder and their applications in implementing Boolean functions using multiplexers.
This document discusses error detection and correction codes. It introduces parity bits which add an extra bit to allow detection of errors in binary data transmission. Hamming codes are described as allowing for both error detection and correction by adding multiple parity bits in specific locations. Finally, the document notes that Hamming codes can be modified to enable single error correction and double error detection.
This document defines and classifies different types of binary codes. It explains that binary codes represent numeric and alphanumeric data as groups of bits. Binary codes are classified as weighted or non-weighted, reflective or non-reflective, and sequential or non-sequential. Common binary codes include ASCII, EBCDIC, Hollerith, BCD, excess-3, and Gray codes. Error detecting and correcting codes are also discussed which add extra bits to detect or correct errors during data transmission. Examples of different binary codes are provided.
The document discusses different types of encoders. It defines an encoder as a device, circuit, transducer, software, algorithm, or person that converts information from one format to another. It provides examples of linear encoders that encode position and digital encoders that convert multiple inputs into a binary coded output. Specifically, it describes an n-bit binary encoder that has 2n inputs and n outputs, and provides truth tables for 8-to-3 and 4-to-2 bit encoders. It also discusses priority encoders that prioritize inputs and output the code of the highest priority active input.
The document discusses computer arithmetic and binary numbers. It begins by explaining why computers use the binary number system instead of decimal. The key reasons are that electronic components can only represent two states, binary is simpler for circuit design, and arithmetic is possible with binary. The document then covers the basic arithmetic operations of addition, subtraction, multiplication, and division in binary. It provides rules for each operation and examples to illustrate how to perform the calculations in binary. Finally, it discusses complementary subtraction and the additive method for multiplication and division.
This document discusses binary codes and their use in digital systems. It begins by defining code as the symbolic representation of discrete information elements. It then discusses various types of binary codes, including binary codes, decimal codes, Gray codes, error detection codes, and alphanumeric codes. It also discusses binary storage in registers and how information is transferred between registers in a computer's memory and processor units.
Dlc{binary to gray code conversion} pptTanish Gupta
BINARY TO GRAY CODE CONVERSION
1- WHAT IS A BINARY CODE ?
-> A binary code represents text or computer processor instructions using the binary number system's two binary digits, 0 and 1. The binary code assigns a bit string to each symbol or instruction.
2- WHAT IS A GRAY CODE ?
-> The reflected binary code(RBC), also known as Gray code after Frank Gray, is a binary numeral system where two successive values differ in only one bit. This code was originally designed to prevent spurious output from electromechanical switches.
THE GRAY CODE{Image in Ppt}
3- Binary-to-Gray code conversion
->
The MSB in the Gray code is the same as corresponding MSB in the binary number.
Going from left to right, add each adjacent pair of binary code bits to get the next Gray code bit. Discard carries.
ex: convert 101102 to Gray code
1 + 0 + 1 + 1 + 0 binary
1 1 1 0 1 Gray
CONVERTING CIRCUIT{Image in Ppt}
LOGIC DIAGRAM OF 4 BIT BINARY TO GRAY CODE CONVERTER{Image in Ppt}
TRUTH TABLE{Image in Ppt}
All images related to topics are in ppt.
THANK YOU
This document discusses various computer arithmetic operations including addition, subtraction, multiplication, and division for signed magnitude and two's complement data representations. It describes the Booth multiplication algorithm, array multipliers for performing multiplication using combinational circuits, and the division algorithm. It also covers detecting divide overflow conditions.
Digital Light Intensity Meter Project
Content:
Introduction
Block diagram
Main components
Schematic Diagram
How do these components work together
Practical Applications of light intensity meter
Test result
More info email Us :
Engineeringgaragevir@gmail.com
Regards
xubair khan
15-bit NOVEL Hamming Codec using HSPICE 22nm CMOS Technology based on GDI Tec...theijes
GDI(Gate Diffusion Input) technique allows low power consumption, low propagation delay and also minimum number of transistor count (low chip area) for the logic design. in this paper 15-bit NOVEL hamming codec has been proposed. This Novel hamming codec has been simulated with HSPICE using 22nm CMOS technology with various design methodologies like TG technology, pass transistor logic and GDI Technique and designs are compared to 15-bit simple hamming codec with each of various design methodologies respectively. GDI technique provide excellent result in terms power consumption, chip area and propagation delay and also novel hamming codec provide less transistor count over general hamming codec.
Error detection and correction codes add additional data bits to transmitted messages to detect and possibly correct errors caused by noise during transmission. Error-detecting codes only detect errors while error-correcting codes can detect and correct errors by determining the location of corrupted bits. Common techniques for error detection include parity checks, which use an extra parity bit to make the total number of 1 bits in a message either even or odd.
This document advertises Indus Tour & Travels' taxi and car rental services between Gurgaon and Jaipur. It provides a phone number, 9717618797, for customers to call 24/7 to book taxi or car rental services for travel between Gurgaon and Jaipur. Indus Tour & Travels offers packages for touring Jaipur from Gurgaon as well as taxi and car rental services.
Benefits of email ! Batra Computer Centrejatin batra
Are you in search Basic Computer Training in Ambala? Now your search is end here BATRA COMPUTER provides best training in C, C++, S.E.O, web designing, web development and So much courses are available .
Tecnologías de la información y la comunicación Gustavo Abraham Castañeda Bec...abraham castañeda
El documento describe las tecnologías de la información y la comunicación (TIC). Explica que las TIC incluyen recursos como computadoras, teléfonos, televisores y otros dispositivos que se usan para procesar, administrar y compartir información. También describe algunos impactos positivos de las TIC como ampliar las capacidades humanas y posibilidades de desarrollo social. Luego define conceptos como hardware, software, sistemas operativos y otros componentes tecnológicos clave.
Віртуальна бібліотечна виставка - це, багатофункціональний інформаційний ресурс, що надає широкому колу користувачів
можливість підвищити
ефективність пошуку інформації,
розширити коло необхідних матеріалів (тексти, графіка, аудіо, відео та ін.)
Kaja Najimutheen is seeking a position as an electrical engineer. He has over 1 year of experience as an electrical engineer for AA Industries, where he oversaw electrical system installations and undertook inspections of buildings. He has a Bachelor's degree in Electrical and Electronics Engineering from Anna University with 66% and a diploma in Industrial Safety. His areas of interest include electrical design, electrical machines, and switchgear and protection. He is proficient in Windows, MS Office, and computer assembly.
This document provides information about an arrangement of the Hebrew folk song "Hevenu Shalom Aleichem" for SATB voices and keyboard. It includes the musical score, as well as notes about the song's origins and stylistic elements like augmented seconds that are common in Jewish music. The arrangement features an English text in the middle section to augment the message of peace in the original Hebrew words.
This document provides information about purchasing a 3Com 3C16981A Superstack 3 Switch 3300 from Launch 3 Telecom. It details how to purchase the product via phone, email, or by submitting a request for quote online. It also provides information about payment options, same day shipping and order tracking, warranty, and additional services offered by Launch 3 Telecom such as repairs, maintenance contracts, and equipment deinstallation.
This proposal form requests information from an applicant seeking commercial litigation insurance. It requests details about the applicant and their legal representatives, estimates of costs and the coverage sought, information about the opposing party and their representatives, and details of the claim including the nature of the dispute, evidence, damages, defenses, settlement prospects, costs awards, and enforcement. The applicant is asked to provide documentation to support their costs estimates and a breakdown of anticipated legal costs and funding arrangements. The purpose is to allow the insurer to assess the risks and make an informed decision about the application.
El documento describe varias redes sociales populares como Facebook, YouTube, Pinterest, Instagram y Twitter, y explica brevemente sus funciones principales. Luego discute la importancia de usar las redes sociales de manera responsable para proteger la reputación profesional, ya que los empleadores a menudo revisan los perfiles públicos de los candidatos. Se enfatiza la necesidad de ser cuidadoso con la información y el contenido que se publica, y de entender las configuraciones de privacidad.
My curriculum vitae is a summary of my current credentials. I am ready to enter the market place to gain knowledge and expertise in any field of business operations. I am a very driven and goal orientated individual who wants to continually grow in his profession and most importantly as an individual.
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FPGA Based Decimal Matrix Code for Passive RFID Tag
1. Neelappa. Int. Journal of Engineering Research and Application www.ijera.com
ISSN : 2248-9622, Vol. 7, Issue 1, ( Part -1) Janaury 2017, pp.63-67
www.ijera.com 63 | P a g e
FPGA Based Decimal Matrix Code for Passive RFID Tag
Neelappa1
, N.G.Kurahatti2
1
Asst. Professor, Department of E and C, Govt. Engineering College Kushalanagar, Karnataka-571234.
2
Professor, Department of E and C, East point college of Engineering and Technology, Bangalore, Karnataka
ABSTRACT
In this paper, Decimal Matrix Code is developed for RFID passive tag. The proposed DMC uses the decimal
algorithm to obtain the maximum error detection and correction capability. The Encoder-Reuse Technique is
used to minimize the area overhead of extra circuits without disturbing the complete encoding and decoding
processes. ERT uses DMC encoder itself to be part of the decoder. The Simulation results reveals that the
Decimal Matrix Code is effective than existing Matrix and Hamming odes in terms of Error Correction
Capability. Xilinx ISE 14.7 Software is used for the simulation outputs. The complete design is verified and
tested on Spartan-6 FPGA board. The performance of system is measured in terms of power, area and delay.
The Synthesis result shows that, the power required for complete design of Decimal Matrix Code is 0.1mW with
a delay of 3.109ns.
Keywords: RFID, base band processor, HDL, FPGA, DMC
I. INTRODUCTION
Radio Frequency Identification (RFID) is “An
automatic identification technology that uses radio
frequency signals to transmit the identity of objects
in the form of a unique serial number”. This
technology does not use line of sight for
communication between reader and tag. It is the
best choice for automatic identification due to
flexibility, easy to use, contactless, multiple tag
identification, high data rate, long read range and
the lowest cost. RFID application is growing in
many fields such as smart table, access control,
animal tracking, logistics, supermarkets, airport
baggage handling, antifraud systems and medical
treatment [1-5]. RFID system consists of reader,
tag and antenna. The reader has antenna that
send/receive radio frequency signals to/from tags.
Tag shares the data with the reader through radio
frequency signals. The main component of the tag
is digital base band processor which controls the all
the functions of the tag. Several Decimal Matrix
Code have been presented before namely, Jing
Guo,[8] presented a paper on a “Enhanced Memory
Reliability Against Multiple Cell Upsets Using
Decimal Matrix Code” with reduced power
consumption and chip area with a power
consumption of about 10.8mW and area
41572.6μm2
. The challenge in designing UHF
passive RFID tag is to reduce power consumption
because the energy of a passive tag comes from the
signal sent by a reader and also it is a power limited
device. The operation range of a RFID system
depending on the maximum of the dynamic power
of the tag. There are static power dissipation and
dynamic power dissipation in the VLSI circuit.
Dynamic power dissipation includes switching
power due to charge and discharge of load
capacitance of input signals. Static power
dissipation result from the leakage current when
the logic gate is static [6]. To reduce power
consumption and area in RFID tag, a DMC coding
technique is included and there by power
dissipation, area and delay of the RFID tag are
reduced. In this proposed paper, we have developed
a DMC coding technique for UHF RFID tag which
includes, encoding and decoding architecture
compatible with ISO/IEC 1800-6 tag on Spartan 6
FPGA to observe its functionality. The DMC
coding technique is developed by ModelSim is
implemented and verified on Spartan-6 FPGA.
This paper is organized as follows: Section 2
defines DMC encoder. Section 3 describes DMC
encoder. Section 4 simulation results. Finally
section 5 presents the Conclusion.
II. DMC ENCODER
DMC Encoder, which uses decimal algorithm to
increase the error detection and correction
capability. In this algorithm power consumed will
be less compared to other detection methods. This
algorithm involves decimal integer subtraction and
integer addition. In the decimal algorithm, the
divide-symbol and arrange-matrix are performed.
Here the N-bit word is divided into n symbols of m
bits (𝑁 = 𝑛 × 𝑚), and these symbols are arranged
in a n= 𝑛1 × 𝑛2 2-D matrix (n1=number of
columns and n2 =number of rows). The horizontal
redundant bits H are obtained by performing
decimal integer addition on symbols per row.
Finally, then vertical redundant bits V are obtained
by binary operation on the bits per column. It is
noted that both divide-symbol and arrange-matrix
are presented in logical instead of in physical.
RESEARCH ARTICLE OPEN ACCESS
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Figure.2.1.1 32-bits DMC logical Organization [8]
To explain the DMC scheme, take a 32-bit word is
input, which is shown in Fig.2.1.1. The cells from
D0 to D31 are information bits. This 32-bit word has
been divided into eight symbols of 4-bits. n1=2 and
n2=4 have been chosen simultaneously. 𝐻0 − 𝐻19
are horizontal check bits;V0 through V15 are
vertical check bits.
The horizontal redundant bits H can be obtained by
decimal integer addition as follows:
𝐻4 𝐻3 𝐻2 𝐻1 𝐻0=𝐷3 𝐷2 𝐷1 𝐷0 + 𝐷11 𝐷10 𝐷9 𝐷8 1
𝐻7 𝐻6 𝐻5 = 𝐷7 𝐷6 𝐷5 𝐷4 + 𝐷15 𝐷14 𝐷13 𝐷12 2
Similarly other remaining horizontal redundant
bits are obtained where “+”represents decimal
integer addition.
For the vertical redundant bits V, we have
𝑉0 = 𝐷0 ⊕ 𝐷16 3
𝑉1 = 𝐷1 ⊕ 𝐷17 4
In a similar manner remaining vertical redundant
bits are obtained. The encoding can be done by
decimal and binary addition operations from (1) to
(4). The encoder that computes the redundant bits
using multi-bit adders and XOR gates is shown in
Fig.2.1.2 In this figure, H19−H0 are horizontal
redundant bits, V15−V0 are vertical redundant bits,
and the remaining bits U31−U0 are the information
bits which are directly copied from D31 to D0.
Fig. 2.1.2 32 bit DMC encoder structure using
multi bit adders and XOR gate [8]
III. DMC Decoder
For the correction of word obtained, the decoding
process is required. At the beginning, the received
redundant 𝐻4 𝐻3 𝐻2 𝐻1 𝐻0
′
and 𝑉0′ − 𝑉3
′
are
generated by the received information bits D‟.
Secondly, the horizontal syndrome bits
𝐻4 𝐻3 𝐻2 𝐻1 𝐻0 and the vertical syndrome bits S3
−S0 can be calculated as follows:
△ 𝐻4 𝐻3 𝐻2 𝐻1 𝐻0
′
=𝐻4 𝐻3 𝐻2 𝐻1 𝐻0
′
− 𝐻4 𝐻3 𝐻2 𝐻1 𝐻0 5
𝑆3 − 𝑆0 =𝑉0′⊕𝑉0 6
Similarly for the remaining vertical syndrome bits.
Where “−” represents decimal integer subtraction.
When △ 𝐻4 𝐻3 𝐻2 𝐻1 𝐻0
′
and 𝑆3 − 𝑆0 are equal to
zero, the stored codeword has original information
bits in symbol 0 are nonzero, then there is an error.
Induced errors are detected and located in symbol 0
and these errors can be corrected by
𝐷0𝐶𝑜𝑟𝑟𝑒𝑐𝑡 = 𝐷0⊕𝑆0 7
Figure.2.2.1 32-bit DMC decoder [8]
The DMC decoder is used in our design is shown
in Fig.2.2.1, which consists of Syndrome
calculator, Error locator, and Error corrector. Here,
each module performs a particular function in the
decoding process. It is noted from Fig. 2.2.1, that
the redundant bits re obtained from the received
information bits „D‟ and compared with the
original set of redundant bits in order to obtain the
syndrome bits △ 𝐻 and S. Then, error locator uses
△ 𝐻 and S to detect and locate error bits. Finally,
the error corrector corrects the error bits by
inverting the values of error bits. The „En‟ signal is
used to decide whether encoder is a part of the
decoder.
IV. SIMULATION RESULTS
The proposed design has been done in Verilog
HDL. Simulated using model Sim Simulator. For
synthesis, we have used the EDA tool Xilinx and
all sub module simulation results and top module
results are shown in the following sections.
Figure.4.1 shows the simulation result and of
encoder module. Input is a 32-bit tag ID number
and generates 20-bit horizontal and 16-bit vertical
redundant numbers as output.
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Figure.4.1.Simulation result of encoder
Figure.4.2 shows the simulation result of
transmitter module. The 32-bit Tag ID number is
input to this module. It generates a output frame of
68-bit length. The frame contains 16-bit vertical
redundant number, 20-bit horizontal redundant
number and 32-bit input.
Figure.4.2 Simulation result of transmitter
The Figure.4.3 shows simulation result of encoder
in receiver. The received data may be corrupted
due to the transmission error. So, the error data is
given to this module as an input, then it generates
20-bit horizontal redundant bits and 16-bit vertical
redundant bits derived from error data as an output.
Figure.4.3 Simulation waveform of encoder in receiver
Figure. 4.4 shows the simulation result of CRC
module, to check whether the received data bits are
correct or not. It calculates the vertical syndrome
bits by XORing the original vertical V [15-0] bits
with the vertical bits being derived from received
data Vd [15-0].
Figure.4.4 Simulation result of CRC for vertical
syndrome bits
Figure.4.5 shows the simulation result of CRC
module, to calculate horizontal syndrome and
whether the received data bits are corrupted or not.
It calculates the horizontal syndrome bits by
subtracting the original horizontal H [19-0] bits
with the horizontal bits which are derived from
received data Hd [19-0]. If it is non-zero value the
data is corrupted otherwise it is not corrupted.
Figure.4.5 Simulation result of CRC for horizontal
syndrome bits
The Figure 4.6 shows simulation result of
corrector, the 32-bit error data, computed 20-bit
horizontal syndrome bits and 16-bit vertical
syndrome bits given as an input to the model. It
generates a output of corrected 32-bit data.
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Figure 4.6 Simulation waveform of corrector
Figure.4.7 shows the simulation result of receiver
module, the 68-bit frame is input and generates 32-
bit decoded data as an output. It performs the data
correction if it is required. This module is
comprised of CRC and error corrector modules.
Figure.4.7 Simulation result of receiver
Figure.4.8 It consists of all sub modules such as
encoder, decoder, CRC checker, error corrector,
frame generator and buffer. It fetches the 32-bit tag
ID number stored in ROM memory, performs
encoding, frame generating, decoding, error
corrections and generates fetched 32-bit tag ID as
output.
Figure 4.8 Simulation results of Top Module
The table 4.1 shows Area Comparison summary of
the DMC Technique. It indicates that DMC Technique
performance is better in terms of area when compared
with other publications.
Table 4.1 Area Comparison summary of the DMC
Technique.
Name Ref. No[13] Ref. No[14] This work
No. of Slices 75 38 15
No. of flip-flops 100 50 15
No. of LUTs 132 68 14
No. of Logic 196 50 13
No .of IOS 72 56 44
No. of bounded IOB 72 40 44
No. of GCLK 1 1 1
Total 584 321 146
Various other parameters such as Delay and Power
Summary for DMC Technique are shown in the
table 4.2 for various ECC‟s. This Technique has
better performance in terms of power and speed.
Table 4.2 Power and delay comparison summary of the
DMC Technique
Type of ECC used Slices flip flops LUTs Bounded
IO
Delay(ns) Power
This work 174 30 96 44 3.10ns 0.5mW
DMC[40] NA NA NA NA 4.9ns 10.8mW
PDS* [41] NA NA NA NA 18.7ns 221.1mW
MC [15] NA NA NA NA 7.1ns 24.7mW
Matrix
Code
164 32 291 96 14.548ns 0.121W
Hamming
Code
1350 32 2682 84 17.133ns 0.163W
PIE/FM0
[21]
NA NA NA NA NA 1.58mW
V. CONCLUSION
In this paper, the Decimal Matrix Code for UHF
passive RFID tag has been presented. Encoder re-
use technique reduced the area overhead of extra
circuits. Simulation and synthesis results reveal that
our Decimal Matrix Code can complete its function
successfully with power consumption of about
0.1 mW, delay is about 3.109 ns.
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