scholarly journals Lookup Table Algorithm for Error Correction in Color Images

2018 ◽  
Vol 2 (2) ◽  
pp. 63
Author(s):  
Ruaa Alaadeen Abdulsattar ◽  
Nada Hussein M. Ali
Keyword(s):  
Error Correction ◽  
Error Detection ◽  
Color Image ◽  
Color Images ◽  
Lookup Table ◽  
Hamming Code ◽  
Detection Techniques ◽  
Error Ratio ◽  
Error Detection And Correction ◽  
Large Burst

Error correction and error detection techniques are often used in wireless transmission systems. A color image of type BMP is considered as an application of developed lookup table algorithms to detect and correct errors in these images. Decimal Matrix Code (DMC) and Hamming code (HC) techniques were integrated to compose Hybrid Matrix Code (HMC) to maximize the error detection and correction. The results obtained from HMC still have some error not corrected because the redundant bits added by Hamming codes to the data are considered inadequate, and it is suitable when the error rate is low for detection and correction processes. Besides, a Hamming code could not detect large burst error period, in addition, the have same values sometimes which lead to not detect the error and consequently increase the error ratio. The proposed algorithm LUT_CORR is presented to detect and correct errors in color images over noisy channels, the proposed algorithm depends on the parallel Cyclic Redundancy Code (CRC) method that's based on two algorithms: Sarwate and slicing By N algorithms. The LUT-CORR and the aforementioned algorithms were merged to correct errors in color images, the output results correct the corrupted images with a 100 % ratio almost. The above high correction ratio due to some unique values that the LUT-CORR algorithm have. The HMC and the proposed algorithm applied to different BMP images, the obtained results from LUT-CORR are compared to HMC for both Mean Square Error (MSE) and correction ratio.  The outcome from the proposed algorithm shows a good performance and has a high correction ratio to retrieve the source BMP image.

scholarly journals Error Detection and Correction On-Board Nanosatellites Using Hamming Codes

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Caleb Hillier ◽  
Vipin Balyan
Keyword(s):  
Error Correction ◽  
Error Detection ◽  
Simulation Software ◽  
Hamming Code ◽  
Single Event ◽  
Hamming Codes ◽  
Single Event Effects ◽  
Effective Version ◽  
Fast Speed ◽  
Error Detection And Correction

The field of nanosatellites is constantly evolving and growing at a very fast speed. This creates a growing demand for more advanced and reliable EDAC systems that are capable of protecting all memory aspects of satellites. The Hamming code was identified as a suitable EDAC scheme for the prevention of single event effects on-board a nanosatellite in LEO. In this paper, three variations of Hamming codes are tested both in Matlab and VHDL. The most effective version was Hamming [16, 11, 4]2. This code guarantees single-error correction and double-error detection. All developed Hamming codes are suited for FPGA implementation, for which they are tested thoroughly using simulation software and optimized.

scholarly journals BIT ERROR DETECTION AND CORRECTION WITH HAMMING CODE ALGORITHM

2017 ◽  
Author(s):  
Robbi Rahim
Keyword(s):  
Error Detection ◽  
Scientific Research ◽  
Hamming Code ◽  
Error Detection And Correction ◽  
Engineering And Technology ◽  
Code Algorithm

This paper has been published in International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET) Volume 3 Issue 1 year of 2017

Design of High-Speed Decoder for New High-Speed Bus

2010 ◽  
Vol 20-23 ◽  
pp. 958-962
Author(s):  
Wei Gong Zhang ◽  
Bo Yang ◽  
Rui Ding ◽  
Yong Qin Hu
Keyword(s):  
Error Correction ◽  
Intelligent Control ◽  
Error Detection ◽  
High Speed ◽  
Critical Path ◽  
Speed Error ◽  
Error Detection And Correction ◽  
Traditional Algorithm ◽  
New Type ◽  
Correction System

This paper presents a new type of high-speed error correction for the requirements of new high-Speed Bus. Use RS (255, 239). Not only optimization traditional algorithm, but also design bidirectional synchronous calculated adjoint form module, Fast B-M algorithm module. and full parallel Chien Search module. These design used in new high-Speed Bus, Larger than usual decoder designed to significantly shorten the critical path decoding, and achieve continuous decoding. In addition, this error correction system separated error detection and correction module modules, And after error detection module add intelligent control, which reduced the complexity and power consumption of equipment. The error correction system design for the requirements of the new bus which speed is above 400m / s.

What does a Man do after he Makes an Error? An Analysis of Response Programming

1977 ◽  
Vol 29 (4) ◽  
pp. 727-743 ◽  
Author(s):  
Patrick Rabbitt ◽  
Bryan Rodgers
Keyword(s):  
Information Processing ◽  
Error Correction ◽  
Error Detection ◽  
Single Channel ◽  
Previous Trial ◽  
Limited Capacity ◽  
Error Detection And Correction ◽  
Channel Information ◽  
The Subject ◽  
Response Programming

When people make errors during continuous tasks they temporarily pause and then slow down. One line of explanation has been that they monitor feedback to detect errors, that they may make incidental responses when errors occur (e.g. they may swear) and that they may pause to analyse their errors. In all these cases they may be assumed to act as single channel information processing systems of limited capacity, and to be unable to recognise any new signal until these processes have been completed. Analysis of response after errors shows that this cannot be the case. Responses after errors are inaccurate, but are not slow when they require the subject to make the response which he should have made on the previous trial (i.e. to make an error correction response). Subjects thus must recognise new signals as soon as they occur. The present results require a new model of error detection and correction, and a model for response programming and priming.

scholarly journals SEC-TAED based Error Detection and Correction Technique for Data Transmission Systems

2018 ◽  
Vol 10 (2) ◽  
pp. 696
Author(s):  
Mr. G. Manikandan ◽  
Dr. M. Anand
Keyword(s):  
Error Detection ◽  
Gaussian Noise ◽  
Data Transmission ◽  
High Speed ◽  
Additive White Gaussian Noise ◽  
Hamming Code ◽  
Correction Technique ◽  
Error Detection And Correction ◽  
Placement Algorithm ◽  
Original Information

<p>In the OFDM communication system channel encoder and decoder is the part of the architecture. OFDM channel is mostly affected by Additive White Gaussian Noise (AWGN) in which bit flipping of original information leads to fault transmission in the channel. To overcome this problem by using hamming code for error detection and correction. Hamming codes are more attractive and it easy to process the encoding and decoding with low latency. In general the hamming is perfectly detected and corrects the single bit error. In this paper, design of single Error Correction-Triple Adjacent Error Detection (SEC-TAED) codes with bit placement algorithm is presented with less number of parity bits. In the conventional Double Adjacent Error Detection (DAED) and Hamming (13, 8) SEC-TAED are process the codes and detects the error, but it require more parity bits for performing the operation. The higher number of parity bits causes processing delay. To avoid this problem by proposed the Hamming (12, 8) SEC-TAED code, it require only four parity bits to perform the detection process. Bit-reordered format used in the method increases the probability detection of triple adjacent error. It is more suitable for efficient and high speed communication.</p>

Taking DDL online

2020 ◽  
Vol 43 (2) ◽  
pp. 169-195 ◽  
Author(s):  
Peter Crosthwaite
Keyword(s):  
Error Correction ◽  
Academic Writing ◽  
Error Detection ◽  
Data Driven ◽  
Online Course ◽  
Design And Implementation ◽  
Methodological Challenges ◽  
Error Detection And Correction

Abstract This paper describes the rationale, design and implementation of a short private online course (SPOC) on data-driven learning (DDL) (Johns, 1991), focusing on L2 error correction in postgraduate academic writing and involving over 300 registered users. I discuss the affordances of using a SPOC platform (namely EdX) for online DDL training, describing activities that cover a range of useful strategies for DDL-led error detection and correction. Learners’ usage of the SPOC platform and their quantitative and qualitative perceptions of the course are described for the reader. The paper also outlines certain conceptual and methodological challenges involved in taking DDL instruction online.

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