Hamming code performance evaluation using artificial neural network decoder

Aldrin Claytus Vaz, C. Gurudas Nayak, Dayananda Nayak

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the increase in the connectivity among various electronic devices day-by-day, the technology has stepped up into a new era of Internet-of-Things. To ensure the accuracy, integrity and fault-tolerance in the transmitted data, Error Correcting Codes are used. Various techniques are available to decode the received data and correct the errors. In this paper, an approach based on Artificial Neural Networks (ANN) is been used to decode the received data because of their real-time operation, self-organization and adaptive learning. Back propagation Algorithm for feed forward ANN has been simulated using MATLAB for (7, 4) Hamming Code. The synaptic weights are updated during each training cycle. The designed ANN is trained for all possible combination of code words such that it can detect and correct 1-bit error. The Bit Error rate performance of the proposed ANN based method is compared with the syndrome decoding.

Original languageEnglish
Title of host publication2019 15th International Conference on Engineering of Modern Electric Systems, EMES 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages37-40
Number of pages4
ISBN (Electronic)9781728107738
DOIs
Publication statusPublished - 06-2019
Event15th International Conference on Engineering of Modern Electric Systems, EMES 2019 - Oradea, Romania
Duration: 13-06-201914-06-2019

Publication series

Name2019 15th International Conference on Engineering of Modern Electric Systems, EMES 2019

Conference

Conference15th International Conference on Engineering of Modern Electric Systems, EMES 2019
CountryRomania
CityOradea
Period13-06-1914-06-19

Fingerprint

decoders
artificial neural network
Neural networks
evaluation
real time operation
error correcting codes
fault tolerance
self organization
Backpropagation algorithms
back propagation
decoding
bit error rate
Fault tolerance
Bit error rate
integrity
learning
MATLAB
Decoding
connectivity
education

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Hardware and Architecture
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Waste Management and Disposal
  • Instrumentation

Cite this

Vaz, A. C., Nayak, C. G., & Nayak, D. (2019). Hamming code performance evaluation using artificial neural network decoder. In 2019 15th International Conference on Engineering of Modern Electric Systems, EMES 2019 (pp. 37-40). [8795093] (2019 15th International Conference on Engineering of Modern Electric Systems, EMES 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMES.2019.8795093
Vaz, Aldrin Claytus ; Nayak, C. Gurudas ; Nayak, Dayananda. / Hamming code performance evaluation using artificial neural network decoder. 2019 15th International Conference on Engineering of Modern Electric Systems, EMES 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 37-40 (2019 15th International Conference on Engineering of Modern Electric Systems, EMES 2019).
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Vaz, AC, Nayak, CG & Nayak, D 2019, Hamming code performance evaluation using artificial neural network decoder. in 2019 15th International Conference on Engineering of Modern Electric Systems, EMES 2019., 8795093, 2019 15th International Conference on Engineering of Modern Electric Systems, EMES 2019, Institute of Electrical and Electronics Engineers Inc., pp. 37-40, 15th International Conference on Engineering of Modern Electric Systems, EMES 2019, Oradea, Romania, 13-06-19. https://doi.org/10.1109/EMES.2019.8795093

Hamming code performance evaluation using artificial neural network decoder. / Vaz, Aldrin Claytus; Nayak, C. Gurudas; Nayak, Dayananda.

2019 15th International Conference on Engineering of Modern Electric Systems, EMES 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 37-40 8795093 (2019 15th International Conference on Engineering of Modern Electric Systems, EMES 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Vaz AC, Nayak CG, Nayak D. Hamming code performance evaluation using artificial neural network decoder. In 2019 15th International Conference on Engineering of Modern Electric Systems, EMES 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 37-40. 8795093. (2019 15th International Conference on Engineering of Modern Electric Systems, EMES 2019). https://doi.org/10.1109/EMES.2019.8795093