Vaz, Aldrin and Nayak, Gurudas C and Nayak, Dayananda (2020) Neural network decoder for (7, 4) hamming code. International Journal of Inteeligent System Technologies and Applications, 19 (4). pp. 405-420. ISSN 1740-8865

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Abstract

To ensure the accuracy, integrity, and fault-tolerance in the data to be transmitted, error correcting codes (ECC) are used. To decode the received data and correct the errors, different techniques have been developed. In this paper, artificial neural networks (ANN) have been used instead of traditional error-correcting techniques, because of their real-time operation, self-organisation, and adaptive learning and to project what will most likely happen on the analogy of human brain. A decoding approach based on the backpropagation algorithm for feed-forward ANN has been simulated using MATLAB for (7, 4) hamming code. The designed ANN is trained on all possible combinations of code words such that it can detect and correct up to 1-bit error. The synaptic weights are updated during each training cycle of the network. The simulation results show that the proposed technique is correctly able to detect and correct 1-bit error in the received dat

Item Type:	Article
Uncontrolled Keywords:	artificial neural network; ANN; back propagation algorithm; error correcting code; hamming code.
Subjects:	Engineering > MIT Manipal > Instrumentation and Control
Depositing User:	MIT Library
Date Deposited:	12 Jan 2021 09:16
Last Modified:	12 Jan 2021 09:16
URI:	http://eprints.manipal.edu/id/eprint/156200

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