Hamming Code Performance Evaluation using Artificial Neural Network Decoder

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.