Advances in Electrical and Computer Engineering (2011-08-01)

Fault Tolerant Neural Network for ECG Signal Classification Systems

  • MERAH, M.,
  • OUAMRI, A.,
  • NAIT-ALI, A.,
  • KECHE, M.

DOI
https://doi.org/10.4316/AECE.2011.03003
Journal volume & issue
Vol. 11, no. 3
pp. 17 – 24

Abstract

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The aim of this paper is to apply a new robust hardware Artificial Neural Network (ANN) for ECG classification systems. This ANN includes a penalization criterion which makes the performances in terms of robustness. Specifically, in this method, the ANN weights are normalized using the auto-prune method. Simulations performed on the MIT ? BIH ECG signals, have shown that significant robustness improvements are obtained regarding potential hardware artificial neuron failures. Moreover, we show that the proposed design achieves better generalization performances, compared to the standard back-propagation algorithm.

Keywords