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An Improved Compression Scheme Using Particle Swarm Optimised Neural Network for ECG Signals

M.J.Jayashree, Dr.A.Sukesh Kumar

The emergence of artificial neural networks in signal processing has led to improvements in signal compression. In this paper a comparison of ECG signal compression using Multi Layer Perceptron(MLP) neural network and Particle Swarm Optimisation(PSO) is made. For this different back propagation artificial networks are used as compressor and decompressor. Particle swarm optimisation (PSO) is used for optimising the learning rate and momentum. The proposed algorithm yields minimum mean square error for the ECG signals from MIT-BIH arrhythmia data base.