ECG DATA-COMPRESSION USING HEBBIAN NEURAL NETWORKS

Principal component analysis has long been used for a variety of signa l processing applications, including signal compression. Neural networ k implementations of principal component analysis provide a means for unsupervised feature discovery and dimension reduction. In this paper we describe a method for the compression of ECG data using principal c omponent analysis. Hebbian neural networks were used for principal com ponents computation. A variety of examples of normal and pathological ECGs obtained from the MIT ECG database demonstrate that the proposed method cart provide compression ratio up to 30 with PRD% less than 5%.