Vector quantization neural network for ECG signal compression

Better compression results can be achieved by coding vectors instead of scalars. The proposed algorithm is used for competitive learning of a vector quantization neural network, which is used to generate a codebook for the vector quantization of ECG signals. The competitive learning algorithm can successfully group the sample group to generate the codebook and reproduce at the time of reconstruction.