AL-Rafidain Journal of Computer Sciences and Mathematics

Abstract

In this paper audio files are compressed using counter propagation neural network (CPNN) which is one of the fastest neural networks in multi media. The utilized counter propagation neural network was trained on uncompressed sound file to obtain the final weights of this CPNN (Kohonen layer, Grossberg layer ).
In compression operation: the sound signal segmented to number of frames equal in size. Then these frames are applied step by step, to the first layer of the neural network(kohonen layer) to obtain some compression results. The decompression operation done by retrieve stored information  in resulted file. This information is applied to second layer of this CPNN (Grosberg layer) which will perform decompression operation and retrieve the original sound file. The proposed algorithm is applied on (.wav) audio files , The results show high performance in addition to short time in compression and decompression operation.