Audio File Compression Using Counter Propagation Neural Network

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, Grossbe...

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Main Author: Saja Mohammed
Format: Article
Language:English
Published: Mosul University 2010-06-01
Series:Al-Rafidain Journal of Computer Sciences and Mathematics
Subjects:
Online Access:https://csmj.mosuljournals.com/article_163869_c8facf3ec6f5260da9e51a4bf2034d81.pdf
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author Saja Mohammed
author_facet Saja Mohammed
author_sort Saja Mohammed
collection DOAJ
description 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.
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record_format Article
series Al-Rafidain Journal of Computer Sciences and Mathematics
spelling doaj-art-e494c220fcb14693917f766d86c9c7572025-08-20T03:09:58ZengMosul UniversityAl-Rafidain Journal of Computer Sciences and Mathematics1815-48162311-79902010-06-017115316810.33899/csmj.2010.163869163869Audio File Compression Using Counter Propagation Neural NetworkSaja Mohammed0University of Mosul/ College of Computer Science and MathematicsIn 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.https://csmj.mosuljournals.com/article_163869_c8facf3ec6f5260da9e51a4bf2034d81.pdfneural networkcounter propagationcompressionaudio file
spellingShingle Saja Mohammed
Audio File Compression Using Counter Propagation Neural Network
Al-Rafidain Journal of Computer Sciences and Mathematics
neural network
counter propagation
compression
audio file
title Audio File Compression Using Counter Propagation Neural Network
title_full Audio File Compression Using Counter Propagation Neural Network
title_fullStr Audio File Compression Using Counter Propagation Neural Network
title_full_unstemmed Audio File Compression Using Counter Propagation Neural Network
title_short Audio File Compression Using Counter Propagation Neural Network
title_sort audio file compression using counter propagation neural network
topic neural network
counter propagation
compression
audio file
url https://csmj.mosuljournals.com/article_163869_c8facf3ec6f5260da9e51a4bf2034d81.pdf
work_keys_str_mv AT sajamohammed audiofilecompressionusingcounterpropagationneuralnetwork