DocumentCode
1345226
Title
Data compression by the recursive algorithm of exponential bidirectional associative memory
Author
Wang, Chua-Chin ; Tsai, Chang-Rong
Author_Institution
Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan
Volume
28
Issue
2
fYear
1998
fDate
4/1/1998 12:00:00 AM
Firstpage
125
Lastpage
134
Abstract
A novel data compression algorithm utilizing the histogram and the high-capacity exponential bidirectional associative memory (eBAM) is presented. Since eBAM has been proved to possess high capacity and fault tolerance, it is suitable to be utilized in the data compression using the table-lookup scheme. The histogram approach is employed to extract the feature vectors in the given data. The result of the simulation of the proposed algorithm turns out to be better than the traditional methods
Keywords
content-addressable storage; data compression; vector quantisation; SNR; associative memory; data compression; eBAM; exponential bidirectional; histogram; recursive algorithm; table-lookup; vector quantization; Associative memory; Data compression; Data mining; Fault tolerance; Feature extraction; Histograms; Image coding; Magnesium compounds; Neural networks; Vector quantization;
fLanguage
English
Journal_Title
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
Publisher
ieee
ISSN
1083-4419
Type
jour
DOI
10.1109/3477.662754
Filename
662754
Link To Document