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
fDate :
4/1/1998 12:00:00 AM
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;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/3477.662754
