A network processing model for address learning and IP recognition
Information Sciences—Informatics and Computer Science: An International Journal
Letters: Fast image compression using matrix K-L transform
Neurocomputing
Bidirectional associative memories: Different approaches
ACM Computing Surveys (CSUR)
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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