Data Mining: Multimedia, Soft Computing, and Bioinformatics
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Page 93
... sequence often helps in reducing the entropy estimation of the source . Let us consider that the numeric data sequence generated by a source of alphabet A2 = { 0 , 1 , 2 , 3 } is D = 0 1 1 2 3 3 3 3 3 3 3 3 3 2 2 2 3 3 3 3 , as an ...
... sequence often helps in reducing the entropy estimation of the source . Let us consider that the numeric data sequence generated by a source of alphabet A2 = { 0 , 1 , 2 , 3 } is D = 0 1 1 2 3 3 3 3 3 3 3 3 3 2 2 2 3 3 3 3 , as an ...
Page 132
... sequence that precedes the current coding position , can be considered as a dictionary . The encoder matches the input sequence through a sliding window , as illustrated in Fig . 3.18 . The window is divided into two parts , namely ...
... sequence that precedes the current coding position , can be considered as a dictionary . The encoder matches the input sequence through a sliding window , as illustrated in Fig . 3.18 . The window is divided into two parts , namely ...
Page 366
... sequence . BLAST compares the new sequence to all sequences in the database to find the most similar known sequences . Advances related to recognizing protein interactions , improving homology search , and identifying cellular location ...
... sequence . BLAST compares the new sequence to all sequences in the database to find the most similar known sequences . Advances related to recognizing protein interactions , improving homology search , and identifying cellular location ...
Contents
Soft Computing | 37 |
Multimedia Data Compression | 89 |
standard | 129 |
Copyright | |
9 other sections not shown
Other editions - View all
Data Mining: Multimedia, Soft Computing, and Bioinformatics Sushmita Mitra,Tinku Acharya Limited preview - 2005 |
Data Mining: Multimedia, Soft Computing, and Bioinformatics Sushmita Mitra,Tinku Acharya No preview available - 2005 |
Common terms and phrases
applications approach association rules ATATA binary Bioinformatics Boyer-Moore algorithm C₁ categorical classification clustering coding coefficients color components computational complexity content-based image retrieval corresponding data compression data mining database dataset decision tree decoder defined dictionary distance document domain efficient encoder outputs entropy entropy encoding evaluation example extracted feature fuzzy sets gene Hence Huffman code IEEE Transactions image retrieval initial input integer involving JPEG Karp-Rabin knowledge discovery knowledge-based network learning length linguistic matching algorithms matrix measure method mismatch Mitra multimedia data neural networks neuro-fuzzy neurons objects occurrence optimal partition pattern matching pixel prediction prefix protein pruning quantization query represented result rough set sample Section sequence shown in Fig soft computing split statistical string matching structure substring suffix symbol Table techniques text mining transformed vector wavelet Web mining weights