Data Mining: Multimedia, Soft Computing, and Bioinformatics
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Page 52
... output nodes form a weighted linear combination of the basis functions computed by the hidden nodes . The input and output nodes correspond to the input features and output classes , while the hidden nodes represent the number of ...
... output nodes form a weighted linear combination of the basis functions computed by the hidden nodes . The input and output nodes correspond to the input features and output classes , while the hidden nodes represent the number of ...
Page 136
... output is the pattern for entry 2 in the dictionary concatenated by the decoded symbol b . Since entry 2 represents a , the output will be ab . A new pattern ab is now inserted in index 4 of the dictionary . The following input pair is ...
... output is the pattern for entry 2 in the dictionary concatenated by the decoded symbol b . Since entry 2 represents a , the output will be ab . A new pattern ab is now inserted in index 4 of the dictionary . The following input pair is ...
Page 138
... outputs the index 7 to encode cb , and it stops . As a result , the output of the LZW encoder is 2 1 4 3 4 8 5 7 . It should be noted that statistical probabilities of appearance of the pointers from the LZW encoder can be further ...
... outputs the index 7 to encode cb , and it stops . As a result , the output of the LZW encoder is 2 1 4 3 4 8 5 7 . It should be noted that statistical probabilities of appearance of the pointers from the LZW encoder can be further ...
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