Data Mining: Multimedia, Soft Computing, and Bioinformatics
|
From inside the book
Results 1-3 of 33
Page 103
... matrix F of rank L there exists an M × M unitary matrix U and an N × N unitary matrix V so that UT FV = A3 , where X ( 1 ) λ ( 2 ) A 12 = X ( L ) 0 0 ( 3.6 ) is an M × N diagonal matrix and the first L diagonal elements \ ( i ) , for i ...
... matrix F of rank L there exists an M × M unitary matrix U and an N × N unitary matrix V so that UT FV = A3 , where X ( 1 ) λ ( 2 ) A 12 = X ( L ) 0 0 ( 3.6 ) is an M × N diagonal matrix and the first L diagonal elements \ ( i ) , for i ...
Page 120
... Matrix , and it is the prerogative of the user to select the matrix . There are two quantization matrices provided in Annex K of the JPEG standard for reference , but not as a requirement . These two quantization matrices are shown in ...
... Matrix , and it is the prerogative of the user to select the matrix . There are two quantization matrices provided in Annex K of the JPEG standard for reference , but not as a requirement . These two quantization matrices are shown in ...
Page 337
... matrix is constructed based on the orientation and distance between image pixels . Meaningful statistics are extracted from this co - occurrence matrix , as the representation of texture . Since basic texture patterns are governed by ...
... matrix is constructed based on the orientation and distance between image pixels . Meaningful statistics are extracted from this co - occurrence matrix , as the representation of texture . Since basic texture patterns are governed by ...
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