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Pattern Classification (2nd ed.) by Duda, Richard O. …
Pattern Classification (2nd ed.) by Richard O. Duda. The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances.
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Pattern Classification - Richard O. Duda, Peter E. …
The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises ...
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The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises ...
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PATTERN CLASSIFICATION Second Edition Richard O. Duda Peter E. Hart DavidG. Stork AWiley-Interscience Publication JOHNWILEY&SONS,INC. NewYork …
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Pattern Classification (eBook, PDF) von Peter E. Hart ...
Pattern Classification (eBook, PDF) ... RICHARD O. DUDA, PhD, is Professor in the Electrical Engineering Department at San Jose State University, San Jose, California. PETER E. HART, PhD, is Chief Executive Officer and President of Ricoh Innovations, Inc. in Menlo Park, California.
Pattern Classification, Second Edition: 1 (A Wiley ...
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Pattern Classification by Richard O. Duda · …
The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances.