Neural Networks for Pattern Recognition

Neural Networks for Pattern Recognition
Author: Christopher M. Bishop
Publisher: Oxford University Press
Total Pages: 501
Release: 1995-11-23
Genre: Computers
ISBN: 0198538642

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Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.


Neural Networks for Pattern Recognition
Language: en
Pages: 501
Authors: Christopher M. Bishop
Categories: Computers
Type: BOOK - Published: 1995-11-23 - Publisher: Oxford University Press

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Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Par
Artificial Neural Networks in Pattern Recognition
Language: en
Pages: 415
Authors: Luca Pancioni
Categories: Computers
Type: BOOK - Published: 2018-08-29 - Publisher: Springer

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This book constitutes the refereed proceedings of the 8th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2018, held
Pattern Recognition and Neural Networks
Language: en
Pages: 420
Authors: Brian D. Ripley
Categories: Computers
Type: BOOK - Published: 2007 - Publisher: Cambridge University Press

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This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.
Pattern Recognition with Neural Networks in C++
Language: en
Pages: 434
Authors: Abhijit S. Pandya
Categories: Computers
Type: BOOK - Published: 1995-10-17 - Publisher: CRC Press

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The addition of artificial neural network computing to traditional pattern recognition has given rise to a new, different, and more powerful methodology that is
Pattern Recognition by Self-organizing Neural Networks
Language: en
Pages: 724
Authors: Gail A. Carpenter
Categories: Computers
Type: BOOK - Published: 1991 - Publisher: MIT Press

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Pattern Recognition by Self-Organizing Neural Networks presentsthe most recent advances in an area of research that is becoming vitally important in the fields