Neural Networks For Pattern Recognition


Neural Networks For Pattern Recognition
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Neural Networks For Pattern Recognition


Neural Networks For Pattern Recognition
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Author : Christopher M. Bishop
language : en
Publisher: Oxford University Press
Release Date : 1995-11-23

Neural Networks For Pattern Recognition written by Christopher M. Bishop and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-11-23 with Computers categories.


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


Neural Networks For Pattern Recognition
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Author : Albert Nigrin
language : en
Publisher: MIT Press
Release Date : 1993

Neural Networks For Pattern Recognition written by Albert Nigrin and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Computers categories.


In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Neural Networks for Pattern Recognition takes the pioneering work in artificial neural networks by Stephen Grossberg and his colleagues to a new level. In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Following a tutorial of existing neural networks for pattern classification, Nigrin expands on these networks to present fundamentally new architectures that perform realtime pattern classification of embedded and synonymous patterns and that will aid in tasks such as vision, speech recognition, sensor fusion, and constraint satisfaction. Nigrin presents the new architectures in two stages. First he presents a network called Sonnet 1 that already achieves important properties such as the ability to learn and segment continuously varied input patterns in real time, to process patterns in a context sensitive fashion, and to learn new patterns without degrading existing categories. He then removes simplifications inherent in Sonnet 1 and introduces radically new architectures. These architectures have the power to classify patterns that may have similar meanings but that have different external appearances (synonyms). They also have been designed to represent patterns in a distributed fashion, both in short-term and long-term memory.



Neural Networks In Pattern Recognition And Their Applications


Neural Networks In Pattern Recognition And Their Applications
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Author : Chi-hau Chen
language : en
Publisher: World Scientific
Release Date : 1991

Neural Networks In Pattern Recognition And Their Applications written by Chi-hau Chen and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Computers categories.


The revitalization of neural network research in the past few years has already had a great impact on research and development in pattern recognition and artificial intelligence. Although neural network functions are not limited to pattern recognition, there is no doubt that a renewed progress in pattern recognition and its applications now critically depends on neural networks. This volume specially brings together outstanding original research papers in the area and aims to help the continued progress in pattern recognition and its applications.



Artificial Neural Networks In Pattern Recognition


Artificial Neural Networks In Pattern Recognition
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Author : Frank-Peter Schilling
language : en
Publisher: Springer Nature
Release Date : 2020-09-01

Artificial Neural Networks In Pattern Recognition written by Frank-Peter Schilling and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-01 with Computers categories.


This book constitutes the refereed proceedings of the 9th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2020, held in Winterthur, Switzerland, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 22 revised full papers presented were carefully reviewed and selected from 34 submissions. The papers present and discuss the latest research in all areas of neural network-and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications.



Pattern Recognition And Neural Networks


Pattern Recognition And Neural Networks
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Author : Brian D. Ripley
language : en
Publisher: Cambridge University Press
Release Date : 2007

Pattern Recognition And Neural Networks written by Brian D. Ripley and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.


This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.



Artificial Neural Networks In Pattern Recognition


Artificial Neural Networks In Pattern Recognition
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Author : Luca Pancioni
language : en
Publisher: Springer
Release Date : 2018-08-29

Artificial Neural Networks In Pattern Recognition written by Luca Pancioni and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-29 with Computers categories.


This book constitutes the refereed proceedings of the 8th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2018, held in Siena, Italy, in September 2018. The 29 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 35 submissions. The papers present and discuss the latest research in all areas of neural network- and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications. Chapter "Bounded Rational Decision-Making with Adaptive Neural Network Priors" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.



Artificial Neural Networks In Pattern Recognition


Artificial Neural Networks In Pattern Recognition
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Author : Nadia Mana
language : en
Publisher: Springer
Release Date : 2012-09-11

Artificial Neural Networks In Pattern Recognition written by Nadia Mana and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-11 with Computers categories.


This book constitutes the refereed proceedings of the 5th INNS IAPR TC3 GIRPR International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2012, held in Trento, Italy, in September 2012. The 21 revised full papers presented were carefully reviewed and selected for inclusion in this volume. They cover a large range of topics in the field of neural network- and machine learning-based pattern recognition presenting and discussing the latest research, results, and ideas in these areas.



Artificial Neural Networks In Pattern Recognition


Artificial Neural Networks In Pattern Recognition
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Author : Lionel Prevost
language : en
Publisher: Springer
Release Date : 2008-06-30

Artificial Neural Networks In Pattern Recognition written by Lionel Prevost and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-06-30 with Computers categories.


Annotation This book constitutes the refereed proceedings of the Third TC3 IAPR Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2008, held in Paris, France, in July 2008. The 18 revised full papers and 11 revised poster papers presented were carefully reviewed and selected from 57 submissions. The papers combine many ideas from machine learning, advanced statistics, signal and image processing for solving complex real-world pattern recognition problems. The papers are organized in topical sections on unsupervised learning, supervised learning, multiple classifiers, applications, and feature selection.



Artificial Neural Networks In Pattern Recognition


Artificial Neural Networks In Pattern Recognition
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Author : Neamat El Gayar
language : en
Publisher: Springer
Release Date : 2014-09-29

Artificial Neural Networks In Pattern Recognition written by Neamat El Gayar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-29 with Computers categories.


This book constitutes the refereed proceedings of the 6th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2014, held in Montreal, QC, Canada, in October 2014. The 24 revised full papers presented were carefully reviewed and selected from 37 submissions for inclusion in this volume. They cover a large range of topics in the field of learning algorithms and architectures and discussing the latest research, results, and ideas in these areas.



Neural Networks And Pattern Recognition


Neural Networks And Pattern Recognition
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Author : Omid Omidvar
language : en
Publisher: Academic Press
Release Date : 1998

Neural Networks And Pattern Recognition written by Omid Omidvar and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Business & Economics categories.


Pulse-coupled neural networks; A neural network model for optical flow computation; Temporal pattern matching using an artificial neural network; Patterns of dynamic activity and timing in neural network processing; A macroscopic model of oscillation in ensembles of inhibitory and excitatory neurons; Finite state machines and recurrent neural networks: automata and dynamical systems approaches; biased random-waldk learning; a neurobiological correlate to trial-and-error; Using SONNET 1 to segment continuous sequences of items; On the use of high-level petri nets in the modeling of biological neural networks; Locally recurrent networks: the gmma operator, properties, and extensions.