Adaptive Pattern Recognition And Neural Networks

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Adaptive Pattern Recognition And Neural Networks

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Author : Yoh-Han Pao
language : en
Publisher: Addison Wesley Publishing Company
Release Date : 1989

Adaptive Pattern Recognition And Neural Networks written by Yoh-Han Pao and has been published by Addison Wesley Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Computers categories.

A coherent introduction to the basic concepts of pattern recognition, incorporating recent advances from AI, neurobiology, engineering, and other disciplines. Treats specifically the implementation of adaptive pattern recognition to neural networks. Annotation copyright Book News, Inc. Portland, Or.

Adaptive Pattern Recognition And Neural Networks

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Author : Yoh-Han Pao
language : it
Publisher:
Release Date : 1989

Adaptive Pattern Recognition And Neural Networks written by Yoh-Han Pao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with categories.

Pattern Recognition With Neural Networks In C

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Author : Abhijit S. Pandya
language : en
Publisher: CRC Press
Release Date : 2020

Pattern Recognition With Neural Networks In C written by Abhijit S. Pandya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computers categories.

The addition of artificial neural network computing to traditional pattern recognition has given rise to a new, different, and more powerful methodology that is presented in this interesting book. This is a practical guide to the application of artificial neural networks. Geared toward the practitioner, Pattern Recognition with Neural Networks in C++ covers pattern classification and neural network approaches within the same framework. Through the book's presentation of underlying theory and numerous practical examples, readers gain an understanding that will allow them to make judicious design choices rendering neural application predictable and effective. The book provides an intuitive explanation of each method for each network paradigm. This discussion is supported by a rigorous mathematical approach where necessary. C++ has emerged as a rich and descriptive means by which concepts, models, or algorithms can be precisely described. For many of the neural network models discussed, C++ programs are presented for the actual implementation. Pictorial diagrams and in-depth discussions explain each topic. Necessary derivative steps for the mathematical models are included so that readers can incorporate new ideas into their programs as the field advances with new developments. For each approach, the authors clearly state the known theoretical results, the known tendencies of the approach, and their recommendations for getting the best results from the method. The material covered in the book is accessible to working engineers with little or no explicit background in neural networks. However, the material is presented in sufficient depth so that those with prior knowledge will find this book beneficial. Pattern Recognition with Neural Networks in C++ is also suitable for courses in neural networks at an advanced undergraduate or graduate level. This book is valuable for academic as well as practical research.

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.

Pattern Recognition By Self Organizing Neural Networks

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Author : Gail A. Carpenter
language : en
Publisher: MIT Press
Release Date : 1991

Pattern Recognition By Self Organizing Neural Networks written by Gail A. Carpenter and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Computers categories.

Pattern Recognition by Self-Organizing Neural Networks presentsthe most recent advances in an area of research that is becoming vitally important in the fields ofcognitive science, neuroscience, artificial intelligence, and neural networks in general. The 19articles take up developments in competitive learning and computational maps, adaptive resonancetheory, and specialized architectures and biological connections. Introductorysurvey articles provide a framework for understanding the many models involved in various approachesto studying neural networks. These are followed in Part 2 by articles that form the foundation formodels of competitive learning and computational mapping, and recent articles by Kohonen, applyingthem to problems in speech recognition, and by Hecht-Nielsen, applying them to problems in designingadaptive lookup tables. Articles in Part 3 focus on adaptive resonance theory (ART) networks,selforganizing pattern recognition systems whose top-down template feedback signals guarantee theirstable learning in response to arbitrary sequences of input patterns. In Part 4, articles describeembedding ART modules into larger architectures and provide experimental evidence fromneurophysiology, event-related potentials, and psychology that support the prediction that ARTmechanisms exist in the brain. Contributors: J.-P. Banquet, G.A. Carpenter, S.Grossberg, R. Hecht-Nielsen, T. Kohonen, B. Kosko, T.W. Ryan, N.A. Schmajuk, W. Singer, D. Stork, C.von der Malsburg, C.L. Winter.

Neural Networks And Adaptive Pattern Recognition

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Author : Olli Simula
language : en
Publisher:
Release Date : 1991

Neural Networks And Adaptive Pattern Recognition written by Olli Simula and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with categories.

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.

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.

Adaptive Pattern Recognition Approach For Dynamic System Control Using Neural Networks

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Author : Dennis Tak-Fat Lee
language : en
Publisher:
Release Date : 1991

Adaptive Pattern Recognition Approach For Dynamic System Control Using Neural Networks written by Dennis Tak-Fat Lee and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with categories.

Neural Networks For Intelligent Signal Processing

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Author : Anthony Zaknich
language : en
Publisher: World Scientific
Release Date : 2003-01-23

Neural Networks For Intelligent Signal Processing written by Anthony Zaknich and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-01-23 with Computers categories.

This book provides a thorough theoretical and practical introduction to the application of neural networks to pattern recognition and intelligent signal processing. It has been tested on students, unfamiliar with neural networks, who were able to pick up enough details to successfully complete their masters or final year undergraduate projects. The text also presents a comprehensive treatment of a class of neural networks called common bandwidth spherical basis function NNs, including the probabilistic NN, the modified probabilistic NN and the general regression NN.