Theoretical Aspects Of Neurocomputing

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Theoretical Aspects Of Neurocomputing: Selected Papers From The Symposium On Neural Networks And Neurocomputing (Neuronet '90)

Author : Novak Mirko
Publisher : World Scientific
ISBN 13 : 9814569208
Total Pages : 300 pages
Book Rating : 4.8/5 (145 download)

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Book Synopsis Theoretical Aspects Of Neurocomputing: Selected Papers From The Symposium On Neural Networks And Neurocomputing (Neuronet '90) by : Novak Mirko

Download or read book Theoretical Aspects Of Neurocomputing: Selected Papers From The Symposium On Neural Networks And Neurocomputing (Neuronet '90) written by Novak Mirko and published by World Scientific. This book was released on 1991-03-15 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains a selection of both full and extended contributions presented at NEURONET '90. These contributions are predominantly oriented towards the theoretical problems of neurocomputing, and involve a wide scope of aspects — from neurophysiology and cytology to theoretical problems in neural network architectures, mathematical background of neurocomputing and learning strategies.

Theoretical Aspects of Neurocomputing

Author : M. Novak
Publisher :
ISBN 13 :
Total Pages : 289 pages
Book Rating : 4.:/5 (658 download)

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Book Synopsis Theoretical Aspects of Neurocomputing by : M. Novak

Download or read book Theoretical Aspects of Neurocomputing written by M. Novak and published by . This book was released on 1991 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Theoretical Aspects of Neurocomputing

Author : M. Novak
Publisher : World Scientific Publishing Company
ISBN 13 :
Total Pages : 308 pages
Book Rating : 4.:/5 (43 download)

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Book Synopsis Theoretical Aspects of Neurocomputing by : M. Novak

Download or read book Theoretical Aspects of Neurocomputing written by M. Novak and published by World Scientific Publishing Company. This book was released on 1991 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains a selection of both full and extended contributions presented at NEURONET '90. These contributions are predominantly oriented towards the theoretical problems of neurocomputing, and involve a wide scope of aspects -- from neurophysiology and cytology to theoretical problems in neural network architectures, mathematical background of neurocomputing and learning strategies.

Theoretical Aspects of Neurocomputing

Author : Mirko Novak
Publisher :
ISBN 13 : 9789814539302
Total Pages : 302 pages
Book Rating : 4.5/5 (393 download)

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Book Synopsis Theoretical Aspects of Neurocomputing by : Mirko Novak

Download or read book Theoretical Aspects of Neurocomputing written by Mirko Novak and published by . This book was released on 1991 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Information-Theoretic Aspects of Neural Networks

Author : P. S. Neelakanta
Publisher : CRC Press
ISBN 13 : 1000102750
Total Pages : 417 pages
Book Rating : 4.0/5 (1 download)

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Book Synopsis Information-Theoretic Aspects of Neural Networks by : P. S. Neelakanta

Download or read book Information-Theoretic Aspects of Neural Networks written by P. S. Neelakanta and published by CRC Press. This book was released on 2020-09-23 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theoretics vis-a-vis neural networks generally embodies parametric entities and conceptual bases pertinent to memory considerations and information storage, information-theoretic based cost-functions, and neurocybernetics and self-organization. Existing studies only sparsely cover the entropy and/or cybernetic aspects of neural information. Information-Theoretic Aspects of Neural Networks cohesively explores this burgeoning discipline, covering topics such as: Shannon information and information dynamics neural complexity as an information processing system memory and information storage in the interconnected neural web extremum (maximum and minimum) information entropy neural network training non-conventional, statistical distance-measures for neural network optimizations symmetric and asymmetric characteristics of information-theoretic error-metrics algorithmic complexity based representation of neural information-theoretic parameters genetic algorithms versus neural information dynamics of neurocybernetics viewed in the information-theoretic plane nonlinear, information-theoretic transfer function of the neural cellular units statistical mechanics, neural networks, and information theory semiotic framework of neural information processing and neural information flow fuzzy information and neural networks neural dynamics conceived through fuzzy information parameters neural information flow dynamics informatics of neural stochastic resonance Information-Theoretic Aspects of Neural Networks acts as an exceptional resource for engineers, scientists, and computer scientists working in the field of artificial neural networks as well as biologists applying the concepts of communication theory and protocols to the functioning of the brain. The information in this book explores new avenues in the field and creates a common platform for analyzing the neural complex as well as artificial neural networks.

An Information-Theoretic Approach to Neural Computing

Author : Gustavo Deco
Publisher : Springer Science & Business Media
ISBN 13 : 1461240166
Total Pages : 265 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis An Information-Theoretic Approach to Neural Computing by : Gustavo Deco

Download or read book An Information-Theoretic Approach to Neural Computing written by Gustavo Deco and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: A detailed formulation of neural networks from the information-theoretic viewpoint. The authors show how this perspective provides new insights into the design theory of neural networks. In particular they demonstrate how these methods may be applied to the topics of supervised and unsupervised learning, including feature extraction, linear and non-linear independent component analysis, and Boltzmann machines. Readers are assumed to have a basic understanding of neural networks, but all the relevant concepts from information theory are carefully introduced and explained. Consequently, readers from varied scientific disciplines, notably cognitive scientists, engineers, physicists, statisticians, and computer scientists, will find this an extremely valuable introduction to this topic.

Principles of Neurocomputing for Science and Engineering

Author : Fredric M. Ham
Publisher : McGraw-Hill Science, Engineering & Mathematics
ISBN 13 :
Total Pages : 680 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Principles of Neurocomputing for Science and Engineering by : Fredric M. Ham

Download or read book Principles of Neurocomputing for Science and Engineering written by Fredric M. Ham and published by McGraw-Hill Science, Engineering & Mathematics. This book was released on 2000 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neurocomputing can be applied to problems such as pattern recognition, optimization, event classification, control and identification of nonlinear systems, and statistical analysis - just to name a few. This book is intended for a course in neural networks."--BOOK JACKET.

Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications

Author : Oscar Castillo
Publisher : Springer
ISBN 13 : 3319710087
Total Pages : 546 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications by : Oscar Castillo

Download or read book Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications written by Oscar Castillo and published by Springer. This book was released on 2018-01-10 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises papers on diverse aspects of fuzzy logic, neural networks, and nature-inspired optimization meta-heuristics and their application in various areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book is organized into seven main parts, each with a collection of papers on a similar subject. The first part presents new concepts and algorithms based on type-2 fuzzy logic for dynamic parameter adaptation in meta-heuristics. The second part discusses network theory and applications, and includes papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The third part addresses the theory and practice of meta-heuristics in different areas of application, while the fourth part describes diverse fuzzy logic applications in the control area, which can be considered as intelligent controllers. The next two parts explore applications in areas, such as time series prediction, and pattern recognition and new optimization and evolutionary algorithms and their applications respectively. Lastly, the seventh part addresses the design and application of different hybrid intelligent systems.

Bio-inspired Neurocomputing

Author : Akash Kumar Bhoi
Publisher : Springer Nature
ISBN 13 : 9811554951
Total Pages : 427 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Bio-inspired Neurocomputing by : Akash Kumar Bhoi

Download or read book Bio-inspired Neurocomputing written by Akash Kumar Bhoi and published by Springer Nature. This book was released on 2020-07-21 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the latest technological advances in neuro-computational intelligence in biological processes where the primary focus is on biologically inspired neuro-computational techniques. The theoretical and practical aspects of biomedical neural computing, brain-inspired computing, bio-computational models, artificial intelligence (AI) and machine learning (ML) approaches in biomedical data analytics are covered along with their qualitative and quantitative features. The contents cover numerous computational applications, methodologies and emerging challenges in the field of bio-soft computing and bio-signal processing. The authors have taken meticulous care in describing the fundamental concepts, identifying the research gap and highlighting the problems with the strategical computational approaches to address the ongoing challenges in bio-inspired models and algorithms. Given the range of topics covered, this book can be a valuable resource for students, researchers as well as practitioners interested in the rapidly evolving field of neurocomputing and biomedical data analytics.

RAM-based Neural Networks

Author : James Austin
Publisher : World Scientific
ISBN 13 : 9789810232535
Total Pages : 256 pages
Book Rating : 4.2/5 (325 download)

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Book Synopsis RAM-based Neural Networks by : James Austin

Download or read book RAM-based Neural Networks written by James Austin and published by World Scientific. This book was released on 1998 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: RAM-based networks are a class of methods for building pattern recognition systems. Unlike other neural network methods, they learn very quickly and as a result are applicable to a wide variety of problems. This important book presents the latest work by the majority of researchers in the field of RAM-based networks.

Computational Ecology

Author : Wenjun Zhang
Publisher : World Scientific
ISBN 13 : 9814282626
Total Pages : 310 pages
Book Rating : 4.8/5 (142 download)

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Book Synopsis Computational Ecology by : Wenjun Zhang

Download or read book Computational Ecology written by Wenjun Zhang and published by World Scientific. This book was released on 2010 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the complexity and non-linearity of most ecological problems, artificial neural networks (ANNs) have attracted attention from ecologists and environmental scientists. This book provides readers with knowledge on algorithms, programs, and applications of ANNs in ecology. It proposes computational ecology.

Knowledge-based Neurocomputing

Author : Ian Cloete
Publisher : MIT Press
ISBN 13 : 9780262032742
Total Pages : 512 pages
Book Rating : 4.0/5 (327 download)

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Book Synopsis Knowledge-based Neurocomputing by : Ian Cloete

Download or read book Knowledge-based Neurocomputing written by Ian Cloete and published by MIT Press. This book was released on 2000 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: Looking at ways to encode prior knowledge and to extract, refine, and revise knowledge within a neurocomputing system.Neurocomputing methods are loosely based on a model of the brain as a network of simple interconnected processing elements corresponding to neurons. These methods derive their power from the collective processing of artificial neurons, the chief advantage being that such systems can learn and adapt to a changing environment. In knowledge-based neurocomputing, the emphasis is on the use and representation of knowledge about an application. Explicit modeling of the knowledge represented by such a system remains a major research topic. The reason is that humans find it difficult to interpret the numeric representation of a neural network.The key assumption of knowledge-based neurocomputing is that knowledge is obtainable from, or can be represented by, a neurocomputing system in a form that humans can understand. That is, the knowledge embedded in the neurocomputing system can also be represented in a symbolic or well-structured form, such as Boolean functions, automata, rules, or other familiar ways. The focus of knowledge-based computing is on methods to encode prior knowledge and to extract, refine, and revise knowledge within a neurocomputing system.ContributorsC. Aldrich, J. Cervenka, I. Cloete, R.A. Cozzio, R. Drossu, J. Fletcher, C.L. Giles, F.S. Gouws, M. Hilario, M. Ishikawa, A. Lozowski, Z. Obradovic, C.W. Omlin, M. Riedmiller, P. Romero, G.P.J. Schmitz, J. Sima, A. Sperduti, M. Spott, J. Weisbrod, J.M. Zurada

The Handbook of Brain Theory and Neural Networks

Author : Michael A. Arbib
Publisher : MIT Press
ISBN 13 : 0262011972
Total Pages : 1328 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis The Handbook of Brain Theory and Neural Networks by : Michael A. Arbib

Download or read book The Handbook of Brain Theory and Neural Networks written by Michael A. Arbib and published by MIT Press. This book was released on 2003 with total page 1328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions : how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).

Rough-Neural Computing

Author : Sankar Kumar Pal
Publisher : Springer Science & Business Media
ISBN 13 : 3642188591
Total Pages : 741 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Rough-Neural Computing by : Sankar Kumar Pal

Download or read book Rough-Neural Computing written by Sankar Kumar Pal and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soft computing comprises various paradigms dedicated to approximately solving real-world problems, e.g. in decision making, classification or learning; among these paradigms are fuzzy sets, rough sets, neural networks, genetic algorithms, and others. It is well understood now in the soft computing community that hybrid approaches combining various paradigms are very promising approaches for solving complex problems. Exploiting the potential and strength of both neural networks and rough sets, this book is devoted to rough-neuro computing which is also related to the novel aspect of computing based on information granulation, in particular to computing with words. It provides foundational and methodological issues as well as applications in various fields.

An Information-Theoretic Approach to Neural Computing

Author : Gustavo Deco
Publisher : Springer Science & Business Media
ISBN 13 : 9780387946665
Total Pages : 288 pages
Book Rating : 4.9/5 (466 download)

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Book Synopsis An Information-Theoretic Approach to Neural Computing by : Gustavo Deco

Download or read book An Information-Theoretic Approach to Neural Computing written by Gustavo Deco and published by Springer Science & Business Media. This book was released on 1996-02-08 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks provide a powerful new technology to model and control nonlinear and complex systems. In this book, the authors present a detailed formulation of neural networks from the information-theoretic viewpoint. They show how this perspective provides new insights into the design theory of neural networks. In particular they show how these methods may be applied to the topics of supervised and unsupervised learning including feature extraction, linear and non-linear independent component analysis, and Boltzmann machines. Readers are assumed to have a basic understanding of neural networks, but all the relevant concepts from information theory are carefully introduced and explained. Consequently, readers from several different scientific disciplines, notably cognitive scientists, engineers, physicists, statisticians, and computer scientists, will find this to be a very valuable introduction to this topic.

Artificial Neural Networks - ICANN 2007

Author : Joaquim Marques de Sá
Publisher : Springer
ISBN 13 : 3540746951
Total Pages : 990 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Artificial Neural Networks - ICANN 2007 by : Joaquim Marques de Sá

Download or read book Artificial Neural Networks - ICANN 2007 written by Joaquim Marques de Sá and published by Springer. This book was released on 2007-09-14 with total page 990 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the second of a two-volume set that constitutes the refereed proceedings of the 17th International Conference on Artificial Neural Networks, ICANN 2007. It features contributions related to computational neuroscience, neurocognitive studies, applications in biomedicine and bioinformatics, pattern recognition, self-organization, text mining and internet applications, signal and times series processing, vision and image processing, robotics, control, and more.

From Parallel to Emergent Computing

Author : Andrew Adamatzky
Publisher : CRC Press
ISBN 13 : 1351681923
Total Pages : 608 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis From Parallel to Emergent Computing by : Andrew Adamatzky

Download or read book From Parallel to Emergent Computing written by Andrew Adamatzky and published by CRC Press. This book was released on 2019-03-13 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern computing relies on future and emergent technologies which have been conceived via interaction between computer science, engineering, chemistry, physics and biology. This highly interdisciplinary book presents advances in the fields of parallel, distributed and emergent information processing and computation. The book represents major breakthroughs in parallel quantum protocols, elastic cloud servers, structural properties of interconnection networks, internet of things, morphogenetic collective systems, swarm intelligence and cellular automata, unconventionality in parallel computation, algorithmic information dynamics, localized DNA computation, graph-based cryptography, slime mold inspired nano-electronics and cytoskeleton computers. Features Truly interdisciplinary, spanning computer science, electronics, mathematics and biology Covers widely popular topics of future and emergent computing technologies, cloud computing, parallel computing, DNA computation, security and network analysis, cryptography, and theoretical computer science Provides unique chapters written by top experts in theoretical and applied computer science, information processing and engineering From Parallel to Emergent Computing provides a visionary statement on how computing will advance in the next 25 years and what new fields of science will be involved in computing engineering. This book is a valuable resource for computer scientists working today, and in years to come.