Theoretical Aspects Of Neurocomputing: Selected Papers From The Symposium On Neural Networks And Neurocomputing (Neuronet '90) PDF Download
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Author: Novak Mirko
Publisher: World Scientific
ISBN: 9814569208
Category :
Languages : en
Pages : 300
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Book Description
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.
Author: Novak Mirko
Publisher: World Scientific
ISBN: 9814569208
Category :
Languages : en
Pages : 300
Get Book Here
Book Description
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.
Author: M. Novak
Publisher:
ISBN:
Category :
Languages : en
Pages : 289
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Book Description
Author: M. Novak
Publisher: World Scientific Publishing Company
ISBN:
Category : Computers
Languages : en
Pages : 308
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Book Description
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.
Author: Mirko Novak
Publisher:
ISBN: 9789814539302
Category : Neural computers
Languages : en
Pages : 302
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Book Description
Author: Fredric M. Ham
Publisher: McGraw-Hill Science, Engineering & Mathematics
ISBN:
Category : Computers
Languages : en
Pages : 680
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Book Description
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.
Author: P. S. Neelakanta
Publisher: CRC Press
ISBN: 1000102750
Category : History
Languages : en
Pages : 417
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Book Description
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.
Author: Gustavo Deco
Publisher: Springer Science & Business Media
ISBN: 1461240166
Category : Computers
Languages : en
Pages : 265
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Book Description
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.
Author: Akash Kumar Bhoi
Publisher: Springer Nature
ISBN: 9811554951
Category : Technology & Engineering
Languages : en
Pages : 427
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Book Description
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.
Author: Oscar Castillo
Publisher: Springer
ISBN: 3319710087
Category : Technology & Engineering
Languages : en
Pages : 535
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Book Description
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.
Author: James Austin
Publisher: World Scientific
ISBN: 9789810232535
Category : Computers
Languages : en
Pages : 256
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Book Description
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.
