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Information-Theoretic Aspects of Neural Networks

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Release : 2020-09-23
Genre : Technology & Engineering
Kind : eBook
Book Rating : 25X/5 ( reviews)

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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. This book was released on 2020-09-23. 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.

Information-Theoretic Aspects of Neural Networks

Download Information-Theoretic Aspects of Neural Networks PDF Online Free

Author :
Release : 2020-09-23
Genre : History
Kind : eBook
Book Rating : 750/5 ( reviews)

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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. This book was released on 2020-09-23. 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.

Information-Theoretic Aspects of Neural Networks

Download Information-Theoretic Aspects of Neural Networks PDF Online Free

Author :
Release : 1999-03-30
Genre : Computers
Kind : eBook
Book Rating : 985/5 ( reviews)

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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. This book was released on 1999-03-30. 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

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Author :
Release : 2012-12-06
Genre : Computers
Kind : eBook
Book Rating : 166/5 ( reviews)

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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. This book was released on 2012-12-06. 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.

Information Theoretic Learning

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Author :
Release : 2010-04-06
Genre : Computers
Kind : eBook
Book Rating : 702/5 ( reviews)

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Book Synopsis Information Theoretic Learning by : Jose C. Principe

Download or read book Information Theoretic Learning written by Jose C. Principe. This book was released on 2010-04-06. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first cohesive treatment of ITL algorithms to adapt linear or nonlinear learning machines both in supervised and unsupervised paradigms. It compares the performance of ITL algorithms with the second order counterparts in many applications.

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