An Information Theoretic Approach To Neural Network Design

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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.

Information Theory, Inference and Learning Algorithms

Author : David J. C. MacKay
Publisher : Cambridge University Press
ISBN 13 : 9780521642989
Total Pages : 694 pages
Book Rating : 4.6/5 (429 download)

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Book Synopsis Information Theory, Inference and Learning Algorithms by : David J. C. MacKay

Download or read book Information Theory, Inference and Learning Algorithms written by David J. C. MacKay and published by Cambridge University Press. This book was released on 2003-09-25 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.

The Principles of Deep Learning Theory

Author : Daniel A. Roberts
Publisher : Cambridge University Press
ISBN 13 : 1316519333
Total Pages : 473 pages
Book Rating : 4.3/5 (165 download)

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Book Synopsis The Principles of Deep Learning Theory by : Daniel A. Roberts

Download or read book The Principles of Deep Learning Theory written by Daniel A. Roberts and published by Cambridge University Press. This book was released on 2022-05-26 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume develops an effective theory approach to understanding deep neural networks of practical relevance.

Advances in Neural Network Research and Applications

Author : Zhigang Zeng
Publisher : Springer Science & Business Media
ISBN 13 : 3642129900
Total Pages : 921 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Advances in Neural Network Research and Applications by : Zhigang Zeng

Download or read book Advances in Neural Network Research and Applications written by Zhigang Zeng and published by Springer Science & Business Media. This book was released on 2010-05-10 with total page 921 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a part of the Proceedings of the Seventh International Symposium on Neural Networks (ISNN 2010), held on June 6-9, 2010 in Shanghai, China. Over the past few years, ISNN has matured into a well-established premier international symposium on neural networks and related fields, with a successful sequence of ISNN series in Dalian (2004), Chongqing (2005), Chengdu (2006), Nanjing (2007), Beijing (2008), and Wuhan (2009). Following the tradition of ISNN series, ISNN 2010 provided a high-level international forum for scientists, engineers, and educators to present the state-of-the-art research in neural networks and related fields, and also discuss the major opportunities and challenges of future neural network research. Over the past decades, the neural network community has witnessed significant breakthroughs and developments from all aspects of neural network research, including theoretical foundations, architectures, and network organizations, modeling and simulation, empirical studies, as well as a wide range of applications across different domains. The recent developments of science and technology, including neuroscience, computer science, cognitive science, nano-technologies and engineering design, among others, has provided significant new understandings and technological solutions to move the neural network research toward the development of complex, large scale, and networked brain-like intelligent systems. This long-term goals can only be achieved with the continuous efforts from the community to seriously investigate various issues on neural networks and related topics.

Information-Theoretic Aspects of Neural Networks

Author : P. S. Neelakanta
Publisher : CRC Press
ISBN 13 : 100014125X
Total Pages : 233 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 233 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.

Information Theoretic Learning

Author : Jose C. Principe
Publisher : Springer Science & Business Media
ISBN 13 : 1441915702
Total Pages : 538 pages
Book Rating : 4.4/5 (419 download)

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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 and published by Springer Science & Business Media. This book was released on 2010-04-06 with total page 538 pages. 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.

Artificial Neural Networks-Icann '97

Author : Wulfram Gerstner
Publisher : Springer Science & Business Media
ISBN 13 : 9783540636311
Total Pages : 1300 pages
Book Rating : 4.6/5 (363 download)

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Book Synopsis Artificial Neural Networks-Icann '97 by : Wulfram Gerstner

Download or read book Artificial Neural Networks-Icann '97 written by Wulfram Gerstner and published by Springer Science & Business Media. This book was released on 1997-09-29 with total page 1300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Content Description #Includes bibliographical references and index.

Information-Theoretic Methods in Data Science

Author : Miguel R. D. Rodrigues
Publisher : Cambridge University Press
ISBN 13 : 1108427138
Total Pages : 561 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Information-Theoretic Methods in Data Science by : Miguel R. D. Rodrigues

Download or read book Information-Theoretic Methods in Data Science written by Miguel R. D. Rodrigues and published by Cambridge University Press. This book was released on 2021-04-08 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first unified treatment of the interface between information theory and emerging topics in data science, written in a clear, tutorial style. Covering topics such as data acquisition, representation, analysis, and communication, it is ideal for graduate students and researchers in information theory, signal processing, and machine learning.

Textbook Of Bioinformatics, A: Information-theoretic Perspectives Of Bioengineering And Biological Complexes

Author : Perambur S Neelakanta
Publisher : World Scientific
ISBN 13 : 9811212902
Total Pages : 684 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Textbook Of Bioinformatics, A: Information-theoretic Perspectives Of Bioengineering And Biological Complexes by : Perambur S Neelakanta

Download or read book Textbook Of Bioinformatics, A: Information-theoretic Perspectives Of Bioengineering And Biological Complexes written by Perambur S Neelakanta and published by World Scientific. This book was released on 2020-08-24 with total page 684 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book on bioinformatics is designed as an introduction to the conventional details of genomics and proteomics as well as a practical comprehension text with an extended scope on the state-of-the-art bioinformatic details pertinent to next-generation sequencing, translational/clinical bioinformatics and vaccine-design related viral informatics.It includes four major sections: (i) An introduction to bioinformatics with a focus on the fundamentals of information-theory applied to biology/microbiology, with notes on bioinformatic resources, data bases, information networking and tools; (ii) a collection of annotations on the analytics of biomolecular sequences, with pertinent details presented on biomolecular informatics, pairwise and multiple sequences, viral sequence informatics, next-generation sequencing and translational/clinical bioinformatics; (iii) a novel section on cytogenetic and organelle bioinformatics explaining the entropy-theoretics of cellular structures and the underlying informatics of synteny correlations; and (iv) a comprehensive presentation on phylogeny and species informatics.The book is aimed at students, faculty and researchers in biology, health/medical sciences, veterinary/agricultural sciences, bioengineering, biotechnology and genetic engineering. It will be a useful companion for managerial personnel in the biotechnology and bioengineering industries as well as in health/medical science.

Research in Progress

Author :
Publisher :
ISBN 13 :
Total Pages : 274 pages
Book Rating : 4.:/5 (31 download)

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Book Synopsis Research in Progress by :

Download or read book Research in Progress written by and published by . This book was released on 1991 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Neural Network Design

Author : Martin T. Hagan
Publisher :
ISBN 13 : 9789812403766
Total Pages : pages
Book Rating : 4.4/5 (37 download)

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Book Synopsis Neural Network Design by : Martin T. Hagan

Download or read book Neural Network Design written by Martin T. Hagan and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author :
Publisher : IOS Press
ISBN 13 :
Total Pages : 7289 pages
Book Rating : 4./5 ( download)

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Book Synopsis by :

Download or read book written by and published by IOS Press. This book was released on with total page 7289 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Implementation Techniques

Author : Cornelius T. Leondes
Publisher : Academic Press
ISBN 13 : 0080551823
Total Pages : 421 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Implementation Techniques by : Cornelius T. Leondes

Download or read book Implementation Techniques written by Cornelius T. Leondes and published by Academic Press. This book was released on 1998-02-09 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume covers practical and effective implementation techniques, including recurrent methods, Boltzmann machines, constructive learning with methods for the reduction of complexity in neural network systems, modular systems, associative memory, neural network design based on the concept of the Inductive Logic Unit, and a comprehensive treatment of implementations in the area of data classification. Numerous examples enhance the text. Practitioners, researchers,and students in engineering and computer science will find Implementation Techniques a comprehensive and powerful reference. - Recurrent methods - Boltzmann machines - Constructive learning with methods for the reduction of complexity in neural network systems - Modular systems - Associative memory - Neural network design based on the concept of the Inductive Logic Unit - Data classification - Integrated neuron model systems that function as programmable rational approximators

Index Medicus

Author :
Publisher :
ISBN 13 :
Total Pages : 1938 pages
Book Rating : 4.:/5 (319 download)

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Book Synopsis Index Medicus by :

Download or read book Index Medicus written by and published by . This book was released on 2004 with total page 1938 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vols. for 1963- include as pt. 2 of the Jan. issue: Medical subject headings.

Decision Diagram Techniques for Micro- and Nanoelectronic Design Handbook

Author : Svetlana N. Yanushkevich
Publisher : CRC Press
ISBN 13 : 1351836382
Total Pages : 960 pages
Book Rating : 4.3/5 (518 download)

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Book Synopsis Decision Diagram Techniques for Micro- and Nanoelectronic Design Handbook by : Svetlana N. Yanushkevich

Download or read book Decision Diagram Techniques for Micro- and Nanoelectronic Design Handbook written by Svetlana N. Yanushkevich and published by CRC Press. This book was released on 2018-10-03 with total page 960 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision diagram (DD) techniques are very popular in the electronic design automation (EDA) of integrated circuits, and for good reason. They can accurately simulate logic design, can show where to make reductions in complexity, and can be easily modified to model different scenarios. Presenting DD techniques from an applied perspective, Decision Diagram Techniques for Micro- and Nanoelectronic Design Handbook provides a comprehensive, up-to-date collection of DD techniques. Experts with more than forty years of combined experience in both industrial and academic settings demonstrate how to apply the techniques to full advantage with more than 400 examples and illustrations. Beginning with the fundamental theory, data structures, and logic underlying DD techniques, they explore a breadth of topics from arithmetic and word-level representations to spectral techniques and event-driven analysis. The book also includes abundant references to more detailed information and additional applications. Decision Diagram Techniques for Micro- and Nanoelectronic Design Handbook collects the theory, methods, and practical knowledge necessary to design more advanced circuits and places it at your fingertips in a single, concise reference.

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

System and Circuit Design for Biologically-Inspired Intelligent Learning

Author : Temel, Turgay
Publisher : IGI Global
ISBN 13 : 1609600207
Total Pages : 411 pages
Book Rating : 4.6/5 (96 download)

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Book Synopsis System and Circuit Design for Biologically-Inspired Intelligent Learning by : Temel, Turgay

Download or read book System and Circuit Design for Biologically-Inspired Intelligent Learning written by Temel, Turgay and published by IGI Global. This book was released on 2010-10-31 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The objective of the book is to introduce and bring together well-known circuit design aspects, as well as to cover up-to-date outcomes of theoretical studies in decision-making, biologically-inspired, and artificial intelligent learning techniques"--Provided by publisher.