Connectionist Neuron And Network Models For Unsupervised Competitive Learning

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Proceedings of the 1993 Connectionist Models Summer School

Author : Michael C. Mozer
Publisher : Psychology Press
ISBN 13 : 1317780531
Total Pages : 424 pages
Book Rating : 4.3/5 (177 download)

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Book Synopsis Proceedings of the 1993 Connectionist Models Summer School by : Michael C. Mozer

Download or read book Proceedings of the 1993 Connectionist Models Summer School written by Michael C. Mozer and published by Psychology Press. This book was released on 2014-03-05 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: The result of the 1993 Connectionist Models Summer School, the papers in this volume exemplify the tremendous breadth and depth of research underway in the field of neural networks. Although the slant of the summer school has always leaned toward cognitive science and artificial intelligence, the diverse scientific backgrounds and research interests of accepted students and invited faculty reflect the broad spectrum of areas contributing to neural networks, including artificial intelligence, cognitive science, computer science, engineering, mathematics, neuroscience, and physics. Providing an accurate picture of the state of the art in this fast-moving field, the proceedings of this intense two-week program of lectures, workshops, and informal discussions contains timely and high-quality work by the best and the brightest in the neural networks field.

Connectionist Models

Author : David S. Touretzky
Publisher : Morgan Kaufmann
ISBN 13 : 1483214486
Total Pages : 417 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis Connectionist Models by : David S. Touretzky

Download or read book Connectionist Models written by David S. Touretzky and published by Morgan Kaufmann. This book was released on 2014-05-12 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Connectionist Models contains the proceedings of the 1990 Connectionist Models Summer School held at the University of California at San Diego. The summer school provided a forum for students and faculty to assess the state of the art with regards to connectionist modeling. Topics covered range from theoretical analysis of networks to empirical investigations of learning algorithms; speech and image processing; cognitive psychology; computational neuroscience; and VLSI design. Comprised of 40 chapters, this book begins with an introduction to mean field, Boltzmann, and Hopfield networks, focusing on deterministic Boltzmann learning in networks with asymmetric connectivity; contrastive Hebbian learning in the continuous Hopfield model; and energy minimization and the satisfiability of propositional logic. Mean field networks that learn to discriminate temporally distorted strings are described. The next sections are devoted to reinforcement learning and genetic learning, along with temporal processing and modularity. Cognitive modeling and symbol processing as well as VLSI implementation are also discussed. This monograph will be of interest to both students and academicians concerned with connectionist modeling.

Learning in Natural and Connectionist Systems

Author : R.H. Phaf
Publisher : Springer Science & Business Media
ISBN 13 : 9401108404
Total Pages : 307 pages
Book Rating : 4.4/5 (11 download)

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Book Synopsis Learning in Natural and Connectionist Systems by : R.H. Phaf

Download or read book Learning in Natural and Connectionist Systems written by R.H. Phaf and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern research in neural networks has led to powerful artificial learning systems, while recent work in the psychology of human memory has revealed much about how natural systems really learn, including the role of unconscious, implicit, memory processes. Regrettably, the two approaches typically ignore each other. This book, combining the approaches, should contribute to their mutual benefit. New empirical work is presented showing dissociations between implicit and explicit memory performance. Recently proposed explanations for such data lead to a new connectionist learning procedure: CALM (Categorizing and Learning Module), which can learn with or without supervision, and shows practical advantages over many existing procedures. Specific experiments are simulated by a network model (ELAN) composed of CALM modules. A working memory extension to the model is also discussed that could give it symbol manipulation abilities. The book will be of interest to memory psychologists and connectionists, as well as to cognitive scientists who in the past have tended to restrict themselves to symbolic models.

An Introduction to Neural Networks

Author : Kevin Gurney
Publisher : CRC Press
ISBN 13 : 1482286998
Total Pages : 148 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis An Introduction to Neural Networks by : Kevin Gurney

Download or read book An Introduction to Neural Networks written by Kevin Gurney and published by CRC Press. This book was released on 2018-10-08 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation. The book also includes several real-world examples to provide a concrete focus. This should enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to one of the most important topics in cognitive and computer science, this volume should interest a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering.

Elements of Artificial Neural Networks

Author : Kishan Mehrotra
Publisher : MIT Press
ISBN 13 : 9780262133289
Total Pages : 376 pages
Book Rating : 4.1/5 (332 download)

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Book Synopsis Elements of Artificial Neural Networks by : Kishan Mehrotra

Download or read book Elements of Artificial Neural Networks written by Kishan Mehrotra and published by MIT Press. This book was released on 1997 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elements of Artificial Neural Networks provides a clearly organized general introduction, focusing on a broad range of algorithms, for students and others who want to use neural networks rather than simply study them. The authors, who have been developing and team teaching the material in a one-semester course over the past six years, describe most of the basic neural network models (with several detailed solved examples) and discuss the rationale and advantages of the models, as well as their limitations. The approach is practical and open-minded and requires very little mathematical or technical background. Written from a computer science and statistics point of view, the text stresses links to contiguous fields and can easily serve as a first course for students in economics and management. The opening chapter sets the stage, presenting the basic concepts in a clear and objective way and tackling important -- yet rarely addressed -- questions related to the use of neural networks in practical situations. Subsequent chapters on supervised learning (single layer and multilayer networks), unsupervised learning, and associative models are structured around classes of problems to which networks can be applied. Applications are discussed along with the algorithms. A separate chapter takes up optimization methods. The most frequently used algorithms, such as backpropagation, are introduced early on, right after perceptrons, so that these can form the basis for initiating course projects. Algorithms published as late as 1995 are also included. All of the algorithms are presented using block-structured pseudo-code, and exercises are provided throughout. Software implementing many commonly used neural network algorithms is available at the book's website. Transparency masters, including abbreviated text and figures for the entire book, are available for instructors using the text.

Deep Learning

Author : Li Deng
Publisher :
ISBN 13 : 9781601988140
Total Pages : 212 pages
Book Rating : 4.9/5 (881 download)

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Book Synopsis Deep Learning by : Li Deng

Download or read book Deep Learning written by Li Deng and published by . This book was released on 2014 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks

Connectionist Models of Behaviour and Cognition II - Proceedings of the 11th Neural Computation and Psychology Workshop

Author : Julien Mayor
Publisher : World Scientific
ISBN 13 : 9812834230
Total Pages : 427 pages
Book Rating : 4.8/5 (128 download)

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Book Synopsis Connectionist Models of Behaviour and Cognition II - Proceedings of the 11th Neural Computation and Psychology Workshop by : Julien Mayor

Download or read book Connectionist Models of Behaviour and Cognition II - Proceedings of the 11th Neural Computation and Psychology Workshop written by Julien Mayor and published by World Scientific. This book was released on 2009-04-21 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: The neural computational approach to cognitive and psychological processes is relatively new. However, Neural Computation and Psychology Workshops (NCPW), first held 16 years ago, lie at the heart of this fast-moving discipline, thanks to its interdisciplinary nature OCo bringing together researchers from different disciplines such as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their work on models of cognitive processes."

NeuralSource

Author : Philip D. Wasserman
Publisher : Van Nostrand Reinhold Company
ISBN 13 :
Total Pages : 1032 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis NeuralSource by : Philip D. Wasserman

Download or read book NeuralSource written by Philip D. Wasserman and published by Van Nostrand Reinhold Company. This book was released on 1990 with total page 1032 pages. Available in PDF, EPUB and Kindle. Book excerpt: Derived from the database Neural Base (still available at $495.00), this bibliography, covering more than 4,000 references, is an important collection of research information. Extensive annotations have been added to approximately 75% of the entries in the print version. Periodicals, private reports, and books are included. Indexed by author, keyword, and publication. Neurons were slacking off when A mathematical theory... was indexed under "A". Annotation copyrighted by Book News, Inc., Portland, OR

Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society

Author : Cognitive Science Society (US) Conference
Publisher : Psychology Press
ISBN 13 : 1317781600
Total Pages : 1212 pages
Book Rating : 4.3/5 (177 download)

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Book Synopsis Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society by : Cognitive Science Society (US) Conference

Download or read book Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society written by Cognitive Science Society (US) Conference and published by Psychology Press. This book was released on 2014-05-12 with total page 1212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume features the complete text of all regular papers, posters, and summaries of symposia presented at the 14th annual meeting of the Cognitive Science Society.

Artificial Neural Network Modelling

Author : Subana Shanmuganathan
Publisher : Springer
ISBN 13 : 3319284959
Total Pages : 468 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Artificial Neural Network Modelling by : Subana Shanmuganathan

Download or read book Artificial Neural Network Modelling written by Subana Shanmuganathan and published by Springer. This book was released on 2016-02-03 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling.

Neural Networks and Statistical Learning

Author : Ke-Lin Du
Publisher : Springer Science & Business Media
ISBN 13 : 1447155718
Total Pages : 834 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Neural Networks and Statistical Learning by : Ke-Lin Du

Download or read book Neural Networks and Statistical Learning written by Ke-Lin Du and published by Springer Science & Business Media. This book was released on 2013-12-09 with total page 834 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardware implementations, and some machine learning topics. Applications to biometric/bioinformatics and data mining are also included. Focusing on the prominent accomplishments and their practical aspects, academic and technical staff, graduate students and researchers will find that this provides a solid foundation and encompassing reference for the fields of neural networks, pattern recognition, signal processing, machine learning, computational intelligence, and data mining.

Connectionist Models of Memory and Language (PLE: Memory)

Author : Joseph P. Levy
Publisher : Psychology Press
ISBN 13 : 1317744675
Total Pages : 393 pages
Book Rating : 4.3/5 (177 download)

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Book Synopsis Connectionist Models of Memory and Language (PLE: Memory) by : Joseph P. Levy

Download or read book Connectionist Models of Memory and Language (PLE: Memory) written by Joseph P. Levy and published by Psychology Press. This book was released on 2014-05-09 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Connectionist modelling and neural network applications had become a major sub-field of cognitive science by the mid-1990s. In this ground-breaking book, originally published in 1995, leading connectionists shed light on current approaches to memory and language modelling at the time. The book is divided into four sections: Memory; Reading; Computation and statistics; Speech and audition. Each section is introduced and set in context by the editors, allowing a wide range of language and memory issues to be addressed in one volume. This authoritative advanced level book will still be of interest for all engaged in connectionist research and the related areas of cognitive science concerned with language and memory.

Fluctuation Phenomena: Disorder And Nonlinearity - Proceedings Of The International Workshop

Author : Luis Vazquez
Publisher : World Scientific
ISBN 13 : 9814603775
Total Pages : 444 pages
Book Rating : 4.8/5 (146 download)

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Book Synopsis Fluctuation Phenomena: Disorder And Nonlinearity - Proceedings Of The International Workshop by : Luis Vazquez

Download or read book Fluctuation Phenomena: Disorder And Nonlinearity - Proceedings Of The International Workshop written by Luis Vazquez and published by World Scientific. This book was released on 1995-05-04 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the issues of nonlinearity and disorder. It covers mathematical and numerical techniques as well as applications of nonlinearity and disorder. The analysis of continuous and discrete systems is also shown.

The Cambridge Handbook of Computational Psychology

Author : Ron Sun
Publisher : Cambridge University Press
ISBN 13 : 0521674107
Total Pages : 767 pages
Book Rating : 4.5/5 (216 download)

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Book Synopsis The Cambridge Handbook of Computational Psychology by : Ron Sun

Download or read book The Cambridge Handbook of Computational Psychology written by Ron Sun and published by Cambridge University Press. This book was released on 2008-04-28 with total page 767 pages. Available in PDF, EPUB and Kindle. Book excerpt: A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.

Neural Network Fundamentals with Graphs, Algorithms, and Applications

Author : Nirmal K. Bose
Publisher : McGraw-Hill Companies
ISBN 13 :
Total Pages : 520 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Neural Network Fundamentals with Graphs, Algorithms, and Applications by : Nirmal K. Bose

Download or read book Neural Network Fundamentals with Graphs, Algorithms, and Applications written by Nirmal K. Bose and published by McGraw-Hill Companies. This book was released on 1996 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Neural Networks

Author : Raul Rojas
Publisher : Springer Science & Business Media
ISBN 13 : 3642610684
Total Pages : 511 pages
Book Rating : 4.6/5 (426 download)

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Book Synopsis Neural Networks by : Raul Rojas

Download or read book Neural Networks written by Raul Rojas and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. Always with a view to biology and starting with the simplest nets, it is shown how the properties of models change when more general computing elements and net topologies are introduced. Each chapter contains examples, numerous illustrations, and a bibliography. The book is aimed at readers who seek an overview of the field or who wish to deepen their knowledge. It is suitable as a basis for university courses in neurocomputing.

Computational Intelligence in Games

Author : Norio Baba
Publisher : Physica
ISBN 13 : 379081833X
Total Pages : 172 pages
Book Rating : 4.7/5 (98 download)

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Book Synopsis Computational Intelligence in Games by : Norio Baba

Download or read book Computational Intelligence in Games written by Norio Baba and published by Physica. This book was released on 2012-08-11 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: The most powerful computers in the world are not only used for scientific research, defence, and business, but also in game playing. Computer games are a multi-billion dollar industry. Recent advances in computational intelligence paradigms have generated tremendous interest among researchers in the theory and implementation of games. Game theory is a branch of operational research dealing with decision theory in a competitive situation. Game theory involves the mathematical calculations and heuristics to optimize the efficient lines of play. This book presents a sample of the most recent research on the application of computational intelligence techniques in games. This book contains 7 chapters. The first chapter, by Chen, Fanelli, Castellano, and Jain, is an introduction to computational intelligence paradigms. It presents the basics of the main constituents of compu tational intelligence paradigms including knowledge representation, probability-based approaches, fuzzy logic, neural networks, genetic algorithms, and rough sets. In the second chapter, Chellapilla and Fogel present the evolution of a neural network to play checkers without human expertise. This chapter focuses on the use of a population of neural networks, where each network serves as an evaluation function to describe the quality of the current board position. After only a little more than 800 generations, the evolutionary process has generated a neural network that can play checkers at the expert level as designated by the u.s. Chess Federation rating system. The program developed by the authors has also competed well against commercially available software.