1993 IEEE International Conference on Neural Networks, San Francisco, California, March 28-April 1, 1993 PDF Download
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Author:
Publisher:
ISBN:
Category : Neural circuitry
Languages : en
Pages : 880
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Book Description
Author:
Publisher:
ISBN:
Category : Neural circuitry
Languages : en
Pages : 880
Get Book Here
Book Description
Author: Cornelius T. Leondes
Publisher: Elsevier
ISBN: 0080498981
Category : Computers
Languages : en
Pages : 485
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Book Description
This volume is the first diverse and comprehensive treatment of algorithms and architectures for the realization of neural network systems. It presents techniques and diverse methods in numerous areas of this broad subject. The book covers major neural network systems structures for achieving effective systems, and illustrates them with examples. This volume includes Radial Basis Function networks, the Expand-and-Truncate Learning algorithm for the synthesis of Three-Layer Threshold Networks, weight initialization, fast and efficient variants of Hamming and Hopfield neural networks, discrete time synchronous multilevel neural systems with reduced VLSI demands, probabilistic design techniques, time-based techniques, techniques for reducing physical realization requirements, and applications to finite constraint problems. A unique and comprehensive reference for a broad array of algorithms and architectures, this book will be of use to practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as in computer science and engineering. - Radial Basis Function networks - The Expand-and-Truncate Learning algorithm for the synthesis of Three-Layer Threshold Networks - Weight initialization - Fast and efficient variants of Hamming and Hopfield neural networks - Discrete time synchronous multilevel neural systems with reduced VLSI demands - Probabilistic design techniques - Time-based techniques - Techniques for reducing physical realization requirements - Applications to finite constraint problems - Practical realization methods for Hebbian type associative memory systems - Parallel self-organizing hierarchical neural network systems - Dynamics of networks of biological neurons for utilization in computational neuroscience
Author: Jian Ping Li
Publisher: World Scientific
ISBN: 9812383433
Category : Computers
Languages : en
Pages : 534
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Book Description
This book captures the essence of the current state of research in active media technology and identifies the new changes and opportunities ? both current and future ? in the field. Distinguished researchers such as Prof Ning Zhong from the Maebashi Institute of Technology, Prof John Yen from the Pennsylvania State University, and Prof Sanker K Pal from the Indian Statistical Institute present their research papers.
Author: Ron Sun
Publisher: Psychology Press
ISBN: 1134802137
Category : Psychology
Languages : en
Pages : 394
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Book Description
A variety of ideas, approaches, and techniques exist -- in terms of both architecture and learning -- and this abundance seems to lead to many exciting possibilities in terms of theoretical advances and application potentials. Despite the apparent diversity, there is clearly an underlying unifying theme: architectures that bring together symbolic and connectionist models to achieve a synthesis and synergy of the two different paradigms, and the learning and knowledge acquisition methods for developing such architectures. More effort needs to be extended to exploit the possibilities and opportunities in this area. This book is the outgrowth of The IJCAI Workshop on Connectionist-Symbolic Integration: From Unified to Hybrid Approaches, held in conjunction with the fourteenth International Joint Conference on Artificial Intelligence (IJCAI '95). Featuring various presentations and discussions, this two-day workshop brought to light many new ideas, controversies, and syntheses which lead to the present volume. This book is concerned with the development, analysis, and application of hybrid connectionist-symbolic models in artificial intelligence and cognitive science. Drawing contributions from a large international group of experts, it describes and compares a variety of models in this area. The types of models discussed cover a wide range of the evolving spectrum of hybrid models, thus serving as a well-balanced progress report on the state of the art. As such, this volume provides an information clearinghouse for various proposed approaches and models that share the common belief that connectionist and symbolic models can be usefully combined and integrated, and such integration may lead to significant advances in understanding intelligence.
Author: Mohamad H. Hassoun
Publisher: MIT Press
ISBN: 9780262082396
Category : Computers
Languages : en
Pages : 546
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Book Description
A systematic account of artificial neural network paradigms that identifies fundamental concepts and major methodologies. Important results are integrated into the text in order to explain a wide range of existing empirical observations and commonly used heuristics.
Author: Lipo Wang
Publisher: Springer Science & Business Media
ISBN: 3540288031
Category : Computers
Languages : en
Pages : 280
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Book Description
Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others. Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.
Author: Sankar Kumar Pal
Publisher: World Scientific
ISBN: 9814489476
Category : Technology & Engineering
Languages : en
Pages : 421
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Book Description
Neural networks (NNs) and systolic arrays (SAs) have many similar features. This volume describes, in a unified way, the basic concepts, theories and characteristic features of integrating or formulating different facets of NNs and SAs, as well as presents recent developments and significant applications. The articles, written by experts from all over the world, demonstrate the various ways this integration can be made to efficiently design methodologies, algorithms and architectures, and also implementations, for NN applications. The book will be useful to graduate students and researchers in many related areas, not only as a reference book but also as a textbook for some parts of the curriculum. It will also benefit researchers and practitioners in industry and R&D laboratories who are working in the fields of system design, VLSI, parallel processing, neural networks, and vision.
Author: Richard K. Belew
Publisher: Cambridge University Press
ISBN: 9780521630283
Category : Computers
Languages : en
Pages : 388
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Book Description
Explains how to build useful tools for searching collections of text and other media.
Author: Paul Werbos
Publisher: Routledge
ISBN: 1317713427
Category : Psychology
Languages : en
Pages : 860
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Book Description
Centered around 20 major topic areas of both theoretical and practical importance, the World Congress on Neural Networks provides its registrants -- from a diverse background encompassing industry, academia, and government -- with the latest research and applications in the neural network field.
Author: Ron Sun
Publisher: Springer
ISBN: 354044565X
Category : Computers
Languages : en
Pages : 400
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Book Description
Sequential behavior is essential to intelligence in general and a fundamental part of human activities, ranging from reasoning to language, and from everyday skills to complex problem solving. Sequence learning is an important component of learning in many tasks and application fields: planning, reasoning, robotics natural language processing, speech recognition, adaptive control, time series prediction, financial engineering, DNA sequencing, and so on. This book presents coherently integrated chapters by leading authorities and assesses the state of the art in sequence learning by introducing essential models and algorithms and by examining a variety of applications. The book offers topical sections on sequence clustering and learning with Markov models, sequence prediction and recognition with neural networks, sequence discovery with symbolic methods, sequential decision making, biologically inspired sequence learning models.
