Neurodynamics Proceedings Of The 9th Summer Workshop

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Neurodynamics - Proceedings Of The 9th Summer Workshop

Author : Heinz-dietrich Doebner
Publisher : World Scientific
ISBN 13 : 9814555541
Total Pages : 246 pages
Book Rating : 4.8/5 (145 download)

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Book Synopsis Neurodynamics - Proceedings Of The 9th Summer Workshop by : Heinz-dietrich Doebner

Download or read book Neurodynamics - Proceedings Of The 9th Summer Workshop written by Heinz-dietrich Doebner and published by World Scientific. This book was released on 1991-10-31 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents applications of mathematical techniques for modelling and performance analysis of neural networks. The collection of articles is motivated by the observation that the theory of neural network dynamics, i.e. Neurodynamics, still has to be given a thorough mathematical foundation. Therefore, the volume comprises research work on different mathematical approaches to neural networks; analytical and numerical techniques of dynamical systems theory, geometrical techniques, and methods of statistical physics. Articles analyse dynamics of neural netwroks in general or concentrate on specific network models of biological or neurocomputing origin. A few of the articles serve as a good introduction to these subjects.

Neurodynamics

Author : Heinz Dietrich Doebner
Publisher :
ISBN 13 : 9789814538244
Total Pages : 233 pages
Book Rating : 4.5/5 (382 download)

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Book Synopsis Neurodynamics by : Heinz Dietrich Doebner

Download or read book Neurodynamics written by Heinz Dietrich Doebner and published by . This book was released on 1991 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Mathematics as a Laboratory Tool

Author : John Milton
Publisher : Springer Nature
ISBN 13 : 3030695794
Total Pages : 650 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Mathematics as a Laboratory Tool by : John Milton

Download or read book Mathematics as a Laboratory Tool written by John Milton and published by Springer Nature. This book was released on 2021-08-11 with total page 650 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of Mathematics as a Laboratory Tool reflects the growing impact that computational science is having on the career choices made by undergraduate science and engineering students. The focus is on dynamics and the effects of time delays and stochastic perturbations (“noise”) on the regulation provided by feedback control systems. The concepts are illustrated with applications to gene regulatory networks, motor control, neuroscience and population biology. The presentation in the first edition has been extended to include discussions of neuronal excitability and bursting, multistability, microchaos, Bayesian inference, second-order delay differential equations, and the semi-discretization method for the numerical integration of delay differential equations. Every effort has been made to ensure that the material is accessible to those with a background in calculus. The text provides advanced mathematical concepts such as the Laplace and Fourier integral transforms in the form of Tools. Bayesian inference is introduced using a number of detective-type scenarios including the Monty Hall problem.

Mathematical Perspectives on Neural Networks

Author : Paul Smolensky
Publisher : Psychology Press
ISBN 13 : 1134772947
Total Pages : 865 pages
Book Rating : 4.1/5 (347 download)

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Book Synopsis Mathematical Perspectives on Neural Networks by : Paul Smolensky

Download or read book Mathematical Perspectives on Neural Networks written by Paul Smolensky and published by Psychology Press. This book was released on 2013-05-13 with total page 865 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent years have seen an explosion of new mathematical results on learning and processing in neural networks. This body of results rests on a breadth of mathematical background which even few specialists possess. In a format intermediate between a textbook and a collection of research articles, this book has been assembled to present a sample of these results, and to fill in the necessary background, in such areas as computability theory, computational complexity theory, the theory of analog computation, stochastic processes, dynamical systems, control theory, time-series analysis, Bayesian analysis, regularization theory, information theory, computational learning theory, and mathematical statistics. Mathematical models of neural networks display an amazing richness and diversity. Neural networks can be formally modeled as computational systems, as physical or dynamical systems, and as statistical analyzers. Within each of these three broad perspectives, there are a number of particular approaches. For each of 16 particular mathematical perspectives on neural networks, the contributing authors provide introductions to the background mathematics, and address questions such as: * Exactly what mathematical systems are used to model neural networks from the given perspective? * What formal questions about neural networks can then be addressed? * What are typical results that can be obtained? and * What are the outstanding open problems? A distinctive feature of this volume is that for each perspective presented in one of the contributed chapters, the first editor has provided a moderately detailed summary of the formal results and the requisite mathematical concepts. These summaries are presented in four chapters that tie together the 16 contributed chapters: three develop a coherent view of the three general perspectives -- computational, dynamical, and statistical; the other assembles these three perspectives into a unified overview of the neural networks field.

Singapore National Bibliography

Author :
Publisher :
ISBN 13 :
Total Pages : 644 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Singapore National Bibliography by :

Download or read book Singapore National Bibliography written by and published by . This book was released on 1993 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Index of Conference Proceedings

Author :
Publisher :
ISBN 13 :
Total Pages : 856 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Index of Conference Proceedings by :

Download or read book Index of Conference Proceedings written by and published by . This book was released on 1996 with total page 856 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Directory of Published Proceedings

Author :
Publisher :
ISBN 13 :
Total Pages : 836 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Directory of Published Proceedings by :

Download or read book Directory of Published Proceedings written by and published by . This book was released on 1996 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Reinforcement Learning, second edition

Author : Richard S. Sutton
Publisher : MIT Press
ISBN 13 : 0262352702
Total Pages : 549 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Reinforcement Learning, second edition by : Richard S. Sutton

Download or read book Reinforcement Learning, second edition written by Richard S. Sutton and published by MIT Press. This book was released on 2018-11-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

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:

Neural Networks for Optimization and Signal Processing

Author : Andrzej Cichocki
Publisher : John Wiley & Sons
ISBN 13 :
Total Pages : 578 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Neural Networks for Optimization and Signal Processing by : Andrzej Cichocki

Download or read book Neural Networks for Optimization and Signal Processing written by Andrzej Cichocki and published by John Wiley & Sons. This book was released on 1993-06-07 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: A topical introduction on the ability of artificial neural networks to not only solve on-line a wide range of optimization problems but also to create new techniques and architectures. Provides in-depth coverage of mathematical modeling along with illustrative computer simulation results.

Neural Networks

Author : Simon Haykin
Publisher :
ISBN 13 : 9788178083001
Total Pages : 842 pages
Book Rating : 4.0/5 (83 download)

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Book Synopsis Neural Networks by : Simon Haykin

Download or read book Neural Networks written by Simon Haykin and published by . This book was released on 1999 with total page 842 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Readings in Machine Learning

Author : Jude W. Shavlik
Publisher : Morgan Kaufmann
ISBN 13 : 9781558601437
Total Pages : 868 pages
Book Rating : 4.6/5 (14 download)

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Book Synopsis Readings in Machine Learning by : Jude W. Shavlik

Download or read book Readings in Machine Learning written by Jude W. Shavlik and published by Morgan Kaufmann. This book was released on 1990 with total page 868 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to learn is a fundamental characteristic of intelligent behavior. Consequently, machine learning has been a focus of artificial intelligence since the beginnings of AI in the 1950s. The 1980s saw tremendous growth in the field, and this growth promises to continue with valuable contributions to science, engineering, and business. Readings in Machine Learning collects the best of the published machine learning literature, including papers that address a wide range of learning tasks, and that introduce a variety of techniques for giving machines the ability to learn. The editors, in cooperation with a group of expert referees, have chosen important papers that empirically study, theoretically analyze, or psychologically justify machine learning algorithms. The papers are grouped into a dozen categories, each of which is introduced by the editors.

Introduction to Machine Learning

Author : Ethem Alpaydin
Publisher : MIT Press
ISBN 13 : 0262028182
Total Pages : 639 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Introduction to Machine Learning by : Ethem Alpaydin

Download or read book Introduction to Machine Learning written by Ethem Alpaydin and published by MIT Press. This book was released on 2014-08-22 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.

Supervised Sequence Labelling with Recurrent Neural Networks

Author : Alex Graves
Publisher : Springer
ISBN 13 : 3642247970
Total Pages : 148 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Supervised Sequence Labelling with Recurrent Neural Networks by : Alex Graves

Download or read book Supervised Sequence Labelling with Recurrent Neural Networks written by Alex Graves and published by Springer. This book was released on 2012-02-06 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supervised sequence labelling is a vital area of machine learning, encompassing tasks such as speech, handwriting and gesture recognition, protein secondary structure prediction and part-of-speech tagging. Recurrent neural networks are powerful sequence learning tools—robust to input noise and distortion, able to exploit long-range contextual information—that would seem ideally suited to such problems. However their role in large-scale sequence labelling systems has so far been auxiliary. The goal of this book is a complete framework for classifying and transcribing sequential data with recurrent neural networks only. Three main innovations are introduced in order to realise this goal. Firstly, the connectionist temporal classification output layer allows the framework to be trained with unsegmented target sequences, such as phoneme-level speech transcriptions; this is in contrast to previous connectionist approaches, which were dependent on error-prone prior segmentation. Secondly, multidimensional recurrent neural networks extend the framework in a natural way to data with more than one spatio-temporal dimension, such as images and videos. Thirdly, the use of hierarchical subsampling makes it feasible to apply the framework to very large or high resolution sequences, such as raw audio or video. Experimental validation is provided by state-of-the-art results in speech and handwriting recognition.

The Elements of Skill

Author : Theodore Dimon, Jr
Publisher : North Atlantic Books
ISBN 13 : 1583947035
Total Pages : 249 pages
Book Rating : 4.5/5 (839 download)

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Book Synopsis The Elements of Skill by : Theodore Dimon, Jr

Download or read book The Elements of Skill written by Theodore Dimon, Jr and published by North Atlantic Books. This book was released on 2013-01-08 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why do so many beginners, both children and adults, fail to master chosen skills? The Elements of Skill was inspired by—and addresses—that question with a program based on proven techniques. The book, written by a renowned practitioner of the Alexander Technique, outlines an educational system that makes the process of learning a performance or athletic skill more conscious, and therefore more successful. Its principles include breaking down a skill into manageable parts, setting realistic goals, observing mind/body processes, overcoming blocks, controlling habits, and achieving heightened awareness and self-mastery. Included are inspiring examples of people who have benefited from the method.

The Quest for Artificial Intelligence

Author : Nils J. Nilsson
Publisher : Cambridge University Press
ISBN 13 : 1139642820
Total Pages : 644 pages
Book Rating : 4.1/5 (396 download)

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Book Synopsis The Quest for Artificial Intelligence by : Nils J. Nilsson

Download or read book The Quest for Artificial Intelligence written by Nils J. Nilsson and published by Cambridge University Press. This book was released on 2009-10-30 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today's AI engineers. AI is becoming more and more a part of everyone's life. The technology is already embedded in face-recognizing cameras, speech-recognition software, Internet search engines, and health-care robots, among other applications. The book's many diagrams and easy-to-understand descriptions of AI programs will help the casual reader gain an understanding of how these and other AI systems actually work. Its thorough (but unobtrusive) end-of-chapter notes containing citations to important source materials will be of great use to AI scholars and researchers. This book promises to be the definitive history of a field that has captivated the imaginations of scientists, philosophers, and writers for centuries.

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.