Author: E. Covey
Publisher: Springer Science & Business Media
ISBN: 1461519195
Category : Medical
Languages : en
Pages : 264
Book Description
Neural Representation of Temporal Patterns
Author: E. Covey
Publisher: Springer Science & Business Media
ISBN: 1461519195
Category : Medical
Languages : en
Pages : 264
Book Description
Publisher: Springer Science & Business Media
ISBN: 1461519195
Category : Medical
Languages : en
Pages : 264
Book Description
Pattern Recognition and Neural Networks
Author: Brian D. Ripley
Publisher: Cambridge University Press
ISBN: 9780521717700
Category : Computers
Languages : en
Pages : 420
Book Description
This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.
Publisher: Cambridge University Press
ISBN: 9780521717700
Category : Computers
Languages : en
Pages : 420
Book Description
This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.
Neural Networks and Pattern Recognition
Author: Omid Omidvar
Publisher: Academic Press
ISBN: 9780125264204
Category : Business & Economics
Languages : en
Pages : 380
Book Description
Pulse-coupled neural networks; A neural network model for optical flow computation; Temporal pattern matching using an artificial neural network; Patterns of dynamic activity and timing in neural network processing; A macroscopic model of oscillation in ensembles of inhibitory and excitatory neurons; Finite state machines and recurrent neural networks: automata and dynamical systems approaches; biased random-waldk learning; a neurobiological correlate to trial-and-error; Using SONNET 1 to segment continuous sequences of items; On the use of high-level petri nets in the modeling of biological neural networks; Locally recurrent networks: the gmma operator, properties, and extensions.
Publisher: Academic Press
ISBN: 9780125264204
Category : Business & Economics
Languages : en
Pages : 380
Book Description
Pulse-coupled neural networks; A neural network model for optical flow computation; Temporal pattern matching using an artificial neural network; Patterns of dynamic activity and timing in neural network processing; A macroscopic model of oscillation in ensembles of inhibitory and excitatory neurons; Finite state machines and recurrent neural networks: automata and dynamical systems approaches; biased random-waldk learning; a neurobiological correlate to trial-and-error; Using SONNET 1 to segment continuous sequences of items; On the use of high-level petri nets in the modeling of biological neural networks; Locally recurrent networks: the gmma operator, properties, and extensions.
Neural Networks for Control
Author: W. Thomas Miller
Publisher: MIT Press
ISBN: 9780262631617
Category : Computers
Languages : en
Pages : 548
Book Description
Neural Networks for Control brings together examples of all the most important paradigms for the application of neural networks to robotics and control. Primarily concerned with engineering problems and approaches to their solution through neurocomputing systems, the book is divided into three sections: general principles, motion control, and applications domains (with evaluations of the possible applications by experts in the applications areas.) Special emphasis is placed on designs based on optimization or reinforcement, which will become increasingly important as researchers address more complex engineering challenges or real biological-control problems.A Bradford Book. Neural Network Modeling and Connectionism series
Publisher: MIT Press
ISBN: 9780262631617
Category : Computers
Languages : en
Pages : 548
Book Description
Neural Networks for Control brings together examples of all the most important paradigms for the application of neural networks to robotics and control. Primarily concerned with engineering problems and approaches to their solution through neurocomputing systems, the book is divided into three sections: general principles, motion control, and applications domains (with evaluations of the possible applications by experts in the applications areas.) Special emphasis is placed on designs based on optimization or reinforcement, which will become increasingly important as researchers address more complex engineering challenges or real biological-control problems.A Bradford Book. Neural Network Modeling and Connectionism series
Advances in Artificial Life
Author: Wolfgang Banzhaf
Publisher: Springer
ISBN: 354039432X
Category : Computers
Languages : en
Pages : 922
Book Description
This book constitutes the refereed proceedings of the 7th European Conference on Artificial Life, ECAL 2003, held in Dortmund, Germany in September 2003. The 96 revised full papers presented were carefully reviewed and selected from more than 140 submissions. The papers are organized in topical sections on artificial chemistries, self-organization, and self-replication; artificial societies; cellular and neural systems; evolution and development; evolutionary and adaptive dynamics; languages and communication; methodologies and applications; and robotics and autonomous agents.
Publisher: Springer
ISBN: 354039432X
Category : Computers
Languages : en
Pages : 922
Book Description
This book constitutes the refereed proceedings of the 7th European Conference on Artificial Life, ECAL 2003, held in Dortmund, Germany in September 2003. The 96 revised full papers presented were carefully reviewed and selected from more than 140 submissions. The papers are organized in topical sections on artificial chemistries, self-organization, and self-replication; artificial societies; cellular and neural systems; evolution and development; evolutionary and adaptive dynamics; languages and communication; methodologies and applications; and robotics and autonomous agents.
Neural Networks for Pattern Recognition
Author: Albert Nigrin
Publisher: MIT Press
ISBN: 9780262140546
Category : Computers
Languages : en
Pages : 450
Book Description
In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Neural Networks for Pattern Recognition takes the pioneering work in artificial neural networks by Stephen Grossberg and his colleagues to a new level. In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Following a tutorial of existing neural networks for pattern classification, Nigrin expands on these networks to present fundamentally new architectures that perform realtime pattern classification of embedded and synonymous patterns and that will aid in tasks such as vision, speech recognition, sensor fusion, and constraint satisfaction. Nigrin presents the new architectures in two stages. First he presents a network called Sonnet 1 that already achieves important properties such as the ability to learn and segment continuously varied input patterns in real time, to process patterns in a context sensitive fashion, and to learn new patterns without degrading existing categories. He then removes simplifications inherent in Sonnet 1 and introduces radically new architectures. These architectures have the power to classify patterns that may have similar meanings but that have different external appearances (synonyms). They also have been designed to represent patterns in a distributed fashion, both in short-term and long-term memory.
Publisher: MIT Press
ISBN: 9780262140546
Category : Computers
Languages : en
Pages : 450
Book Description
In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Neural Networks for Pattern Recognition takes the pioneering work in artificial neural networks by Stephen Grossberg and his colleagues to a new level. In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Following a tutorial of existing neural networks for pattern classification, Nigrin expands on these networks to present fundamentally new architectures that perform realtime pattern classification of embedded and synonymous patterns and that will aid in tasks such as vision, speech recognition, sensor fusion, and constraint satisfaction. Nigrin presents the new architectures in two stages. First he presents a network called Sonnet 1 that already achieves important properties such as the ability to learn and segment continuously varied input patterns in real time, to process patterns in a context sensitive fashion, and to learn new patterns without degrading existing categories. He then removes simplifications inherent in Sonnet 1 and introduces radically new architectures. These architectures have the power to classify patterns that may have similar meanings but that have different external appearances (synonyms). They also have been designed to represent patterns in a distributed fashion, both in short-term and long-term memory.
Proceedings of the 1993 Connectionist Models Summer School
Author: Michael C. Mozer
Publisher: Psychology Press
ISBN: 1317780531
Category : Psychology
Languages : en
Pages : 424
Book Description
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.
Publisher: Psychology Press
ISBN: 1317780531
Category : Psychology
Languages : en
Pages : 424
Book Description
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.
Advances In Pattern Recognition Systems Using Neural Network Technologies
Author: Patrick S P Wang
Publisher: World Scientific
ISBN: 9814611816
Category :
Languages : en
Pages : 329
Book Description
Contents:A Connectionist Approach to Speech Recognition (Y Bengio)Signature Verification Using a “Siamese” Time Delay Neural Network (J Bromley et al.)Boosting Performance in Neural Networks (H Drucker et al.)An Integrated Architecture for Recognition of Totally Unconstrained Handwritten Numerals (A Gupta et al.)Time-Warping Network: A Neural Approach to Hidden Markov Model Based Speech Recognition (E Levin et al.)Computing Optical Flow with a Recurrent Neural Network (H Li & J Wang)Integrated Segmentation and Recognition through Exhaustive Scans or Learned Saccadic Jumps (G L Martin et al.)Experimental Comparison of the Effect of Order in Recurrent Neural Networks (C B Miller & C L Giles)Adaptive Classification by Neural Net Based Prototype Populations (K Peleg & U Ben-Hanan)A Neural System for the Recognition of Partially Occluded Objects in Cluttered Scenes: A Pilot Study (L Wiskott & C von der Malsburg)and other papers Readership: Computer scientists and engineers.
Publisher: World Scientific
ISBN: 9814611816
Category :
Languages : en
Pages : 329
Book Description
Contents:A Connectionist Approach to Speech Recognition (Y Bengio)Signature Verification Using a “Siamese” Time Delay Neural Network (J Bromley et al.)Boosting Performance in Neural Networks (H Drucker et al.)An Integrated Architecture for Recognition of Totally Unconstrained Handwritten Numerals (A Gupta et al.)Time-Warping Network: A Neural Approach to Hidden Markov Model Based Speech Recognition (E Levin et al.)Computing Optical Flow with a Recurrent Neural Network (H Li & J Wang)Integrated Segmentation and Recognition through Exhaustive Scans or Learned Saccadic Jumps (G L Martin et al.)Experimental Comparison of the Effect of Order in Recurrent Neural Networks (C B Miller & C L Giles)Adaptive Classification by Neural Net Based Prototype Populations (K Peleg & U Ben-Hanan)A Neural System for the Recognition of Partially Occluded Objects in Cluttered Scenes: A Pilot Study (L Wiskott & C von der Malsburg)and other papers Readership: Computer scientists and engineers.
The Handbook of Brain Theory and Neural Networks
Author: Michael A. Arbib
Publisher: MIT Press
ISBN: 0262011972
Category : Neural circuitry
Languages : en
Pages : 1328
Book Description
This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions : how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).
Publisher: MIT Press
ISBN: 0262011972
Category : Neural circuitry
Languages : en
Pages : 1328
Book Description
This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions : how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).
Proceedings of the Winter, 1990, International Joint Conference on Neural Networks
Author: Maureen Caudill
Publisher: Taylor & Francis
ISBN: 1317728335
Category : Psychology
Languages : en
Pages : 1588
Book Description
This two volume set provides the complete proceedings of the 1990 International Joint Conference on Neural Networks held in Washington, D.C. Complete with subject, author, and title indices, it provides an invaluable reference to the current state-of-the-art in neural networks. Included in this volume are the latest research results, applications, and products from over 2,000 researchers and application developers from around the world. Ideal as a reference for researchers and practitioners of neuroscience, the two volumes are divided into eight sections: * Neural and Cognitive Sciences * Pattern Recognition and Analysis of Network Dynamics * Learning Theory * Plenary Lecture by Bernard Widrow * Special Lectures on Self-Organizing Neural Architectures * Application Systems and Network Implementations * Robotics, Speech, Signal Processing, and Vision * Expert Systems and Other Real-World Applications
Publisher: Taylor & Francis
ISBN: 1317728335
Category : Psychology
Languages : en
Pages : 1588
Book Description
This two volume set provides the complete proceedings of the 1990 International Joint Conference on Neural Networks held in Washington, D.C. Complete with subject, author, and title indices, it provides an invaluable reference to the current state-of-the-art in neural networks. Included in this volume are the latest research results, applications, and products from over 2,000 researchers and application developers from around the world. Ideal as a reference for researchers and practitioners of neuroscience, the two volumes are divided into eight sections: * Neural and Cognitive Sciences * Pattern Recognition and Analysis of Network Dynamics * Learning Theory * Plenary Lecture by Bernard Widrow * Special Lectures on Self-Organizing Neural Architectures * Application Systems and Network Implementations * Robotics, Speech, Signal Processing, and Vision * Expert Systems and Other Real-World Applications