The Neural Simulation Language

The Neural Simulation Language PDF Author: Alfredo Weitzenfeld
Publisher: MIT Press
ISBN: 9780262731492
Category : Computers
Languages : en
Pages : 466

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Book Description
Simulation in NSL - Modeling in NSL - Schematic Capture System - User Interface and Graphical Windows - The Modeling Language NSLM - The Scripting Language NSLS - Adaptive Resonance Theory - Depth Perception - Retina - Receptive Fields - The Associative Search Network: Landmark Learning and Hill Climbing - A Model of Primate Visual-Motor Conditional Learning - The Modular Design of the Oculomotor System in Monkeys - Crowley-Arbib Saccade Model - A Cerebellar Model of Sensorimotor Adaptation - Learning to Detour - Face Recognition by Dynamic Link Matching - Appendix I : NSLM Methods - NSLJ Extensions - NSLC Extensions - NSLJ and NSLC Differences - NSLJ and NSLC Installation Instructions.

The Neural Simulation Language

The Neural Simulation Language PDF Author: Alfredo Weitzenfeld
Publisher: MIT Press
ISBN: 9780262731492
Category : Computers
Languages : en
Pages : 466

Get Book Here

Book Description
Simulation in NSL - Modeling in NSL - Schematic Capture System - User Interface and Graphical Windows - The Modeling Language NSLM - The Scripting Language NSLS - Adaptive Resonance Theory - Depth Perception - Retina - Receptive Fields - The Associative Search Network: Landmark Learning and Hill Climbing - A Model of Primate Visual-Motor Conditional Learning - The Modular Design of the Oculomotor System in Monkeys - Crowley-Arbib Saccade Model - A Cerebellar Model of Sensorimotor Adaptation - Learning to Detour - Face Recognition by Dynamic Link Matching - Appendix I : NSLM Methods - NSLJ Extensions - NSLC Extensions - NSLJ and NSLC Differences - NSLJ and NSLC Installation Instructions.

Artificial Higher Order Neural Networks for Modeling and Simulation

Artificial Higher Order Neural Networks for Modeling and Simulation PDF Author: Zhang, Ming
Publisher: IGI Global
ISBN: 1466621761
Category : Computers
Languages : en
Pages : 455

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Book Description
"This book introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks"--Provided by publisher.

Neural Models of Language Processes

Neural Models of Language Processes PDF Author: Michael A. Arbib
Publisher:
ISBN:
Category : Language Arts & Disciplines
Languages : en
Pages : 598

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Book Description
Neural Models of Language Processes offers an interdisciplinary approach to understanding the nature of human language and the means whereby we use it. The book is organized into five parts. Part I provides an opening framework that addresses three tasks: to place neurolinguistics in current perspective; to provide two case studies of aphasia; and to discuss the """"rules of the game"""" of the various disciplines that contribute to this volume. Part II on artificial intelligence (AI) and processing models discusses the contribution of AI to neurolinguistics. The chapters in this section intro ...

The Neural Basis of Mentalizing

The Neural Basis of Mentalizing PDF Author: Michael Gilead
Publisher: Springer Nature
ISBN: 3030518906
Category : Psychology
Languages : en
Pages : 685

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Book Description
Humans have a unique ability to understand the beliefs, emotions, and intentions of others—a capacity often referred to as mentalizing. Much research in psychology and neuroscience has focused on delineating the mechanisms of mentalizing, and examining the role of mentalizing processes in other domains of cognitive and affective functioning. The purpose of the book is to provide a comprehensive overview of the current research on the mechanisms of mentalizing at the neural, algorithmic, and computational levels of analysis. The book includes contributions from prominent researchers in the field of social-cognitive and affective neuroscience, as well as from related disciplines (e.g., cognitive, social, developmental and clinical psychology, psychiatry, philosophy, primatology). The contributors review their latest research in order to compile an authoritative source of knowledge on the psychological and brain bases of the unique human capacity to think about the mental states of others. The intended audience is researchers and students in the fields of social-cognitive and affective neuroscience and related disciplines such as neuroeconomics, cognitive neuroscience, developmental neuroscience, social cognition, social psychology, developmental psychology, cognitive psychology, and affective science. Secondary audiences include researchers in decision science (economics, judgment and decision-making), philosophy of mind, and psychiatry.

Neural and Adaptive Systems

Neural and Adaptive Systems PDF Author: José C. Principe
Publisher: John Wiley & Sons
ISBN:
Category : Computers
Languages : en
Pages : 680

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Book Description
Develop New Insight into the Behavior of Adaptive Systems This one-of-a-kind interactive book and CD-ROM will help you develop a better understanding of the behavior of adaptive systems. Developed as part of a project aimed at innovating the teaching of adaptive systems in science and engineering, it unifies the concepts of neural networks and adaptive filters into a common framework. It begins by explaining the fundamentals of adaptive linear regression and builds on these concepts to explore pattern classification, function approximation, feature extraction, and time-series modeling/prediction. The text is integrated with the industry standard neural network/adaptive system simulator NeuroSolutions. This allows the authors to demonstrate and reinforce key concepts using over 200 interactive examples. Each of these examples is 'live,' allowing the user to change parameters and experiment first-hand with real-world adaptive systems. This creates a powerful environment for learning through both visualization and experimentation. Key Features of the Text The text and CD combine to become an interactive learning tool. Emphasis is on understanding the behavior of adaptive systems rather than mathematical derivations. Each key concept is followed by an interactive example. Over 200 fully functional simulations of adaptive systems are included. The text and CD offer a unified view of neural networks, adaptive filters, pattern recognition, and support vector machines. Hyperlinks allow instant access to keyword definitions, bibliographic references, equations, and advanced discussions of concepts. The CD-ROM Contains: A complete, electronic version of the text in hypertext format NeuroSolutions, an industry standard, icon-based neural network/adaptive system simulator A tutorial on how to use NeuroSolutions Additional data files to use with the simulator "An innovative approach to describing neurocomputing and adaptive learning systems from a perspective which unifies classical linear adaptive systems approaches with the modern advances in neural networks. It is rich in examples and practical insight." —James Zeidler, University of California, San Diego

Neurocomputing

Neurocomputing PDF Author: Robert Hecht-Nielsen
Publisher: Addison Wesley Publishing Company
ISBN:
Category : Computers
Languages : en
Pages : 456

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Book Description
The areas covered here are those which are commonly managed by the generalist. The four contributions discuss: the autopsy in fatal non- missile head injuries; viral encephalitis and its pathology; a general approach to neuropathological problems; and dementia in middle and late life. Gives an overview of the network theory, including background review, basic concepts, associative networks, mapping networks, spatiotemporal networks, and adaptive resonance networks. Explores the principles of fuzzy logic. Annotation copyrighted by Book News, Inc., Portland, OR

Fundamentals of Neural Network Modeling

Fundamentals of Neural Network Modeling PDF Author: Randolph W. Parks
Publisher: MIT Press
ISBN: 9780262161756
Category : Computers
Languages : en
Pages : 450

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Book Description
Provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. Over the past few years, computer modeling has become more prevalent in the clinical sciences as an alternative to traditional symbol-processing models. This book provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. It is intended to make the neural network approach accessible to practicing neuropsychologists, psychologists, neurologists, and psychiatrists. It will also be a useful resource for computer scientists, mathematicians, and interdisciplinary cognitive neuroscientists. The editors (in their introduction) and contributors explain the basic concepts behind modeling and avoid the use of high-level mathematics. The book is divided into four parts. Part I provides an extensive but basic overview of neural network modeling, including its history, present, and future trends. It also includes chapters on attention, memory, and primate studies. Part II discusses neural network models of behavioral states such as alcohol dependence, learned helplessness, depression, and waking and sleeping. Part III presents neural network models of neuropsychological tests such as the Wisconsin Card Sorting Task, the Tower of Hanoi, and the Stroop Test. Finally, part IV describes the application of neural network models to dementia: models of acetycholine and memory, verbal fluency, Parkinsons disease, and Alzheimer's disease. Contributors J. Wesson Ashford, Rajendra D. Badgaiyan, Jean P. Banquet, Yves Burnod, Nelson Butters, John Cardoso, Agnes S. Chan, Jean-Pierre Changeux, Kerry L. Coburn, Jonathan D. Cohen, Laurent Cohen, Jose L. Contreras-Vidal, Antonio R. Damasio, Hanna Damasio, Stanislas Dehaene, Martha J. Farah, Joaquin M. Fuster, Philippe Gaussier, Angelika Gissler, Dylan G. Harwood, Michael E. Hasselmo, J, Allan Hobson, Sam Leven, Daniel S. Levine, Debra L. Long, Roderick K. Mahurin, Raymond L. Ownby, Randolph W. Parks, Michael I. Posner, David P. Salmon, David Servan-Schreiber, Chantal E. Stern, Jeffrey P. Sutton, Lynette J. Tippett, Daniel Tranel, Bradley Wyble

Gas Turbines Modeling, Simulation, and Control

Gas Turbines Modeling, Simulation, and Control PDF Author: Hamid Asgari
Publisher: CRC Press
ISBN: 1498726631
Category : Science
Languages : en
Pages : 214

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Book Description
Gas Turbines Modeling, Simulation, and Control: Using Artificial Neural Networks provides new approaches and novel solutions to the modeling, simulation, and control of gas turbines (GTs) using artificial neural networks (ANNs). After delivering a brief introduction to GT performance and classification, the book:Outlines important criteria to consi

Simulating the Evolution of Language

Simulating the Evolution of Language PDF Author: Angelo Cangelosi
Publisher: Springer Science & Business Media
ISBN: 1447106636
Category : Computers
Languages : en
Pages : 350

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Book Description
This book is the first to provide a comprehensive survey of the computational models and methodologies used for studying the evolution and origin of language and communication. Comprising contributions from the most influential figures in the field, it presents and summarises the state-of-the-art in computational approaches to language evolution, and highlights new lines of development. Essential reading for researchers and students in the fields of evolutionary and adaptive systems, language evolution modelling and linguistics, it will also be of interest to researchers working on applications of neural networks to language problems. Furthermore, due to the fact that language evolution models use multi-agent methodologies, it will also be of great interest to computer scientists working on multi-agent systems, robotics and internet agents.

The NEURON Book

The NEURON Book PDF Author: Nicholas T. Carnevale
Publisher: Cambridge University Press
ISBN: 1139447831
Category : Medical
Languages : en
Pages : 399

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Book Description
The authoritative reference on NEURON, the simulation environment for modeling biological neurons and neural networks that enjoys wide use in the experimental and computational neuroscience communities. This book shows how to use NEURON to construct and apply empirically based models. Written primarily for neuroscience investigators, teachers, and students, it assumes no previous knowledge of computer programming or numerical methods. Readers with a background in the physical sciences or mathematics, who have some knowledge about brain cells and circuits and are interested in computational modeling, will also find it helpful. The NEURON Book covers material that ranges from the inner workings of this program, to practical considerations involved in specifying the anatomical and biophysical properties that are to be represented in models. It uses a problem-solving approach, with many working examples that readers can try for themselves.