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Neural Network Models Of Cognition


Neural Network Models Of Cognition
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Introduction To Neural And Cognitive Modeling


Introduction To Neural And Cognitive Modeling
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Author : Daniel S. Levine
language : en
Publisher: Psychology Press
Release Date : 2000-02

Introduction To Neural And Cognitive Modeling written by Daniel S. Levine and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-02 with Psychology categories.


This thoroughly, thoughtfully revised edition of a very successful textbook makes the principles and the details of neural network modeling accessible to cognitive scientists of all varieties as well as to others interested in these models. Research since the publication of the first edition has been systematically incorporated into a framework of proven pedagogical value. Features of the second edition include: * A new section on spatiotemporal pattern processing * Coverage of ARTMAP networks (the supervised version of adaptive resonance networks) and recurrent back-propagation networks * A vastly expanded section on models of specific brain areas, such as the cerebellum, hippocampus, basal ganglia, and visual and motor cortex * Up-to-date coverage of applications of neural networks in areas such as combinatorial optimization and knowledge representation As in the first edition, the text includes extensive introductions to neuroscience and to differential and difference equations as appendices for students without the requisite background in these areas. As graphically revealed in the flowchart in the front of the book, the text begins with simpler processes and builds up to more complex multilevel functional systems. For more information visit the author's personal Web site at www.uta.edu/psychology/faculty/levine/



Neural Network Models Of Cognition


Neural Network Models Of Cognition
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Author : J.W. Donahoe
language : en
Publisher: Elsevier
Release Date : 1997-09-26

Neural Network Models Of Cognition written by J.W. Donahoe and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-09-26 with Computers categories.


This internationally authored volume presents major findings, concepts, and methods of behavioral neuroscience coordinated with their simulation via neural networks. A central theme is that biobehaviorally constrained simulations provide a rigorous means to explore the implications of relatively simple processes for the understanding of cognition (complex behavior). Neural networks are held to serve the same function for behavioral neuroscience as population genetics for evolutionary science. The volume is divided into six sections, each of which includes both experimental and simulation research: (1) neurodevelopment and genetic algorithms, (2) synaptic plasticity (LTP), (3) sensory/hippocampal systems, (4) motor systems, (5) plasticity in large neural systems (reinforcement learning), and (6) neural imaging and language. The volume also includes an integrated reference section and a comprehensive index.



Cognitive Modeling


Cognitive Modeling
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Author : Thad A. Polk
language : en
Publisher: MIT Press
Release Date : 2002

Cognitive Modeling written by Thad A. Polk and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Psychology categories.


A comprehensive introduction to the computational modeling of human cognition.



The Cambridge Handbook Of Computational Psychology


The Cambridge Handbook Of Computational Psychology
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Author : Ron Sun
language : en
Publisher: Cambridge University Press
Release Date : 2008-04-28

The Cambridge Handbook Of Computational Psychology written by Ron Sun and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-28 with Computers categories.


A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.



Connectionist Models In Cognitive Psychology


Connectionist Models In Cognitive Psychology
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Author : George Houghton
language : en
Publisher: Psychology Press
Release Date : 2004-08-02

Connectionist Models In Cognitive Psychology written by George Houghton and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-08-02 with Psychology categories.


A state-of-the-art review of neural network modelling in core areas of cognitive psychology including: memory and learning, language (written and spoken), cognitive development, cognitive control, attention and action.



Neural Symbolic Cognitive Reasoning


Neural Symbolic Cognitive Reasoning
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Author : Artur S. D'Avila Garcez
language : en
Publisher: Springer Science & Business Media
Release Date : 2009

Neural Symbolic Cognitive Reasoning written by Artur S. D'Avila Garcez and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computers categories.


This book explores why, regarding practical reasoning, humans are sometimes still faster than artificial intelligence systems. It is the first to offer a self-contained presentation of neural network models for many computer science logics.



Computational Explorations In Cognitive Neuroscience


Computational Explorations In Cognitive Neuroscience
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Author : Randall C. O'Reilly
language : en
Publisher: MIT Press
Release Date : 2000-08-28

Computational Explorations In Cognitive Neuroscience written by Randall C. O'Reilly and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-08-28 with Medical categories.


This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the computational cognitive neuroscience. The goal of computational cognitive neuroscience is to understand how the brain embodies the mind by using biologically based computational models comprising networks of neuronlike units. This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the field. The neural units in the simulations use equations based directly on the ion channels that govern the behavior of real neurons, and the neural networks incorporate anatomical and physiological properties of the neocortex. Thus the text provides the student with knowledge of the basic biology of the brain as well as the computational skills needed to simulate large-scale cognitive phenomena. The text consists of two parts. The first part covers basic neural computation mechanisms: individual neurons, neural networks, and learning mechanisms. The second part covers large-scale brain area organization and cognitive phenomena: perception and attention, memory, language, and higher-level cognition. The second part is relatively self-contained and can be used separately for mechanistically oriented cognitive neuroscience courses. Integrated throughout the text are more than forty different simulation models, many of them full-scale research-grade models, with friendly interfaces and accompanying exercises. The simulation software (PDP++, available for all major platforms) and simulations can be downloaded free of charge from the Web. Exercise solutions are available, and the text includes full information on the software.



Deep Learning For Robot Perception And Cognition


Deep Learning For Robot Perception And Cognition
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Author : Alexandros Iosifidis
language : en
Publisher: Academic Press
Release Date : 2022-02-04

Deep Learning For Robot Perception And Cognition written by Alexandros Iosifidis and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-04 with Technology & Engineering categories.


Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. - Presents deep learning principles and methodologies - Explains the principles of applying end-to-end learning in robotics applications - Presents how to design and train deep learning models - Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more - Uses robotic simulation environments for training deep learning models - Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis



Functional Models Of Cognition


Functional Models Of Cognition
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Author : A. Carsetti
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11

Functional Models Of Cognition written by A. Carsetti and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Psychology categories.


Our ontology as well as our grammar are, as Quine affirms, ineliminable parts of our conceptual contribution to our theory of the world. It seems impossible to think of enti ties, individuals and events without specifying and constructing, in advance, a specific language that must be used in order to speak about these same entities. We really know only insofar as we regiment our system of the world in a consistent and adequate way. At the level of proper nouns and existence functions we have, for instance, a standard form of a regimented language whose complementary apparatus consists of predicates, variables, quantifiers and truth functions. If, for instance, the discoveries in the field of Quantum Mechanics should oblige us, in the future, to abandon the traditional logic of truth functions, the very notion of existence, as established until now, will be chal lenged. These considerations, as developed by Quine, introduce us to a conceptual perspective like the "internal realist" perspective advocated by Putnam whose principal aim is, for cer tain aspects, to link the philosophical approaches developed respectively by Quine and Wittgenstein. Actually, Putnam conservatively extends the approach to the problem of ref erence outlined by Quine: in his opinion, to talk of "facts" without specifying the language to be used is to talk of nothing.



Process Neural Networks


Process Neural Networks
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Author : Xingui He
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-05

Process Neural Networks written by Xingui He and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-05 with Computers categories.


"Process Neural Network: Theory and Applications" proposes the concept and model of a process neural network for the first time, showing how it expands the mapping relationship between the input and output of traditional neural networks and enhances the expression capability for practical problems, with broad applicability to solving problems relating to processes in practice. Some theoretical problems such as continuity, functional approximation capability, and computing capability, are closely examined. The application methods, network construction principles, and optimization algorithms of process neural networks in practical fields, such as nonlinear time-varying system modeling, process signal pattern recognition, dynamic system identification, and process forecast, are discussed in detail. The information processing flow and the mapping relationship between inputs and outputs of process neural networks are richly illustrated. Xingui He is a member of Chinese Academy of Engineering and also a professor at the School of Electronic Engineering and Computer Science, Peking University, China, where Shaohua Xu also serves as a professor.