Introduction to Neural and Cognitive Modeling
Daniel S. Levine(Author)
Lawrence Erlbaum Associates Inc (Publisher)
Published on 1. August 1991
Book
Hardback
456 pages
978-0-8058-0267-2 (ISBN)
Article exhausted; check for reprint
Description
This text reviews the major theories of the mechanistic organization of cognitive functions -- learning, perception, categorization, motor control and decision making. An excellent introduction to neural networks, it integrates insights from neurobiology, psychology, computer science, and mathematics, making it particularly suitable for those with backgrounds in any of these fields. The history of neural networks and some of their major organizing principles are outlined here, as is the development of cognitive functions -- from the simple to the complex. Computer simulation exercises are also included, some of which implement known models, while others ask students to design networks.
More details
Language
English
Place of publication
Mahwah
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 229 mm
Width: 152 mm
ISBN-13
978-0-8058-0267-2 (9780805802672)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

Daniel S. Levine
Introduction to Neural and Cognitive Modeling
Book
02/2000
2nd Edition
Lawrence Erlbaum Associates Inc
€170.84
Article exhausted; check for reprint
Additional editions
Daniel S. Levine
Introduction to Neural and Cognitive Modeling
Book
08/1991
Lawrence Erlbaum Associates Inc
€38.51
Article exhausted; check for reprint
Content
Contents: Preface. Brain and Machine; The Same Principles? Historical Outline. Associative Learning and Synaptic Plasticity. Competition, Lateral Inhibition, and Short-term Memory. Conditioning, Attention, and Reinforcement. Coding and Categorization. Optimization, Control, Decision, and Knowledge Representation. A Few Recent Technical Advances. Appendices: Basic Facts of Neurobiology. Difference and Differential Equations in Neural Networks.