Overview

the mass of experimental data from current research in psychology and physiology, Grossberg proposes and develops a non-linear mathematics as a model for specific functions of mind and brain. He finds the classic approach to the mathematical modelling of mind and brain systematically inadequate. This inadequacy, he holds, arises from the attempt to describe adaptive systems in the mathematical language of 9 physics developed to describe ""stationary"", i. e. non-adaptive and non-evolving systems. In place of this linear mathematics, Grossberg develops his non-linear approach. His method is at once imaginative, rigorous, and philosophically significant: it is the thought experiment. It is here that the richness of his interdisciplinary mastery, and the power of his methods, constructions and proofs, reveal themselves. The method is what C. S. Peirce characterized as the method of abduction, or of hypothetical inference in theory construction: given the output of the system as a psychological phenomenon (e. g.

Full Product Details

Author:   S.T. Grossberg
Publisher:   Springer
Imprint:   Kluwer Academic Publishers
Edition:   1982 ed.
Volume:   70
Dimensions:   Width: 15.50cm , Height: 3.40cm , Length: 23.50cm
Weight:   2.080kg
ISBN:  

9789027713599

ISBN 10:   9027713596
Pages:   662
Publication Date:   30 June 1982
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

1. How Does a Brain Build a Cognitive Code?.- 2. Some Physiological and Biochemical Consequences of Psychological Postulates.- 3. Classical and Instrumental Learning by Neural Networks.- 4. Pattern Learning by Functional-Differential Neural Networks with Arbitrary Path Weights.- 5. A Neural Theory of Punishment and Avoidance. II: Quantitative Theory.- 6. A Neural Model of Attention, Reinforcement and Discrimination Learning.- 7. Neural Expectation: Cerebellar and Retinal Analogs of Cells Fired by Learnable or Unlearned Pattern Classes.- 8. Contour Enhancement, Short Term Memory, and Constancies in Reverberating Neural Networks.- 9. Biological Competition: Decision Rules, Pattern Formation, and Oscillations.- 10. Competition, Decision, and Consensus.- 11. Behavioral Contrast in Short Term Memory: Serial Binary Memory Models or Parallel Continuous Memory Models?.- 12. Adaptive Pattern Classification and Universal Recoding. I: Parallel Development and Coding of Neural Feature Detectors.- 13. A Theory of Human Memory: Self-Organization and Performance of Sensory-Motor Codes, Maps, and Plans.- List of Publications.

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