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Mathematical Methods of Neurodynamics and Self-Organization

In: Biomathematics and Related Computational Problems

Author

Listed:
  • Shun-ichi Amari

    (University of Tokyo, Faculty of Engineering)

Abstract

Information is processed in the brain by parallel mutual interactions of neurons. Moreover, its behavior is improved by self-organization and learning. In order to understand its information processing mechanism, it is necessary to study the properties of the dynamics of neural excitation patterns and of the dynamics of self-organization or learning. Mathematical methods are presented here for analyzing neurodynamics both in local and distributed representations of information.

Suggested Citation

  • Shun-ichi Amari, 1988. "Mathematical Methods of Neurodynamics and Self-Organization," Springer Books, in: Luigi M. Ricciardi (ed.), Biomathematics and Related Computational Problems, pages 3-11, Springer.
    • Handle: RePEc:spr:sprchp:978-94-009-2975-3_1
    DOI: 10.1007/978-94-009-2975-3_1
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