Accession Number:

ADA295495

Title:

Dynamical Systems, Neural Networks and Cortical Models ASSERT 93.

Descriptive Note:

Final technical rept. 1 Sep 93-30 Nov 94,

Corporate Author:

CALIFORNIA UNIV BERKELEY CENTER FOR PURE AND APPLIED MATHEMATICS

Report Date:

1994-11-30

Pagination or Media Count:

3.0

Abstract:

Work was done on an oscillating neural network computer that could recognize sequences of characters of a grammar. It was extended to employ selective control of synchronization to direct the flow of communication and computation within the architecture to solve a grammatical inference problem. Because intercommunicating modules of the architecture are analytically guaranteed to store and recall multiple oscillatory and chaotic attractors, the architecture served as a framework in which to arrange and exploit the special capabilities dynamic attractors. In this architecture, oscillation amplitude codes the information content or activity of a module unit, whereas phase and frequency are used to softwire the network. Only synchronized modules communicate by exchanging amplitude information. Chaotic attractors from the large family of Chua attractors were synchronized for operation in the architecture using techniques of coupling developed for secure broadspectrum communication by a modulated chaotic carrier wave.

Subject Categories:

  • Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE