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Design Method of Neural Networks for Limit Cycle Generator by Linear Programming

Teru YONEYAMA, Hiroshi NINOMIYA, Hideki ASAI

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Summary :

In this report, a design method of neural networks for limit cycle generator is described. First, the constraint conditions for the synaptic weights, which are given by the linear inequalities, are derived from the dynamics of neural networks. Next, the linear inequalities are solved by the linear programming method. The synaptic weights and other parameters are determined by the above solutions. Furthermore, neuro-based limit cycle generator is designed with analog electronic circuits and simulated by Spice. Finally, we confirm that our design method is efficient and practical for the design of neuro-based limit cycle generator.

Publication
IEICE TRANSACTIONS on Fundamentals Vol.E84-A No.2 pp.688-692
Publication Date
2001/02/01
Publicized
Online ISSN
DOI
Type of Manuscript
LETTER
Category
Neural Networks and Bioengineering

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