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Proceedings Paper

Solving linear hard-optimization problems
Author(s): Hua Li; Yuan Dong Ji
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Paper Abstract

In this paper, we address the linear hard optimization problems with the emphasis on two- point boundary value conditions which is referred to as two-point boundary value problem (TPBVP). We propose two different neural networks for solving a class of linear TPBVPs. We show that the proposed networks can solve linear TPBVPs. We also provide experimental results.

Paper Details

Date Published: 1 July 1992
PDF: 6 pages
Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); doi: 10.1117/12.140089
Show Author Affiliations
Hua Li, Texas Tech Univ. (United States)
Yuan Dong Ji, Case Western Reserve Univ. (United States)

Published in SPIE Proceedings Vol. 1710:
Science of Artificial Neural Networks
Dennis W. Ruck, Editor(s)

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