Electronic Neural Networks For Global Optimization

A. P. Thakoor; A. W. Moopenn; S. Eberhardt

doi:10.1117/12.969917

1 February 1990 Electronic Neural Networks For Global Optimization

A. P. Thakoor, A. W. Moopenn, S. Eberhardt

Proceedings Volume 1196, Intelligent Control and Adaptive Systems; (1990) https://doi.org/10.1117/12.969917
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

An electronic neural network with feedback architecture, implemented in analog custom VLSI is described. Its application to problems of global optimization for dynamic assignment is discussed. The convergence properties of the neural network hardware are compared with computer simulation results. The neural network's ability to provide optimal or near optimal solutions within only a few neuron time constants, a speed enhancement of several orders of magnitude over conventional search methods, is demonstrated. The effect of noise on the circuit dynamics and the convergence behavior of the neural network hardware is also examined.

Citation Download Citation

A. P. Thakoor, A. W. Moopenn, and S. Eberhardt "Electronic Neural Networks For Global Optimization", Proc. SPIE 1196, Intelligent Control and Adaptive Systems, (1 February 1990); https://doi.org/10.1117/12.969917

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