Title :
An analog network for geometric optimization problem
Author :
Li, X. ; Wong, W.S.
Author_Institution :
Dept. of Inf. Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
fDate :
27 Jun-2 Jul 1994
Abstract :
An analog neural-type network was developed based on the elastic net approach to solve a general class of geometric optimization problem. In this paper, a mathematical formulation was first described, and then, the evolution process of the network state was qualitatively analyzed. Experimental results show that the algorithm presented here scales well with the network size and can efficiently find the near-optimal solution within hundreds of iterations
Keywords :
analogue processing circuits; geometric programming; mathematics computing; neural chips; analog neural-type network; elastic net approach; geometric optimization problem; Analog computers; Circuit simulation; Concurrent computing; Costs; Hopfield neural networks; Iterative algorithms; Neural networks; Simulated annealing; Traveling salesman problems; Very large scale integration;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374549
