DocumentCode
288645
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
Volume
4
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
2153
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ICNN.1994.374549
Filename
374549
Link To Document