Design of parallel distributed Cauchy machines
- 1 January 1989
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 529-532 vol.1
- https://doi.org/10.1109/ijcnn.1989.118629
Abstract
A parallel and stochastic version of Hopfield-like neural networks is presented. Cauchy color noise is assumed. The specific noise is desirable for fast convergence to a fixed point representing a neighborhood minimum. It can be quickly quenched at each iteration according to a proven cooling schedule in generating random states on the energy landscape. An exact Cauchy acceptance criterion is analytically derived for hill-climbing capability. The improvement is twofold: a faster cooling schedule (the inversely linear cooling schedule characterized by the Cauchy simulated annealing) and parallel executions of all neurons. Such a Cauchy machine can be electronically implemented, and the design is given.Keywords
This publication has 8 references indexed in Scilit:
- Fast TSP algorithm based on binary neuron output and analog neuron input using the zero-diagonal interconnect matrix and necessary and sufficient constraints of the permutation matrixPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1988
- Fast simulated annealingPhysics Letters A, 1987
- Nonconvex optimization by fast simulated annealingProceedings of the IEEE, 1987
- Simple 'neural' optimization networks: An A/D converter, signal decision circuit, and a linear programming circuitIEEE Transactions on Circuits and Systems, 1986
- Fast simulated annealingAIP Conference Proceedings, 1986
- “Neural” computation of decisions in optimization problemsBiological Cybernetics, 1985
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of ImagesIeee Transactions On Pattern Analysis and Machine Intelligence, 1984
- Optimization by Simulated AnnealingScience, 1983