On the efficiency of Gaussian adaptation
- 92 Downloads
Gaussian Adaptation (GA) is a stochastic process that adapts a Gaussian distribution to a region or set of feasible points in parameter space. As a result of the adaptation, GA becomes a maximum dispersion process extending the sampling over the largest possible volume in parameter space while keeping the probability of finding feasible points at a suitable level. For such a process, a general measure of efficiency is defined and an efficiency theorem is proved.
Key WordsMathematical programming Monte Carlo optimization stochastic adaptation Gaussian adaptation evolution
Unable to display preview. Download preview PDF.
- 1.Kjellström, G.,Network Optimization by Random Variation of Component Values, Ericsson Technics, Vol. 25, pp. 133–151, 1969.Google Scholar
- 2.Kjellström, G.,Optimization of Electrical Networks with Respect to Tolerance Costs, Ericsson Technics, Vol. 3, pp. 157–175, 1970.Google Scholar
- 3.Kjellström, G., andTaxén, L.,Stochastic Optimization in System Design, IEEE Transactions on Circuits and Systems, Vol. CAS-28, pp. 702–715, 1981.Google Scholar
- 4.Kjellström, G., Taxén, L., andLindberg, P. O.,Discrete Optimization of Digital Filters Using Gaussian Adaptation and Quadratic Function Minimization, IEEE Transactions on Circuits and Systems, Vol. CAS-34, pp. 1238–1242, 1987.Google Scholar
- 5.Middleton, D.,An Introduction to Statistical Communication Theory, McGraw-Hill, New York, 1960.Google Scholar
- 6.Kirkpatrick, S., Gelatt, C. D., Jr., andVecci, M.,Optimization by Simulated Annealing, Science, Vol. 220, pp. 671–680, 1983.Google Scholar
- 7.Sharma, B. D., Mitter, J., andMohan, M.,On Measures of Useful Information, Information and Control, Vol. 39, pp. 323–336, 1978.Google Scholar