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Accession Number:
ADP007158
Title:
Randomized Newton-Raphson and Animal Search,
Corporate Author:
TULANE UNIV NEW ORLEANS LA
Report Date:
1992-01-01
Abstract:
Adding systematic noise to the step term of the Newton-Raphson NR root finding algorithm permits expected q-linear convergence and convergence almost surely to the root for a larger class of functions and larger starting sets than those for which NR converges deterministically. These results have application not only to a wide range of optimization problems but also to understanding the behavioral repertory of animals undertaking pheromone induced search. It is shown that the search reduces in many cases to finding the root of a function of two or three dimensions. In cases as in the search of the gypsy moth for its mate where the animal cannot simply travel in the direction of increasing signal scent randomized NR gives insight into the search behavior required to discover the signal source.
Supplementary Note:
This article is from 'Computing Science and Statistics: Proceedings of the Symposium on the Interface Critical Applications of Scientific Computing: Biology, Engineering, Medicine, Speech Held in Seattle, Washington on 21-24 April 1991,' AD-A252 938, p309-312.
Pages:
0004
File Size:
0.00MB
