Adaptive step size random search

作者：M. Schumer, Ken Steiglitz · 发表于：IEEE Transactions on Automatic Control · 年份：1968 · DOI：10.1109/tac.1968.1098903 · 被引用次数：281 · 研究领域：Numerical methods in inverse problems、Neural Networks and Applications、Iterative Methods for Nonlinear Equations

Fixed step size random search for minimization of functions of several parameters is described and compared with the fixed step size gradient method for a particular surface. A theoretical technique, using the optimum step size at each step, is analyzed. A practical adaptive step size random search algorithm is then proposed, and experimental experience is reported that shows the superiority of random search over other methods for sufficiently high dimension.