Gradient minimax techniques for system modelling
J.W. Bandler, N. D. MARKETTOS, T. V. Srinivasan
Abstract
J.W. Bandler, N. D. MARKETTOS, T. V. Srinivasan
Abstract
Some recently proposed gradient methods for minimax or near minimax approximation are applied to producing optimal second-order and third-order models of a high-order system. The Fletcher-Powell method, a more recent method by Fletcher and o. method by Jacobson and Oksman are employed with least pth approximation, using large values of p, as proposed by Bandler and Charalambous and critically compared with the grazer search technique of minimax approximation by Bandler et al. The solutions obtained are shown to satisfy the necessary conditions for a minimax optimum.
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Some recently proposed gradient methods for minimax or near minimax approximation are applied to producing optimal second-order and third-order models of a high-order system. The Fletcher-Powell method, a more recent method by Fletcher and o. method by Jacobson and Oksman are employed with least pth approximation, using large values of p, as proposed by Bandler and Charalambous and critically compared with the grazer search technique of minimax approximation by Bandler et al. The solutions obtained are shown to satisfy the necessary conditions for a minimax optimum.
Key concepts: Minimax, Minimax approximation algorithm, Mathematics, Applied mathematics, Mathematical optimization, Order (exchange), Finance, Economics