Multivariate stochastic approximation using a simultaneous perturbation gradient approximation

作者: J.C. Spall

DOI: 10.1109/9.119632

关键词: Minimax approximation algorithmAsymptotic distributionApproximation algorithmStandard algorithmsSimultaneous perturbation stochastic approximationStochastic approximationMathematical analysisApproximation errorMathematicsFunction approximation

摘要: The problem of finding a root the multivariate gradient equation that arises in function minimization is considered. When only noisy measurements are available, stochastic approximation (SA) algorithm for general Kiefer-Wolfowitz type appropriate estimating root. paper presents an SA based on simultaneous perturbation instead standard finite-difference Keifer-Wolfowitz procedures. Theory and numerical experience indicate can be significantly more efficient than algorithms large-dimensional problems. >

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