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Multivariate stochastic approximation using a simultaneous perturbation gradient approximation

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1 Author(s)
Spall, J.C. ; Appl. Phys. Lab., Johns Hopkins Univ., Laurel, MD, USA

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

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Automatic Control, IEEE Transactions on  (Volume:37 ,  Issue: 3 )