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2005•Electrical Engineering in JapanRequires access

Parameter estimation using simultaneous perturbation stochastic approximation

Tatsuya Hirokami, Yutaka Maeda, Hiroyuki Tsukada

Open publisher page 17 citations

Abstract

The simultaneous perturbation stochastic approximation (SPSA) is an extension of the Kiefer–Wolfowitz stochastic approximation algorithm. In SPSA, since all parameters are perturbed simultaneously, it is possible to modify parameters with only two measurements of an evaluation function regardless of the dimension of the parameter. We propose a parameter estimation algorithm using the SPSA. A convergence theorem for the proposed algorithm is shown. A simulation result also reveals the feasibility of the identification scheme proposed here. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 154(2): 30–39, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20239

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What this paper is about

The simultaneous perturbation stochastic approximation (SPSA) is an extension of the Kiefer–Wolfowitz stochastic approximation algorithm. In SPSA, since all parameters are perturbed simultaneously, it is possible to modify parameters with only two measurements of an evaluation function regardless of the dimension of the parameter. We propose a parameter estimation algorithm using the SPSA. A convergence theorem for the proposed algorithm is shown. A simulation result also reveals the feasibility of the identification scheme proposed here. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 154(2): 30–39, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20239

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Available abstract

The simultaneous perturbation stochastic approximation (SPSA) is an extension of the Kiefer–Wolfowitz stochastic approximation algorithm. In SPSA, since all parameters are perturbed simultaneously, it is possible to modify parameters with only two measurements of an evaluation function regardless of the dimension of the parameter. We propose a parameter estimation algorithm using the SPSA. A convergence theorem for the proposed algorithm is shown. A simulation result also reveals the feasibility of the identification scheme proposed here. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 154(2): 30–39, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20239

Key concepts: Simultaneous perturbation stochastic approximation, Stochastic approximation, Perturbation (astronomy), Applied mathematics, Estimation theory, Convergence (economics), Identification scheme, Mathematical optimization

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