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2003•Unpublished venueRequires access

System identification via simultaneous perturbation stochastic approximation

Tatsuya Hirokami, Yutaka Maeda

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Abstract

The simultaneous perturbation stochastic approximation (SPSA) is an extension of Kiefer-Wolfowitz stochastic approximation (KWSA) algorithm. In SPSA, since all parameters are perturbed simultaneously, it is possible to modify the parameters with only two measurements of the evaluation function disregard of the dimension of the parameters. We propose a parameter identification algorithm using SPSA. Simulation result shows the feasibility of the identification approach proposed.

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What this paper is about

The simultaneous perturbation stochastic approximation (SPSA) is an extension of Kiefer-Wolfowitz stochastic approximation (KWSA) algorithm. In SPSA, since all parameters are perturbed simultaneously, it is possible to modify the parameters with only two measurements of the evaluation function disregard of the dimension of the parameters. We propose a parameter identification algorithm using SPSA. Simulation result shows the feasibility of the identification approach proposed.

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Available abstract

The simultaneous perturbation stochastic approximation (SPSA) is an extension of Kiefer-Wolfowitz stochastic approximation (KWSA) algorithm. In SPSA, since all parameters are perturbed simultaneously, it is possible to modify the parameters with only two measurements of the evaluation function disregard of the dimension of the parameters. We propose a parameter identification algorithm using SPSA. Simulation result shows the feasibility of the identification approach proposed.

Key concepts: Simultaneous perturbation stochastic approximation, Stochastic approximation, Approximation algorithm, Perturbation (astronomy), Mathematical optimization, Identification (biology), Function approximation, Computer science

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