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Comparisons of stochastic gradient and least squares algorithms for multivariable systems

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3 Author(s)
Yuwu Liao ; Dept. of Phys. & Electron. Inf. Technol., Xiangfan Univ., Xiangfan, China ; Yanjun Liu ; Feng Ding

Two identification models are obtained for multivariable ARX systems by different parameterization, and the corresponding two least squares and two stochastic gradient algorithms are given based on the lest squares principle and the stochastic gradient search principle and minimizing different cost functions. The performances of these algorithms are analyzed and compared by the simulation tests.

Published in:

Control and Decision Conference (CCDC), 2010 Chinese

Date of Conference:

26-28 May 2010

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