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Identification Methods for Two-Variable Difference Systems

机译:二变量差分系统的辨识方法

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This paper proposes two identification methods for two-variable difference systems. The output and the input of the two-variable difference systems depend not only on time but also on spatial coordinates. A recursive least squares algorithm and a stochastic gradient algorithm are introduced to estimate the unknown parameters. Furthermore, in order to increase the convergence rate and to decrease the computational effort, a forgetting factor stochastic gradient algorithm is proposed. The simulation results indicate that the proposed methods are effective.
机译:本文针对二元变量系统提出了两种辨识方法。二元差异系统的输出和输入不仅取决于时间,而且取决于空间坐标。引入了递归最小二乘算法和随机梯度算法来估计未知参数。此外,为了提高收敛速度并减少计算量,提出了一种遗忘因子随机梯度算法。仿真结果表明该方法是有效的。

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