A subspace algorithm for identifying 2-D CRSD systems with deterministic inputs

J. Ramos, A. Alenany, H. Shang, P. Santos
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引用次数: 5

Abstract

In this paper, the class of subspace system identification algorithms is used to derive a new identification algorithm for 2-D causal, recursive, and separable-in-denominator (CRSD) state space systems in the Roesser model form. The algorithm take a given deterministic input-output pair of 2-D signals and computes the system order (n) and system parameter matrices {A;B;C;D}. Since the CRSD model can be treated as two 1-D systems, the proposed algorithm first separates the vertical component from the state and output equations and then formulates an equivalent set of 1-D horizontal subspace equations. The solution to the horizontal subspace identification subproblem contains all the information necessary to compute the system order and parameter matrices, including those from the vertical subsystem.
具有确定性输入的二维CRSD系统的子空间识别算法
本文利用子空间系统辨识算法,导出了一种新的Roesser模型形式的二维因果递归可分分母(CRSD)状态空间系统辨识算法。该算法取给定的确定性二维信号输入输出对,计算系统阶数(n)和系统参数矩阵{a;B;C;D}。由于CRSD模型可以视为两个一维系统,因此该算法首先将状态和输出方程中的垂直分量分离出来,然后构建等效的一维水平子空间方程集。水平子空间辨识子问题的解包含了计算系统阶数和参数矩阵所需的所有信息,包括垂直子系统的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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