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On the Convergence Speed of Inverse Identification Adaptive IIR Filters

机译:关于逆识别自适应IIR过滤器的收敛速度

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The approach based on balanced realization theory, previously used to analyze the convergence speed of adaptive IIR filters in the identification configuration and to propose a faster algorithm (sucessive approximations algorithm), is now used in the inverse identification configuration. This case is of interest for applications such as channel equalization and system identification itself. The main result we obtain here is that, while in identification configuration the Hankel singular values of the system being identified have an important effect on convergence speed, in the inverse identification case it is the Hankel singular values of a certain system related to the system being identified that have this role. From this result, a condition for faster convergence speed is obtained, which suggests that an adaptive algorithm similar to the successive approximations algorithm can be obtained for inverse identification. Numerical examples are presented, which strongly corroborate the adopted analytical approach.
机译:基于平衡实现理论的方法,以前用于分析识别配置中自适应IIR滤波器的收敛速度,并提出更快的算法(Sucessive近似算法),现在在逆识别配置中使用。这种情况对诸如信道均衡和系统识别本身等的应用程序感兴趣。我们在此获得的主要结果是,虽然在识别配置中,所识别的系统的Hankel奇异值对收敛速度有重要影响,在逆识别情况下,它是与系统有关的某种系统的Hankel奇异值。确定了这一角色。从该结果,获得了更快的收敛速度的条件,这表明可以获得类似于连续近似算法的自适应算法以进行识别。提出了数值例子,其强烈证实了采用的分析方法。

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