基于累计量辨识非最小相位FIR系统的新方法

李玮; 萧允治

基于累计量辨识非最小相位FIR系统的新方法

李玮,
萧允治

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- 被引次数: 0
出版历程
- 收稿日期: 1999-03-15
- 修回日期: 1999-11-08
- 刊出日期: 2000-11-19

NEW APPROACH TO FIR SYSTEM IDENTIFICATION USING HIGHER ORDER CUMULANTS

Li Wei,
Siu Wan-Chi

摘要

摘要: 该文考虑用带有噪声输出数据的累计量实现对非最小相位PIR系统的参数辨识问题。提出一个新的基于高阶累计量的方法。其特点如下，(1)灵活性：采用了两个任意阶次相邻的输出累计量；(2)线性：方法的表达式相对于未知量为线性。这不同于其它一些已存在的算法。因而，避免了额外的滞后处理，可提高参数估计的准确性。本文在ARMA高斯噪声及三种实际噪声情况下，做了大量的实验。结果表明，本文提出的算法不仅能有效地完成参数估计，而且，在低信噪比下，其估计结果比其它已有的算法更准确。
- PIR系统;高阶累计量;参数估计
Abstract: The problem of identifying the parameters of the nonminimum phase FIR system from the cumulants of noisy output samples is addressed. A novel method by using higher-order cumulants is proposed with the following advantages. (1) Flexibility: the method employs two arbitrary adjacent order cumulants of output.(2) Linearity: the formulation in the method is linear with respect to the unknowns, unlike the existing cumulant-based algorithms. The post-processing is thus avoided.

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参考文献(1)

Mendel J M. Tutorial on higher-order statistics (spectra) in signal processing and system theory:Theoretical results and some applications[J].Proc. IEEE.1991, 79(3):278-305[2]Zhang Xian-Da, Zhang Yuan-Sheng. FIR system identification using higher order statistics alone. IEEE Trans. on Signal Processing, 1994, SP-42(10): 2854-2858.[3]Giannakis G B. Cumulants: A powerful tool in signal processing[J].Proc. of the IEEE.1987, 75(9):1333-1334[4]Giannakis G B, Mendel J M. Identification of non-minimum phase systems using higher-order statistics. IEEE Trans. on Acoustics Speech and Signal Processing, 1989, ASSP-37(3): 360-377.[5]Friedlander B, Porat B. Asympotically optimal estimation of MA and ARMA parameters of non-Gaussian processes from higher-order moments. IEEE Trans. on Automat. Contr., 1990,AC-35(1): 27-35.[6]Tugnait J K. Approaches of FIR system identification with noisy data using higher order statistics. IEEE Trans. on Acoustics Speech and Signal Processing, 1990, ASSP-38(7): 1307-1317.[7]Tugnait J K. New results on FIR system identification using higher order statistics. IEEE Trans. on Signal Processing, 1991, SP-39(10): 2216-2221.[8]Carrion M C, Ruiz D P, Gallego A, Morente J A. FIR system identification using third-and fourth-order cumulants[J].Electron. Lett.1995, 31(8):612-614[9]Xiao Y, Shadaydeh M, Tadokoro Y. Overdetermined C(q, k) formula using third and fourth order cumulants[J].Electron. Lett.1996, 32(6):601-603[10]Giannakis G B, Mendel J M. Cumulant-based order determination of non-Gaussian ARMA models. IEEE Trans. on Acoustics Speech and Signal Processing, 1993, ASSP-38(8): 1411-1422.[11]Zhang X D, Zhang Y S. Singular value decomposition-based MA order determination of nonGauusian ARMA models. IEEE Trans. on Signal Processing, 1993, SP-41(8): 2657-2664.[12]Chow T W S, Tan Hong-Zhou. Semiblind identification of nonminimum-phase ARMA models via order recursion with higher order cumulants. IEEE Trans. on Industrial Electronics, 1998,IE-45(4): 663-671.[13]Brillinger D R, Rosenblatt M. Computation and Interpretation of K-th-Order Spectra, in Specrtral Analysis of Time Seriers. B. Harrias, Ed. New York: Wiley, 1967, 189-232.

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