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基于累計(jì)量辨識(shí)非最小相位FIR系統(tǒng)的新方法

李瑋,  蕭允治

李瑋, 蕭允治. 基于累計(jì)量辨識(shí)非最小相位FIR系統(tǒng)的新方法[J]. 電子與信息學(xué)報(bào), 2000, 22(6): 921-928.
引用本文: 李瑋, 蕭允治. 基于累計(jì)量辨識(shí)非最小相位FIR系統(tǒng)的新方法[J]. 電子與信息學(xué)報(bào), 2000, 22(6): 921-928.
Li Wei, Siu Wan-Chi . NEW APPROACH TO FIR SYSTEM IDENTIFICATION USING HIGHER ORDER CUMULANTS[J]. Journal of Electronics & Information Technology, 2000, 22(6): 921-928.
Citation: Li Wei, Siu Wan-Chi . NEW APPROACH TO FIR SYSTEM IDENTIFICATION USING HIGHER ORDER CUMULANTS[J]. Journal of Electronics & Information Technology, 2000, 22(6): 921-928.

基于累計(jì)量辨識(shí)非最小相位FIR系統(tǒng)的新方法

NEW APPROACH TO FIR SYSTEM IDENTIFICATION USING HIGHER ORDER CUMULANTS

  • 摘要: 該文考慮用帶有噪聲輸出數(shù)據(jù)的累計(jì)量實(shí)現(xiàn)對(duì)非最小相位PIR系統(tǒng)的參數(shù)辨識(shí)問(wèn)題。提出一個(gè)新的基于高階累計(jì)量的方法。其特點(diǎn)如下，(1)靈活性：采用了兩個(gè)任意階次相鄰的輸出累計(jì)量；(2)線性：方法的表達(dá)式相對(duì)于未知量為線性。這不同于其它一些已存在的算法。因而，避免了額外的滯后處理，可提高參數(shù)估計(jì)的準(zhǔn)確性。本文在ARMA高斯噪聲及三種實(shí)際噪聲情況下，做了大量的實(shí)驗(yàn)。結(jié)果表明，本文提出的算法不僅能有效地完成參數(shù)估計(jì)，而且，在低信噪比下，其估計(jì)結(jié)果比其它已有的算法更準(zhǔn)確。
    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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  • 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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出版歷程
  • 收稿日期:  1999-03-15
  • 修回日期:  1999-11-08
  • 刊出日期:  2000-11-19

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