Parameter Estimation Method Using Volterra Kernels for Nonlinear IIR Filters

被引:1
|
作者
Iwai, Kenta [1 ]
Kajikawa, Yoshinobu [1 ]
机构
[1] Kansai Univ, Fac Engn Sci, Suita, Osaka 9108507, Japan
关键词
parameter estimation method for loudspeakers; nonlinear IIR filter; nonlinear distortion; loudspeaker system; Volterra filter; LOUDSPEAKER SYSTEM;
D O I
10.1587/transfun.E97.A.2189
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose a parameter estimation method using Volterra kernels for the nonlinear IIR filters, which are used for the linearization of closed-box loudspeaker systems. The nonlinear IIR filter, which originates from a mirror filter, employs nonlinear parameters of the loudspeaker system. Hence, it is very important to realize an appropriate estimation method for the nonlinear parameters to increase the compensation ability of nonlinear distortions. However, it is difficult to obtain exact nonlinear parameters using the conventional parameter estimation method for nonlinear IIR filter, which uses the displacement characteristic of the diaphragm. The conventional method has two problems. First, it requires the displacement characteristic of the diaphragm but it is difficult to measure such tiny displacements. Moreover, a laser displacement gauge is required as an extra measurement instrument. Second, it has a limitation in the excitation signal used to measure the displacement of the diaphragm. On the other hand, in the proposed estimation method for nonlinear IIR filter, the parameters are updated using simulated annealing (SA) according to the cost function that represents the amount of compensation and these procedures are repeated until a given iteration count. The amount of compensation is calculated through computer simulation in which Volterra kernels of a target loudspeaker system is utilized as the loudspeaker model and then the loudspeaker model is compensated by the nonlinear IIR filter with the present parameters. Hence, the proposed method requires only an ordinary microphone and can utilize any excitation signal to estimate the nonlinear parameters. Some experimental results demonstrate that the proposed method can estimate the parameters more accurately than the conventional estimation method.
引用
收藏
页码:2189 / 2199
页数:11
相关论文
共 50 条
  • [1] Sparsity-Aware Estimation of Nonlinear Volterra Kernels
    Kekatos, Vassilis
    Angelosante, Daniele
    Giannakis, Georgios B.
    2009 3RD IEEE INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING (CAMSAP), 2009, : 129 - 132
  • [2] Sparsity-Aware Estimation of Nonlinear Volterra Kernels
    Kekatos, Vassilis
    Angelosante, Daniele
    Giannakis, Georgios B.
    2009 3RD IEEE INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING (CAMSAP 2009), 2009, : 129 - 132
  • [3] Design of IIR Filters With Bayesian Model Selection and Parameter Estimation
    Botts, Jonathan
    Escolano, Jose
    Xiang, Ning
    IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2013, 21 (03): : 669 - 674
  • [4] Nonlinear parameter estimation in rotor-bearing system using volterra series and method of harmonic probing
    Chatterjee, A
    Vyas, NS
    JOURNAL OF VIBRATION AND ACOUSTICS-TRANSACTIONS OF THE ASME, 2003, 125 (03): : 299 - 306
  • [5] Parameter estimation using Volterra series
    Hsieh, MCM
    Rayner, PJW
    PROCEEDINGS OF THE 1998 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-6, 1998, : 2341 - 2344
  • [6] Use of Meixner functions in estimation of Volterra kernels of nonlinear systems with delay
    Asyali, MH
    Juusola, M
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2005, 52 (02) : 229 - 237
  • [7] A MAP estimation algorithm using IIR recursive filters
    Sanches, JM
    Marques, JS
    ENERGY MINIMIZATION METHODS IN COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS, 2003, 2683 : 436 - 449
  • [8] A Parameter Estimation Method using Nonlinear Least Squares
    Oh, Suna
    Song, Jongwoo
    KOREAN JOURNAL OF APPLIED STATISTICS, 2013, 26 (03) : 431 - 440
  • [9] Identification and parameter estimation of cubic nonlinear damping using harmonic probing and volterra series
    Chatterjee, Animesh
    Chintha, Hari Prasad
    INTERNATIONAL JOURNAL OF NON-LINEAR MECHANICS, 2020, 125
  • [10] Nonlinear Stochastic System Identification of Skin Using Volterra Kernels
    Chen, Yi
    Hunter, Ian W.
    ANNALS OF BIOMEDICAL ENGINEERING, 2013, 41 (04) : 847 - 862