著者
Kimiko MOTONAKA Tomoya KOSEKI Yoshinobu KAJIKAWA Seiji MIYOSHI
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (ISSN:09168508)
巻号頁・発行日
pp.2021EAP1013, (Released:2021-06-01)
被引用文献数
2

The Volterra filter is one of the digital filters that can describe nonlinearity. In this paper, we analyze the dynamic behaviors of an adaptive signal-processing system including the Volterra filter by a statistical-mechanical method. On the basis of the self-averaging property that holds when the tapped delay line is assumed to be infinitely long, we derive simultaneous differential equations in a deterministic and closed form, which describe the behaviors of macroscopic variables. We obtain the exact solution by solving the equations analytically. In addition, the validity of the theory derived is confirmed by comparison with numerical simulations.
著者
Seiji MIYOSHI Yoshinobu KAJIKAWA
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences (ISSN:09168508)
巻号頁・発行日
vol.E101-A, no.12, pp.2419-2433, 2018-12-01
被引用文献数
5

We analyze the behaviors of the FXLMS algorithm using a statistical-mechanical method. The cross-correlation between a primary path and an adaptive filter and the autocorrelation of the adaptive filter are treated as macroscopic variables. We obtain simultaneous differential equations that describe the dynamical behaviors of the macroscopic variables under the condition that the tapped-delay line is sufficiently long. The obtained equations are deterministic and closed-form. We analytically solve the equations to obtain the correlations and finally compute the mean-square error. The obtained theory can quantitatively predict the behaviors of computer simulations including the cases of both not only white but also nonwhite reference signals. The theory also gives the upper limit of the step size in the FXLMS algorithm.
著者
Kenta IWAI Yoshinobu KAJIKAWA
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences (ISSN:09168508)
巻号頁・発行日
vol.E97-A, no.11, pp.2189-2199, 2014-11-01

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.
著者
Nobuhiro MIYAZAKI Yoshinobu KAJIKAWA
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences (ISSN:09168508)
巻号頁・発行日
vol.E97-A, no.10, pp.2021-2032, 2014-10-01

In this paper, we propose a modified-error adaptive feedback active noise control (ANC) system using a linear prediction filter. The proposed ANC system is advantageous in terms of the rate of convergence, while maintaining stability, because it can reduce narrowband noise while suppressing disturbance, including wideband components. The estimation accuracy of the noise control filter in the conventional system is degraded because the disturbance corrupts the input signal to the noise control filter. A solution of this problem is to utilize a linear prediction filter. The linear prediction filter is utilized for the modified-error feedback ANC system to suppress the wideband disturbance because the linear prediction filter can separate narrowband and wideband noise. Suppressing wideband noise is important for the head-mounted ANC system we have already proposed for reducing the noise from a magnetic resonance imaging (MRI) device because the error microphones are located near the user's ears and the user's voice consequently corrupts the input signal to the noise control filter. Some simulation and experimental results obtained using a digital signal processor (DSP) demonstrate that the proposed feedback ANC system is superior to a conventional feedback ANC system in terms of the estimation accuracy and the rate of convergence of the noise control filter.