The modeling error shown by the difference of the characteristics between the secondary paths and its models will cause the improper adaptation of the filtered-x LMS adaptive filters in active noise control systems. It is necessary to use the on-line modeling systems for avoiding such improper adaptation, and several on-line modeling methods have been proposed hitherto. Especially, one of them is very useful because the method can identify the primary and the secondary path characteristics without using any additional signal. This method, however, will not always provide the proper modeling results, and the conditions for optimizing the results have not been discussed yet. This paper investigates the conditions for optimal on-line modeling of the primary and the secondary path characteristics without using any additional signal for identification. Theoretical analysis produces the specific conditions which the noise control adaptive filter should satisfy. Those results of the theoretical consideration are confirmed by the computer simulation in which the impulse responses measured in a vehicle cabin are used.

抄録全体を表示

An adaptive enhancement algorithm of signal disturbed by the impulse noise and the white Gaussian noise is proposed in this paper. If the strong dependence between signal enhancement and needed-parameter estimation exists in an algorithm, it is difficult to reduce a large bias occurring in the first estimation. To weaken their relationship, it is considered to introduce a total least squares (TLS) algorithm which estimates model parameters directly from disturbed signals. However, the TLS estimation accuracy is dramatically deteriorated by the impulse noise, even if the TLS estimation accuracy is held to the non-Gaussian noise in some degree. Hence, we ensure the robustness of the algorithm by replacing a high amplitude signal with an estimated value based on a likelihood ratio test. Using these signals, we develop an algorithm based on the TLS and the EM algorithm for enhancing the disturbed signal. We also show the effectiveness of the proposed algorithm through computer simulations.

抄録全体を表示

The convergence characteristics of the feedforward active noise control system with the filtered-x LMS or multiple error filtered-x LMS algorithm are degraded by the transfer functions from the secondary sources to the error sensors (secondary paths). The possible methods to improve the convergence characteristics of the active noise control system with the LMS algorithm by reducing the effect of the secondary paths are discussed in this paper. In the first method, an index in the case of multiple secondary sources and error sensors to evaluate are introduced whether their positions are good or not before performing the cancellation. In the second method in which the number of secondary sources is increased, it is shown that the LMS adaptive algorithm performs well. In the third method with the use of the inverse filters of the secondary paths, the adaptive LMS algorithm is formulated and it is shown from the result of with a simulation using a transfer function measured in a room with a reverberation time of 0.5 s that this method is practically effective.

抄録全体を表示

An active absorber of sound using an adaptive algorithm is studied. To realize an active sound absorber, the incident wave on the absorber which is usually mixed with the reflected wave, must be known. In conventional methods, in order to separate the incident wave from the reflected wave using two microphones, the delay time during which the sound propagates between the two microphones must be precisely known and the two microphones must have exactly the same sensitivity. We propose two methods using adaptive processing, which do not require such preprocessing for extracting the incident wave: an off-line method using an impulse as a learning signal and an on-line method using sound intensity control. The off-line method, in which the optimum conditions are learned efficiently, yields sound absorption coefficients of more than 99% at low requencies. In the on-line method, which do not require such learning signals as the off-line method, sound absorption coefficients of more than 95% can be realized at low frequencies.

抄録全体を表示

The convergence speed of a multiple input adaptive filtering system is often very slow with the conventional NLMS algorithm. This paper describes a new projection algorithm for filtered-x systems with multiple input signals, secondary sources and control points. This algorithm increase the convergence speed of multiple input adaptive filtering systems by eliminating the cross-channel correlation as well as the auto correlation. However, the computational complexity for the proposed algorithm remains only as much as that of the NLMS algorithm. Computer simulation shows twice faster convergence speed than that of the NLMS algorithm, with only a 1.2 fold increase in computation.

抄録全体を表示