A novel approach is proposed for improving adaptive feedback cancellation using a variable step-size affine projection algorithm(VSS-APA) based on global speech absence probability(GSAP).The variable step-size of the ...A novel approach is proposed for improving adaptive feedback cancellation using a variable step-size affine projection algorithm(VSS-APA) based on global speech absence probability(GSAP).The variable step-size of the proposed VSS-APA is adjusted according to the GSAP of the current frame.The weight vector of the adaptive filter is updated by the probability of the speech absence.The performance measure of acoustic feedback cancellation is evaluated using normalized misalignment.Experimental results demonstrate that the proposed approach has better performance than the normalized least mean square(NLMS) and the constant step-size affine projection algorithms.展开更多
The adaptive algorithm used for echo cancellation(EC) system needs to provide 1) low misadjustment and 2) high convergence rate. The affine projection algorithm(APA) is a better alternative than normalized least mean ...The adaptive algorithm used for echo cancellation(EC) system needs to provide 1) low misadjustment and 2) high convergence rate. The affine projection algorithm(APA) is a better alternative than normalized least mean square(NLMS) algorithm in EC applications where the input signal is highly correlated. Since the APA with a constant step-size has to make compromise between the performance criteria 1) and 2), a variable step-size APA(VSS-APA) provides a more reliable solution. A nonparametric VSS-APA(NPVSS-APA) is proposed by recovering the background noise within the error signal instead of cancelling the a posteriori errors. The most problematic term of its variable step-size formula is the value of background noise power(BNP). The power difference between the desired signal and output signal, which equals the power of error signal statistically, has been considered the BNP estimate in a rough manner. Considering that the error signal consists of background noise and misalignment noise, a precise BNP estimate is achieved by multiplying the rough estimate with a corrective factor. After the analysis on the power ratio of misalignment noise to background noise of APA, the corrective factor is formulated depending on the projection order and the latest value of variable step-size. The new algorithm which does not require any a priori knowledge of EC environment has the advantage of easier controllability in practical application. The simulation results in the EC context indicate the accuracy of the proposed BNP estimate and the more effective behavior of the proposed algorithm compared with other versions of APA class.展开更多
基金Project(2010-0020163)supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education
文摘A novel approach is proposed for improving adaptive feedback cancellation using a variable step-size affine projection algorithm(VSS-APA) based on global speech absence probability(GSAP).The variable step-size of the proposed VSS-APA is adjusted according to the GSAP of the current frame.The weight vector of the adaptive filter is updated by the probability of the speech absence.The performance measure of acoustic feedback cancellation is evaluated using normalized misalignment.Experimental results demonstrate that the proposed approach has better performance than the normalized least mean square(NLMS) and the constant step-size affine projection algorithms.
文摘The adaptive algorithm used for echo cancellation(EC) system needs to provide 1) low misadjustment and 2) high convergence rate. The affine projection algorithm(APA) is a better alternative than normalized least mean square(NLMS) algorithm in EC applications where the input signal is highly correlated. Since the APA with a constant step-size has to make compromise between the performance criteria 1) and 2), a variable step-size APA(VSS-APA) provides a more reliable solution. A nonparametric VSS-APA(NPVSS-APA) is proposed by recovering the background noise within the error signal instead of cancelling the a posteriori errors. The most problematic term of its variable step-size formula is the value of background noise power(BNP). The power difference between the desired signal and output signal, which equals the power of error signal statistically, has been considered the BNP estimate in a rough manner. Considering that the error signal consists of background noise and misalignment noise, a precise BNP estimate is achieved by multiplying the rough estimate with a corrective factor. After the analysis on the power ratio of misalignment noise to background noise of APA, the corrective factor is formulated depending on the projection order and the latest value of variable step-size. The new algorithm which does not require any a priori knowledge of EC environment has the advantage of easier controllability in practical application. The simulation results in the EC context indicate the accuracy of the proposed BNP estimate and the more effective behavior of the proposed algorithm compared with other versions of APA class.
