Papers by Keyword: LMS Algorithm

Abstract: With the progress of communication technology,people pay more and more attention to SNR of speech signal.Therefore,speech enhancement under unknown noise is becoming more and more necessary.Currently,the application of speech enhancement in life can be divided into:harmonic enhancement method,based on the parameter estimation of speech synthesis,and based on adaptive noise cancellation method.In this paper,adaptive noise cancellation method is discussed.

Abstract: LMS algorithm is a kind of classic adaptive algorithms. Although it has the virtue of simple operation, it also shows the defects of relatively slow convergence and big steady state errors in low SNR. To remedy these defects, this paper put forward a new variable steps adaptive LMS algorithm. In the transient state, the learning rate increases slowly with the iteration times which accelerate the convergence rate of LMS algorithm. In the steady state, the learning rate decreases gradually with the iteration times which guarantee the convergence accuracy of LMS algorithm. After this improved algorithm is applied in the design of adaptive wavetrap, the simulation results show that it can not only effectively ease up the conflicts between convergence rates and steady state errors, but also improve the performance of wavetrap in real-time trapping.

Abstract: MAI influence, using a low computational complexity variable step size LMS algorithm based on the traditional algorithm to find the optimal weight on, and make estimates for the magnitude, thereby offsetting the presence of MAI and estimates for spread spectrum communication system struck a balance between the consideration to be paid for MAI. The improved algorithm reduces the computational complexity of each level, the simulation results also show that the method has better performance.