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The Separated Speech Signals Combined the Hybrid Adaptive Algorithms by Using Power Spectral Density and Total Harmonic Distortion

机译:分离的语音信号结合功率谱密度和总谐波失真的混合自适应算法

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This paper presents the results of simulation experiments that successfully demonstrate frequency modulation (FM) co-channel speech signals separation by adopting the concepts of power spectral density (PSD) and total harmonic distortion (THD) analyzing adaptive filter combined Fuzzy logic algorithm with the amplitude-locked loop (ALL) separation system in order to improve the signal distortion, co-channel interferences (CCI) of the additive white Gaussian noise (AWGN). The advantage of ALL does not require coding process from modulation, when signals are conveyed by co-channel transmission. In traditional Kalman filter, we find some drawbacks such as low convergence speed and large mean square error (MSE). Hence, we adopted the proposed adaptive algorithm for improving the convergence speed and the MSE value. The improvement simulation results are included separated output signals, the analyses of PSD, THD of the signals, the relation between co-channel signal-to-noise ratio (), and MSE. It is found the performance of Kalman filter combined Fuzzy algorithm better than other algorithms.
机译:本文介绍了仿真实验的结果,通过采用功率谱密度(PSD)和总谐波失真(THD)的概念分析了自适应滤波器与振幅的组合模糊逻辑算法,成功地证明了调频(FM)同信道语音信号的分离锁环(ALL)分离系统,以改善信号失真,加性高斯白噪声(AWGN)的同频干扰(CCI)。当通过同信道传输来传送信号时,ALL的优点不需要调制的编码过程。在传统的卡尔曼滤波器中,我们发现了一些缺点,例如收敛速度低和均方根误差(MSE)大。因此,我们采用提出的自适应算法来提高收敛速度和MSE值。改进的仿真结果包括分离的输出信号,PSD的分析,信号的THD,同信道信噪比()和MSE之间的关系。发现结合模糊算法的卡尔曼滤波器的性能优于其他算法。

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