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A Fast Affine Projection Algorithm Based on Matching Pursuit in Adaptive Noise Cancellation for Speech Enhancement

机译:一种基于匹配追踪的自适应快速仿射投影算法   用于语音增强的噪声消除

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摘要

In many application of noise cancellation, the changes in signalcharacteristics could be quite fast. This requires the utilization of adaptivealgorithms, which converge rapidly. Least Mean Squares (LMS) adaptive filtershave been used in a wide range of signal processing application. The RecursiveLeast Squares (RLS) algorithm has established itself as the "ultimate" adaptivefiltering algorithm in the sense that it is the adaptive filter exhibiting thebest convergence behavior. Unfortunately, practical implementations of thealgorithm are often associated with high computational complexity and/or poornumerical properties. Recently adaptive filtering was presented that was basedon Matching Pursuits, have a nice tradeoff between complexity and theconvergence speed. This paper describes a new approach for noise cancellationin speech enhancement using the new adaptive filtering algorithm named fastaffine projection algorithm (FAPA). The simulation results demonstrate the goodperformance of the FAPA in attenuating the noise.
机译:在噪声消除的许多应用中,信号特性的变化可能非常快。这需要利用自适应算法,这些算法迅速收敛。最小均方(LMS)自适应滤波器已在广泛的信号处理应用中使用。递归最小二乘(RLS)算法已将自身确立为“最终”自适应滤波算法,因为它是表现出最佳收敛行为的自适应滤波器。不幸的是,算法的实际实现常常与较高的计算复杂度和/或较差的数值特性相关联。最近提出了基于匹配追踪的自适应滤波,在复杂度和收敛速度之间进行了很好的权衡。本文介绍了一种新的用于语音增强中的噪声消除的方法,该方法使用了名为“快速仿射投影算法”(FAPA)的新型自适应滤波算法。仿真结果证明了FAPA在衰减噪声方面的良好性能。

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