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Improved NSAF Algorithms with Variable Control Parameter Against Impulsive Noises

机译:利用可变控制参数改进了NSAF算法,防止脉冲噪声

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Some improved normalized subband adaptive filter algorithms derived from nonlinear cost functions, such as the logarithmic function and the arctangent function, have shown splendid robustness against the impulsive noises. However, due to the usage of the constant control parameter in their cost functions, these algorithms need to make a balance between the steady-state error and the convergence rate, especially when the unknown impulse response changes suddenly. For settling this trade-off issue, a way of obtaining the variable control parameter (VCP) recursively is constructed by an exponential function in this paper. In the contexts of system identification and acoustic echo cancellation, simulation results testified the improved performance of these proposed VCP algorithms in terms of the convergence rate, steady-state error, and tracking capability.
机译:一些改进的归一化子带自适应滤波器算法导出的非线性成本函数,例如对数函数和方形功能,对脉冲噪声表示出色的鲁棒性。然而,由于使用恒定控制参数的成本函数,这些算法需要在稳态误差和收敛速度之间进行平衡,尤其是当未知的脉冲响应突然发生变化时。为了解决此权衡问题,通过本文的指数函数构建了获得可变控制参数(VCP)的方法。在系统识别和声学回声消除的背景下,仿真结果证明了这些提出的VCP算法在收敛速率,稳态误差和跟踪能力方面的改进性能。

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