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Development of an Adaptive IIR Filter Based on Modified Robust Mixed-Norm Algorithm for Adaptive Noise Cancellation

机译:基于改进鲁棒混合范数算法的自适应IIR滤波器的研制

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Noise cancellation is one of the most important applications of adaptive filters. The employment of adaptive filtering in most digital signal processing tasks is currently an area of growing interest as adaptive filters, due to their dynamic nature, perform better than the traditional filters in compensating for random noise in their environment. However, the compensation for impulsive interference or noise is desired since most adaptive algorithms earlier proposed modelled noise as a random process of the White Gaussian distribution. A modified robust mixed-norm (MRMN) algorithm recently proposed to compensate for impulsive interference has been found to be hardware efficient, however the MRMN algorithm has only been tested on adaptive FIR system identification task. In this paper, an adaptive IIR filter based on MRMN adaptive algorithm is proposed and tested for noise cancellation task. The developed filter structure was modelled and simulated in MATLAB environment. The results obtained showed that the MRMN algorithm does in fact compensate for the presence of impulsive interference, however, at a higher computational complexity relative to the LMS algorithm.
机译:噪声消除是自适应滤波器的最重要应用之一。当前,在大多数数字信号处理任务中采用自适应滤波是一个越来越引起人们关注的领域,因为自适应滤波器由于其动态特性,在补偿其环境中的随机噪声方面要比传统滤波器表现更好。然而,由于大多数自适应算法较早提出将噪声建模为白高斯分布的随机过程,因此需要对脉冲干扰或噪声进行补偿。已经发现,最近提出的用于补偿脉冲干扰的改进的鲁棒混合范数(MRMN)算法具有较高的硬件效率,但是该MRMN算法仅在自适应FIR系统识别任务上进行了测试。提出了一种基于MRMN自适应算法的自适应IIR滤波器,并进行了噪声消除任务的测试。在MATLAB环境中对开发的滤波器结构进行建模和仿真。获得的结果表明,MRMN算法实际上补偿了脉冲干扰的存在,但是,相对于LMS算法,其计算复杂度更高。

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