Maximum Total Fractional-Order Correntropy Adaptive Filtering Algorithm for Parameter Estimation Under Impulsive Noises

IF 1.8 3区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Jiali Yang, Qiang Zhang, Yongjiang Luo, Yuhang Bai
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Abstract

As an adaptive finite impulse response filtering algorithm, the maximum total correntropy (MTC) algorithm plays an important role in parameter estimation of the errors-in-variables model where both input and output signals are contaminated with impulsive noises. However, the MTC algorithm is difficult to obtain a sufficiently high estimation accuracy under impulsive noises because the MTC cost function contains second-order moments of the error signal and its first-order gradient is susceptible to large outliers in the input noise. In this paper, a maximum total fractional-order correntropy (MTFOC) cost function is proposed and then a fractional-order gradient based MTFOC adaptive filtering algorithm is developed to improve the estimation accuracy of MTC. Moreover, the local stability and computational complexity of the proposed algorithm are analyzed. Simulation results indicate that the estimation accuracy and robustness of the MTFOC algorithm are superior to previous algorithms in both Gaussian mixture noise environments and \(\alpha \)-stable distribution noise environments.

Abstract Image

用于脉冲噪声下参数估计的最大总分阶熵自适应滤波算法
作为一种自适应有限脉冲响应滤波算法,最大总熵算法(MTC)在输入和输出信号都受到脉冲噪声污染的变量误差模型参数估计中发挥着重要作用。然而,由于 MTC 成本函数包含误差信号的二阶矩,且其一阶梯度易受输入噪声中较大异常值的影响,因此 MTC 算法在脉冲噪声下难以获得足够高的估计精度。本文提出了一种最大总分数阶熵 (MTFOC) 成本函数,然后开发了一种基于分数阶梯度的 MTFOC 自适应滤波算法,以提高 MTC 的估计精度。此外,还分析了所提算法的局部稳定性和计算复杂度。仿真结果表明,在高斯混合噪声环境和(α)稳定分布噪声环境下,MTFOC算法的估计精度和鲁棒性都优于之前的算法。
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来源期刊
Circuits, Systems and Signal Processing
Circuits, Systems and Signal Processing 工程技术-工程:电子与电气
CiteScore
4.80
自引率
13.00%
发文量
321
审稿时长
4.6 months
期刊介绍: Rapid developments in the analog and digital processing of signals for communication, control, and computer systems have made the theory of electrical circuits and signal processing a burgeoning area of research and design. The aim of Circuits, Systems, and Signal Processing (CSSP) is to help meet the needs of outlets for significant research papers and state-of-the-art review articles in the area. The scope of the journal is broad, ranging from mathematical foundations to practical engineering design. It encompasses, but is not limited to, such topics as linear and nonlinear networks, distributed circuits and systems, multi-dimensional signals and systems, analog filters and signal processing, digital filters and signal processing, statistical signal processing, multimedia, computer aided design, graph theory, neural systems, communication circuits and systems, and VLSI signal processing. The Editorial Board is international, and papers are welcome from throughout the world. The journal is devoted primarily to research papers, but survey, expository, and tutorial papers are also published. Circuits, Systems, and Signal Processing (CSSP) is published twelve times annually.
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