Abstract
Impulsive noises are widely existing in various systems like noise cancellation system and wireless communication systems, where adaptive filtering (AF) is always employed to identify specific systems. Additionally, the impulsive noises will affect the performance for estimating these systems, resulting in slow convergence or worse identification accuracy. In this paper, a diffusion maximum correntropy criterion (DMCC) algorithm with adaption kernel width is proposed, denoting as DMCC <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">adapt</sub> algorithm, to find out a solution for dynamically choosing the kernel width. The DMCC <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">adapt</sub> algorithm chooses small kernel width at initial stage to improve its convergence speed rate, and uses large kernel width at completion stage to reduce its steady-state error. To render the proposed DMCC <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">adapt</sub> algorithm suitable for sparse system identifications, the DMCC <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">adapt</sub> algorithm based on proportional coefficient adjustment is realized and named as diffusion proportional maximum correntropy criterion (DPMCC <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">adapt</sub> ). The theoretical analysis and simulation results are presented to show that the DPMCC <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">adapt</sub> and DMCC <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">adapt</sub> algorithms have better convergence than the traditional diffusion AF algorithms under impulse noise and sparse systems.
Highlights
Wireless sensor network (WSN) has been widely considered in the use of bridge detections, positioning, area monitoring, and air pollution monitoring
The impulsive noise is common in many practical applications which happens in fan, radar and electromagnetic environments such as electromagnetic interferences [6]– [8]
The theoretical analysis and simulation results are presented to show that the DPMCCadapt and DMCCadapt algorithms have better convergence performance than the traditional diffusion adaptive filtering (AF) algorithms under impulse noise and sparse systems
Summary
This work was supported in part by the National Key Research and Development Program of China under Grant 2016YFE111100, in part by the Key Research and Development Program of Heilongjiang under Grant GX17A016, in part by the Science and Technology Innovative Talents Foundation of Harbin under Grant 2016RAXXJ044, in part by the Opening Fund of Acoustics Science and Technology Laboratory under Grant SSKF2016001, in part by the Natural Science Foundation of Heilongjiang Province, China, under Grant F2017004, and in part by the China Postdoctoral Science Foundation under Grant 2017M620918 and Grant 2019T120134.
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