利用勒让德多项式设计多项式图滤波器

C. Tseng, Su-Ling Lee
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引用次数: 0

摘要

多项式图滤波器(PGF)是处理从各种复杂网络中捕获的不规则数据的重要工具,因此本文对PGF的设计进行了研究。首先,简要回顾了勒让德多项式,并描述了图信号处理(GSP)的基础。其次,提出了基于勒让德多项式的PGF设计。推导了低通、带通和高通滤波器的滤波器系数的闭式解。第三,研究了一种基于Legendre多项式递归关系的PGF的有效实现结构。最后,通过对传感器网络数据的信号去噪实验,验证了PGF方法在提高信噪比方面优于传统的基于平滑度的方法。
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Polynomial Graph Filter Design Using Legendre Polynomials
Polynomial graph filter (PGF) is an important tool for processing the irregular data captured from various complex networks, so the design of PGF is studied in this paper. First, Legendre polynomials are briefly reviewed and the basics of graph signal processing (GSP) are described. Second, the PGF design using Legendre polynomials is presented. The closed-form solution of filter coefficients is derived for lowpass, bandpass and highpass filters. Third, an efficient implementation structure of PGF based on recurrence relation of Legendre polynomials is investigated. Finally, the signal denoising application of sensor network data is demonstrated to show that the PGF method has better performance than the conventional smoothness-based method in term of the improvement of signal to noise ratio.
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