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Adaptive fractional Fourier domain filtering

机译:自适应分数阶傅里叶域滤波

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摘要

A novel adaptive filtering scheme based on fractional Fourier transform (FrFT) is introduced and characterized. As a generalization of the ordinary Fourier transform, FrFT is a powerful analysis tool to describe signals with chirp-type components. We show that in case of linear frequency modulated (LFM) signals fractional Fourier domain adaptive filtering schemes provide less error and faster convergence. The adaptation algorithm is employed in an active noise control system application with various LFM signals and a real multi-component signal. Simulation results present that the adaptation performance in FrFT-domain adaptive filtering is superior compared to time-domain adaptation.
机译:介绍并描述了一种基于分数阶傅里叶变换(FrFT)的自适应滤波方案。作为普通傅立叶变换的概括,FrFT是一种功能强大的分析工具,用于描述具有chi型分量的信号。我们表明,在线性调频(LFM)信号的情况下,分数阶傅里叶域自适应滤波方案可提供更少的误差和更快的收敛速度。自适应算法用于具有各种LFM信号和实际多分量信号的有源噪声控制系统应用中。仿真结果表明,FrFT域自适应滤波的自适应性能优于时域自适应。

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