基于Mittag-Leffler函数的模拟滤波器

IF 3.6 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Signal Processing Pub Date : 2025-08-01 Epub Date: 2025-02-23 DOI:10.1016/j.sigpro.2025.109953
Anis Allagui , Ahmed S. Elwakil , Julia Nako , Costas Psychalinos
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引用次数: 0

摘要

基于Mittag-Leffler函数Eα,β(z)的单参数或双参数形式,将其参数转置到频域,提出并研究了一类新的滤波器(以下称为Mittag-Leffler滤波器);即z =−s =−jω。这些滤波器的一个独特特征是它们的脉冲响应是一个类高斯(类delta)的变形和延迟脉冲函数,我们使用H - Fox函数推导出精确的表达式。我们还研究了这类滤波器的频率响应,得到了其传递函数的低阶、可实现的整阶近似。然后采用二阶曲线拟合近似,利用现场可编程模拟阵列平台进行实验结果验证理论。
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Analog filters based on the Mittag-Leffler functions
We propose and study a new class of filters (named hereinafter the Mittag-Leffler filters) based on the Mittag-Leffler function Eα,β(z) in its single-parameter or double-parameter forms by transposing its argument to the frequency-domain; i.e. z=s=jω. A unique feature of these filters is that their impulse response is a Gaussian-like (delta-like) deformed and delayed impulse function for which we derive exact expressions using the HFox function. We also study the frequency response of this class of filters and obtain lower-order, realizable integer-order approximations of its transfer functions. A second-order curve-fitting approximation is then used to perform experimental results using a Field Programmable Analog Array platform to verify the theory.
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来源期刊
Signal Processing
Signal Processing 工程技术-工程:电子与电气
CiteScore
9.20
自引率
9.10%
发文量
309
审稿时长
41 days
期刊介绍: Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.
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