A Nonparametric Approach for Multicomponent AM–FM Signal Analysis

被引:0
作者
Abhay Upadhyay
Manish Sharma
Ram Bilas Pachori
Rajeev Sharma
机构
[1] Bundelkhand University,Department of Electronics and Communication Engineering, Institute of Engineering and Technology
[2] Institute of Infrastructure Technology Research and Management,School of Electrical Engineering
[3] Indian Institute of Technology Indore,Discipline of Electrical Engineering
[4] Birla Institute of Technology Mesra,Department of Electronics and Communication Engineering
来源
Circuits, Systems, and Signal Processing | 2020年 / 39卷
关键词
Variational mode decomposition method; Discrete energy separation algorithm; Amplitude modulated and frequency modulated signal model; Non-stationary signal analysis;
D O I
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中图分类号
学科分类号
摘要
In this paper, a novel method is presented to analyze the amplitude modulated and frequency modulated (AM–FM) multicomponent signals using a combination of the variational mode decomposition (VMD) and the discrete energy separation algorithm (DESA). In the presented method, firstly, a multicomponent signal is decomposed using VMD method applied in an iterative way. In order to separate the monocomponent signals from multicomponent signal, a suitable convergence criterion is developed based on the values of estimated center frequencies (CF¯\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{\text {CF}}$$\end{document}) and standard deviations (σCF\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sigma _{\text {CF}}$$\end{document}) of the decomposed components. Further, the estimation of amplitude envelope and the instantaneous frequency functions of monocomponent AM–FM signals has been carried out by employing DESA. Moreover, the proposed method is also applied on the synthetic AM–FM signal and speech signals to evaluate its performance. Furthermore, its performance is also compared with the Fourier–Bessel series expansion-based DESA, empirical wavelet transform-based DESA, and iterative eigenvalue decomposition-based DESA methods. The performance of the proposed method is compared with the other methods in terms of mean square error between actual and estimated amplitude envelopes (MSEAE\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text {MSE}_{\text {AE}}}$$\end{document}), mean square error between actual and estimated instantaneous frequencies (MSEIF\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text {MSE}_{\text {IF}}}$$\end{document}) for synthetic signal. The COSH distance measure is used as a performance measure for speech signals. It is found that the proposed method gives better results in terms of performance measures in several cases.
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页码:6316 / 6357
页数:41
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