Adaptive Analysis of Sparse Signals

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Adaptive Analysis of Sparse Signals

机译：稀疏信号的自适应分析

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摘要

We introduce an adaptive method for analysis of sparse signals using bandpass filters obtained by modulated Slepian sequences. Similar to the recently introduced empirical wavelet transform, the proposed method decomposes a signal into different modes which corresponds to segmenting the Fourier spectrum and filtering the existing support. The simulations illustrate the correct signal decomposition for a multiband signal which has a sparse spectrum. The proposed method can be used as an alternative to empirical wavelet transform.

机译：我们介绍了使用通过调制绞线序列所获得的带通滤波器来分析稀疏信号的自适应方法。类似于最近引入的经验小波变换，所提出的方法将信号分解成不同的模式，其对应于分割傅立叶频谱并过滤现有支持。该模拟说明了具有稀疏频谱的多频带信号的正确信号分解。所提出的方法可以用作经验小波变换的替代。

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来源
《WSEAS Transactions on Signal Processing》 |2018年第1期|共5页
作者
SEDA SENAY;
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作者单位

New Mexico Institute of Mining and Technology Department of Electrical Engineering;

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原文格式 PDF
正文语种 eng
中图分类声学;
关键词
Slepian sequences; Multiband signals; Filter banks; Orthogonal bases; Empirical wavelet transform;

机译：绞线序列;多频带信号;过滤银行;正交基础;经验小波变换;

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1. Adaptive Fisher method detects dense and sparse signals in association analysis of SNV sets [J] . Xiaoyu Cai, Lo-Bin Chang, Jordan Potter, BMC Medical Genomics . 2020,第5期

机译：自适应Fisher方法检测SNV集的关联分析中的密集和稀疏信号
2. Robust Reconstruction of Block Sparse Signals from Adaptively One-Bit Measurements [J] . Hou Jingyao, Wang Jianjun, Zhang Feng, Chinese Journal of Electronics . 2020,第5期

机译：从自适应单位测量的块稀疏信号的强大重建
3. Robust Reconstruction of Block Sparse Signals from Adaptively One-Bit Measurements [J] . HOU Jingyao, WANG Jianjun, ZHANG Feng, 电子学报（英文版） . 2020,第005期

机译：自适应一位测量对块稀疏信号的鲁棒重构
4. Compressive sensing of block-sparse signals recovery based on sparsity adaptive regularized orthogonal matching pursuit algorithm [C] . Zhao Qiang, Wang Jinkuan, Han Yinghua, 2012 IEEE Fifth International Conference on Advanced Computational Intelligence. . 2012

机译：基于稀疏自适应正则正交匹配追踪算法的块稀疏信号恢复压缩感知
5. Detection and classification of non-stationary signals using sparse representations in adaptive dictionaries. [D] . Moody, Daniela I. 2012

机译：使用自适应词典中的稀疏表示来检测和分类非平稳信号。
6. Adaptive Fisher method detects dense and sparse signals in association analysis of SNV sets [O] . Xiaoyu Cai, Lo-Bin Chang, Jordan Potter, 2020

机译：自适应Fisher方法在SNV集关联分析中检测密集和稀疏信号
7. Sparseness Theorems and Sparse Representation of Signals (Nonlinear Analysis and Convex Analysis) [O] . Georgiev Pando, Cichocki Andrzej 2004

机译：信号的稀疏定理和稀疏表示（非线性分析和凸分析）

Adaptive Analysis of Sparse Signals

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