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电子与信息学报 2012, Vol. 34 Issue (4) :838-843    DOI: 10.3724/SP.J.1146.2011.00620
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基于混沌压缩感知的稀疏时变信号在线估计
陈胜垚    席峰    刘中**
南京理工大学电子工程系  南京  210094
Online Estimation of Sparse Time-varying Signals with Chaotic Compressive Sensing
Chen Sheng-yao    Xi Feng    Liu Zhong*
Department of Electronic Engineering, Nanjing University of Science and Technology, Nanjing 210094, China

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摘要 混沌压缩感知是一种利用混沌系统实现非线性测量的压缩感知理论。针对稀疏时变信号的混沌压缩感知,该文提出稀疏时变信号的在线估计架构,构建一种递归最小二乘准则下的稀疏约束目标函数;通过利用迭代加权非线性最小二乘算法求解目标函数最小化问题,实现稀疏时变信号的参数估计。以Henon混沌系统为例仿真分析了频域时变稀疏信号的估计性能,数值模拟证明了该方法的有效性。
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陈胜垚
席峰
刘中
关键词混沌压缩感知   脉冲同步   稀疏   递归最小二乘(RLS)     
Abstract: Chaotic Compressive Sensing (ChaCS) is a nonlinear compressive sensing approach using chaos systems. This paper extends the ChaCS to perform the online estimation of sparse time-varying signals. An online estimation structure is proposed and a sparsity-constrained recursive least-squares objective function is formulated. The sparse time-varying signals are estimated through iterative reweighted nonlinear least-square algorithm by minimizing the objective function. The Henon system is taken as examples to expose the estimation performance of frequency sparse time-varying signals. Numerical simulations illustrate the effectiveness of the proposed method.
KeywordsChaotic Compressive Sensing (ChaCS)   Impulsive synchronization   Sparsity   Recursive Least Squares (RLS)     
Received 2011-06-26;
本文基金:

国家自然科学基金(60971090, 61171166, 61101193)资助课题

通讯作者: 刘中     Email: eezliu@mail.njust.edu.cn
引用本文:   
陈胜垚, 席峰, 刘中.基于混沌压缩感知的稀疏时变信号在线估计[J]  电子与信息学报, 2012,V34(4): 838-843
Chen Sheng-Yao, Xi Feng, Liu Zhong.Online Estimation of Sparse Time-varying Signals with Chaotic Compressive Sensing[J]  , 2012,V34(4): 838-843
链接本文:  
http://jeit.ie.ac.cn/CN/10.3724/SP.J.1146.2011.00620      或     http://jeit.ie.ac.cn/CN/Y2012/V34/I4/838
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