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中文摘要：
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。
英文摘要：
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.
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