基于压缩感知的稀疏信号测量估计我要分享

Sparse signal measurement estimation based on Comp

matlab 基于 压缩 感知 稀疏 信号 估计

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开发平台: matlab

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代码描述

中文说明:应用背景这个例子涉及的信号在频域稀疏因此,随机测量的时域。此代码演示了使用稀疏信号的压缩传感在时域。该信号由一个超宽带(超宽带)脉冲组成在时域。该信号是稀疏的时间域,因此频率域随机测量。关键技术这里L1魔术的matlab代码是用来恢复为使用l0范数最小化L1范数凸松弛优化技术的信号。


English Description:

Application backgroundThis example deals with the signal sparse in Frequency domain and hence random measurements are taken in Time domain. This code demonstrates the compressive sensing using a sparse signal in Time domain. The signal consists of a UWB (Ultra Wide Band) pulse in time domain. The signal is sparse in Time domain and therefore K random measurements are taken in Frequency domain.Key TechnologyHere l1-magic Matlab code is used to recover the signal which is an optimization technique for minimizing l1- norm using l0-norm with convex relaxation.


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