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于 2020-12-17 发布
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说明:  以稀疏基有离散余弦变换基(DCT)和快速傅立叶变换基(FFT)做为稀疏基,高斯随机矩阵、部分哈达玛矩阵为测量矩阵,L1范数、正交匹配追踪算法(OMP)为重建算法进行压缩感知算法实现。 以f = cos(2*pi/256*t) + sin(2*pi/128*t)做为原信号,取原信号f的20%做为输入进行压缩感知重建。(The sparse basis includes discrete cosine transform (DCT) and fast Fourier transform (FFT) as sparse basis, Gaussian random matrix and partial Hadamard matrix as measurement matrix, L1 norm and orthogonal matching pursuit algorithm (OMP) as reconstruction algorithm. In this paper, the reconstructed signal is reconstructed by using the original sensing signal (sinf * t) as the original input signal (i.e. sinf * t * 2) + 2 * s * t * as the input signal.)

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main.m, 4284 , 2020-12-17

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