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Gaussian measurement matrices, for n=100 nodes, different RIP constants, and different degrees of nodes.
zero-mean Gaussian entries are known to be appropriate measurement matrices for compressed sensing.
Table 5 Numerical results with Gaussian measurement matrices for noise-free data.
The first step of reconstructing multi-target images is to build the measurement matrices for each target.
We fix the original images and repeat the above experiment 20 times, each time with independently generated measurement matrices for all the three algorithms.
After random observation, the measurement matrices for the targets are different from each other; thus, the images are reconstructed separately using CS algorithms.
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The truncated measurement matrix for y i, Φ i.
A random Gaussian matrix was used as the measurement matrix for compressed UWB radar data acquired.
The Gaussian random measurement matrix is more consistent with respect to the design requirement of the measurement matrix for CS.
The class of matrices is usually selected as the measurement matrix for compressive data gathering in WSNs.
The steps of the ABC algorithm for optimizing the measurement matrix for the recovery algorithm are as follows.
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