The traditional multipath matching pursuit (mmp) algorithm generally uses inner product matching criteria (IPMc) to select the best atom for signal reconstruction, and often lose some important information of atoms. T...
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ISBN:
(纸本)9781728172019
The traditional multipath matching pursuit (mmp) algorithm generally uses inner product matching criteria (IPMc) to select the best atom for signal reconstruction, and often lose some important information of atoms. Therefore, any two similar atoms of the observation matrix will affect the process of selecting the best atom for the residual signal, and reduce the quality of signal reconstruction. Using the improved inner product matching criteria (I-IPMc) improves the sensitivity of the mmp algorithm to atom values, optimizes the selection of support sets, and reduces the impact of similar atoms on the matching process. The simulation results show that under the same conditions, the mmp algorithm based on the I-IPMc has better reconstruction quality and higher signal reconstruction probability than the traditional mmp algorithm.
To increase the possibility of choosing the true support of a sparse signal, multipath matching pursuit (mmp) algorithm generates multiple promising candidates of the support set by tree-searching structure. This Lett...
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To increase the possibility of choosing the true support of a sparse signal, multipath matching pursuit (mmp) algorithm generates multiple promising candidates of the support set by tree-searching structure. This Letter proposes the restricted isometry property-based conditions under which at least one candidate of mmp contains the true support set in cases of $l_{2}$l2 and $l_{\infty }$l infinity bounded noises. Comparison with the existing result is also presented.
This Letter presents a sufficient condition under which the multipath matching pursuit (mmp) algorithm recovers sparse signals perfectly in compressive sensing problems. The derived sufficient condition is much more r...
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This Letter presents a sufficient condition under which the multipath matching pursuit (mmp) algorithm recovers sparse signals perfectly in compressive sensing problems. The derived sufficient condition is much more relaxed than the existing one.
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