Compressive sensing algorithms for recovery of sparse and low rank signals
Many natural signals are atomic, i.e., the signals may be represented in some low dimensional space due to their inherent structure. Two most common atomic structures are sparsity and low rank. A sparse signal (vector/matrix) has very few nonzero entries. A low rank matrix has very small rank in c...
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格式: | Thesis-Master by Research |
語言: | English |
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Nanyang Technological University
2021
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在線閱讀: | https://hdl.handle.net/10356/145980 |
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機構: | Nanyang Technological University |
語言: | English |