Name
Abstract | ||
|---|---|---|
This letter introduces a novel algorithm to construct sensing and measurement dictionaries in compressive sensing using alternating projection method. The cumulative and mutual cross coherence of the constructed dictionaries are lower than those of Gaussian random dictionary. The concept of General Restricted Isometry Constant (GRIC) is introduced. Low cumulative cross coherence puts bound on GRIC and small GRIC improves successful recovery rate of OMP algorithm. Experiments demonstrate that OMP algorithm performs better using dictionaries constructed by the proposed algorithm than Gaussian random dictionaries and those constructed by Schnass' algorithm. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/LSP.2011.2168517 | IEEE Signal Process. Lett. |
Keywords | Field | DocType |
sensing dictionary,coherence,signal processing,omp algorithm,compressive sensing,measurement dictionaries,general restricted isometry constant,schnass algorithm,dictionaries,gaussian distribution,sensing dictionaries,alternating projection method,mutual cross coherence,dictionaries construction,low cumulative cross coherence,gaussian random dictionary,orthogonal matching pursuit,iterative methods,time-frequency analysis,compressed sensing,cumulant,optimization,minimization,indexing terms,time frequency analysis,matching pursuit,sensors | Signal processing,Mathematical optimization,Pattern recognition,Iterative method,Projection method,Coherence (physics),Gaussian,Minification,Artificial intelligence,Time–frequency analysis,Compressed sensing,Mathematics | Journal |
Volume | Issue | ISSN |
18 | 11 | 1070-9908 |
Citations | PageRank | References |
4 | 0.43 | 8 |
Authors | ||
3 | ||