Name
Abstract | ||
|---|---|---|
Compressive sensing (CS) is proposed for signal sampling below the Nyquist rate based on the assumption that the signal is sparse in some transformed domain. Most sensing matrices (e.g., Gaussian random matrix) in CS, however, usually suffer from unfriendly hardware implementation, high computation cost, and huge memory storage. In this letter, we propose a deterministic sensing matrix for collect... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/LSP.2018.2809693 | IEEE Signal Processing Letters |
Keywords | Field | DocType |
Sensors,Sparse matrices,Decoding,Dictionaries,Frequency-domain analysis,Encoding,Hardware | Frequency domain,Pattern recognition,Matrix (mathematics),Algorithm,Fast Fourier transform,Circulant matrix,Artificial intelligence,Nyquist rate,Mathematics,Compressed sensing,Sparse matrix,Encoding (memory) | Journal |
Volume | Issue | ISSN |
25 | 4 | 1070-9908 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sung-Hsien Hsieh | 1 | 48 | 13.71 |
| Chun-shien Lu | 2 | 1238 | 104.71 |
| S. -C. Pei | 3 | 37 | 5.33 |