Name
Title | ||
|---|---|---|
Low-complexity Graph Sampling With Noise and Signal Reconstruction via Neumann Series |
Abstract | ||
|---|---|---|
Graph sampling addresses the problem of selecting a node subset in a graph to collect samples, so that a K-bandlimited signal can be reconstructed with high fidelity. Assuming an independent and identically distributed (i.i.d.) noise model, minimizing the expected mean square error (MMSE) leads to the known A-optimality criterion for graph sampling, which is expensive to compute and difficult to o... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TSP.2019.2940129 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
Signal reconstruction,Sampling methods,Laplace equations,Matrix decomposition,Complexity theory,Covariance matrices,Fourier transforms | Least squares,Mathematical optimization,Neumann series,Bandlimiting,Matrix decomposition,Algorithm,Mean squared error,Independent and identically distributed random variables,Sampling (statistics),Signal reconstruction,Mathematics | Journal |
Volume | Issue | ISSN |
67 | 21 | 1053-587X |
Citations | PageRank | References |
1 | 0.35 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fen Wang | 1 | 10 | 7.29 |
| Gene Cheung Connie Chan | 2 | 1387 | 121.82 |
| Yongchao Wang | 3 | 29 | 6.54 |