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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Peng Zhang Sumei Sun Cong Ling |
| Copyright Year | 2014 |
| Description | Author affiliation: Dept. of Electr. & Electron. Eng., Imperial Coll. London, London, UK (Peng Zhang; Cong Ling) || Inst. for Infocomm Res., A*STAR, Singapore, Singapore (Sumei Sun) |
| Abstract | Sampling from certain probability distribution shows better recovery performance than uniform sampling in literature. However, a comprehensive theoretical analysis concerning more realistic signal models is still lacking. In this paper, we consider the sampling of stochastic processes and random fields in the Fourier domain. We propose a new variable-density sampling and linear reconstruction technique, and prove its theoretical recovery guarantee. For high dimensional random fields, uniform sampling requires a number of samples increasing exponentially with the dimension, while the variable density sampling scheme guarantees faithful recovery performance with a polynomial size of random samples. |
| Starting Page | 1306 |
| Ending Page | 1310 |
| File Size | 401869 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781479951864 |
| ISSN | 21578117 |
| DOI | 10.1109/ISIT.2014.6875044 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-06-29 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Stochastic processes Lattices Information theory Image reconstruction Random variables Correlation Compressed sensing |
| Content Type | Text |
| Resource Type | Article |
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