Name
Abstract | ||
|---|---|---|
Based on the here developed functional analytic machinery we extend the theory of operator sampling and identification to apply to operators with stochastic spreading functions. We prove that identification with a delta train signal is possible for a large class of stochastic operators that have the property that the autocorrelation of the spreading function is supported on a set of 4D volume less than one and this support set does not have a defective structure. In fact, unlike in the case of deterministic operator identification, the geometry of the support set has a significant impact on the identifiability of the considered operator class. Also, we prove that, analogous to the deterministic case, the restriction of the 4D volume of a support set to be less or equal to one is necessary for identifiability of a stochastic operator class. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.acha.2013.05.001 | Applied and Computational Harmonic Analysis |
Keywords | Field | DocType |
Stochastic modulation spaces,Generalized stochastic processes,Underspread operators,Gabor frame operators,Stochastic spreading function,Measurements of stochastic channels,Time–frequency analysis,Defective patterns | Discrete mathematics,Stochastic optimization,Semi-elliptic operator,Mathematical analysis,Identifiability,Continuous-time stochastic process,Operator (computer programming),Time–frequency analysis,Operator theory,Mathematics,Autocorrelation | Journal |
Volume | Issue | ISSN |
36 | 2 | 1063-5203 |
Citations | PageRank | References |
1 | 0.35 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Götz E. Pfander | 1 | 5 | 2.11 |
| Pavel Zheltov | 2 | 7 | 1.18 |