Matrix analysis
Cyclostationarity: half a century of research
Signal Processing
High-rate interpolation of random signals from nonideal samples
IEEE Transactions on Signal Processing
Spectral analysis of nonuniformly sampled data -- a review
Digital Signal Processing
Sampling theorems for Doppler-stretched wide-band signals
Signal Processing
Signal recovery with cost-constrained measurements
IEEE Transactions on Signal Processing
Recent advances in theory and methods for nonstationary signal analysis
EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in theory and methods for nonstationary signal analysis
On the truncation error of the sampling expansion for stationarybandlimited processes
IEEE Transactions on Signal Processing
Intrinsic Limits of Dimensionality and Richness in Random Multipath Fields
IEEE Transactions on Signal Processing
Sampling of Spectrally Correlated Processes
IEEE Transactions on Signal Processing
A sampling theorem for nonstationary random processes (Corresp.)
IEEE Transactions on Information Theory
Degrees of freedom in multiple-antenna channels: a signal space approach
IEEE Transactions on Information Theory
An Average Sampling Theorem for Bandlimited Stochastic Processes
IEEE Transactions on Information Theory
| Hi-index | 0.00 |
In this article we consider the representation of a finite-energy non-stationary random field with a finite number of samples. We pose the problem as an optimal sampling problem where we seek the optimal sampling interval under the mean-square error criterion, for a given number of samples. We investigate the optimum sampling rates and the resulting trade-offs between the number of samples and the representation error. In our numerical experiments, we consider a parametric non-stationary field model, the Gaussian-Schell model, and present sampling schemes for varying noise levels and for sources with varying numbers of degrees of freedom. We discuss the dependence of the optimum sampling interval on the problem parameters. We also study the sensitivity of the error to the chosen sampling interval.