Abstract
A model-based approach for superresolution signal reconstruction from noisy bandlimited Fourier data is proposed. The approach combines the virtues of parametric and nonparametric techniques by maximum-likelihood fitting of the data by a mixture of exponentials and smooth basis functions. Performance bounds are derived and analyzed, and a model computationally efficient algorithm is described. The performance of the algorithm in simulations closely matches the bounds over a wide range of operating conditions. Overall, the reconstructions are far superior to those obtained by traditional Fourier transform processing.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1205-1208 |
| Number of pages | 4 |
| Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
| Volume | 3 |
| State | Published - 1990 |
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering
- Acoustics and Ultrasonics