Abstract
A data-adaptive time-frequency representation that obtains high resolution of signal components in time-frequency is presented. This representation overcomes the often poor resolution of the traditional short-time Fourier transform, while avoiding the nonlinearities that make the Wigner distribution and other bilinear representations difficult to interpret and use. The method uses adaptive Gaussian windows, with the window parameters varying at different time-frequency locations to maximize the local signal concentration in time frequency. Two methods for selecting the Gaussian parameters are presented: a parameter estimation approach, and a method that maximizes a measure of local signal concentration.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 681-684 |
| Number of pages | 4 |
| Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
| State | Published - 1987 |
| Externally published | Yes |
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering