Abstract
When applied to continuous-time observations, type-based detection strategies are limited by the necessity to crudely quantize each sample. To alleviate this problem, we smooth the types for both the training and observation data with a linear filter. This post-processing improves detector performance significantly (error probabilities decrease by over a factor of three) without incurring a significant computational penalty. However, this improvement depends on the amplitude distribution and on the quantizer's characteristics.
Original language | English (US) |
---|---|
Title of host publication | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
Editors | Anon |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 3717-3720 |
Number of pages | 4 |
Volume | 5 |
State | Published - 1997 |
Event | Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 5) - Munich, Ger Duration: Apr 21 1997 → Apr 24 1997 |
Other
Other | Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 5) |
---|---|
City | Munich, Ger |
Period | 4/21/97 → 4/24/97 |
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering
- Acoustics and Ultrasonics