Abstract
The Wiener-Hopf solution is based on estimates of the covariance matrix and the cross-correlation vector, which will likely be poor for small sample sizes. Yet the solution can be very accurate. We explore why this is, and why it is disadvantageous to separately estimate the two statistics, or try to include explicit knowledge of the input process to the adaptive system. The results are based on a least squares interpretation of Wiener-Hopf and an exploration of the variances of estimates, which we underpin by simulations.
| Original language | English |
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| Title of host publication | 2025 IEEE Statistical Signal Processing Workshop (SSP) |
| Place of Publication | Piscataway, NJ |
| Publisher | IEEE |
| Number of pages | 5 |
| Publication status | Accepted/In press - 3 Apr 2025 |
| Event | 23rd IEEE Statistical Signal Processing Workshop - Edinburgh, United Kingdom Duration: 8 Jun 2025 → 11 Jun 2025 https://2025.ieeessp.org/ |
Publication series
| Name | IEEE/SP Workshop on Statistical Signal Processing (SSP) |
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| ISSN (Print) | 2373-0803 |
| ISSN (Electronic) | 2693-3551 |
Conference
| Conference | 23rd IEEE Statistical Signal Processing Workshop |
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| Abbreviated title | SSP 2025 |
| Country/Territory | United Kingdom |
| City | Edinburgh |
| Period | 8/06/25 → 11/06/25 |
| Internet address |
Keywords
- Wiener-Hopf solution
- statistical signal processing
- linear filtering
- covariance matrix
- cross-correlation vector