Abstract
Predictors are derived which minimize the maximum possible mean-squared prediction error for signals observed in white noise and having a bounded kth derivative. Expressions are given for the resulting worst-case error and a suboptimal solution is presented which, for the case k = 2, performs nearly as well as the optimal and is far easier to implement.
Original language | English (US) |
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Pages (from-to) | 29-44 |
Number of pages | 16 |
Journal | Journal of the Franklin Institute |
Volume | 297 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1974 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Signal Processing
- Computer Networks and Communications
- Applied Mathematics