| Paper: | SPTM-L1.3 | ||
| Session: | Bayesian Approaches and Particle Filters | ||
| Time: | Tuesday, May 16, 11:10 - 11:30 | ||
| Presentation: | Lecture | ||
| Topic: | Signal Processing Theory and Methods: Detection, Estimation, Classification Theory and Applications | ||
| Title: | The Bayesian Abel Bound on the Mean Square Error | ||
| Authors: | Alexandre Renaux, Ecole Normale Superieure de Cachan, France; Philippe Forster, University Paris 10, France; Pascal Larzabal, Ecole Normale Superieure de Cachan, France; Christ Richmond, MIT Lincoln Laboratory, United States | ||
| Abstract: | This paper deals with lower bound on the Mean Square Error (MSE). In the Bayesian framework, we present a new bound which is derived from a constrained optimization problem. This bound is found to be tighter than the Bayesian Bhattacharyya bound, the Reuven-Messer bound, the Bobrovsky- Zakai bound, and the Bayesian Cramer-Rao bound. | ||
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