LOWER ESTIMATION ERROR BOUNDS FOR GAUSS-POISSON PROCESSES.

Adrian Segall

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

The problem is considered of estimation of a signal modulating the rate of an observed jump process. Representation formulas for the least squares estimate have been obtained in previous works, but the exact solution requires solving an infinite set of stochastic differential equations, so that one has to work with suboptimal estimates. In order to investigate their performance compared with the optimal estimate, bounds for the performance of the latter are useful. In this paper a general method developed by Bobrovsky-Aakai is applied to obtain lower bounds for the estimation error when the observed process is of the Gauss-Poisson type.

Original languageEnglish
Pages (from-to)559-565
Number of pages7
JournalAmerican Society of Mechanical Engineers, Applied Mechanics Division, AMD
DOIs
StatePublished - 1979

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