TY - JOUR
T1 - LOWER ESTIMATION ERROR BOUNDS FOR GAUSS-POISSON PROCESSES.
AU - Segall, Adrian
PY - 1979
Y1 - 1979
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=0018724988&partnerID=8YFLogxK
U2 - 10.1007/bfb0009414
DO - 10.1007/bfb0009414
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AN - SCOPUS:0018724988
SN - 0160-8835
SP - 559
EP - 565
JO - American Society of Mechanical Engineers, Applied Mechanics Division, AMD
JF - American Society of Mechanical Engineers, Applied Mechanics Division, AMD
ER -