ON THE UNNORMALIZED SOLUTION OF THE FILTERING PROBLEM WITH COUNTING PROCESS OBSERVATIONS

被引：45
|
作者：
KLIEMANN, WH [1 ]
KOCH, G [1 ]
MARCHETTI, F [1 ]
机构：
[1] UNIV ROME LA SAPIENZA,DEPT MATH,I-00185 ROME,ITALY
来源：
IEEE TRANSACTIONS ON INFORMATION THEORY | 1990年 / 36卷 / 06期
关键词：
D O I：
10.1109/18.59936
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A general procedure to solve filtering problems for counting process observations is discussed. Linear (nonstochastic, integro-dif ferential) equations describe the evolution of unnormalized conditional distribution of the state process between observation jump times, while at jump times a linear updating is called for. Final normalization is the only nonlinear operation to be implemented. Quite general situations may be accommodated in the present setup: the state can be virtually any Markov semimartingale, the observation process may affect the dynamics of the state and vice versa, and there is complete freedom in correlating state and observation martingale terms. © 1990 IEEE
引用
收藏
页码：1415 / 1425
页数：11
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