Nonlinear filtering. A weighted mean squares approach and a Bayesian one via the maximum entropy principle

Signal Processing

Volumn 21, Issue 4, 1990, Pages 323-338

  Jumarie, Guy ^a  

^a UNIVERSITÉ DU QUÉBEC À MONTRÉAL   (Canada)

Author keywords

Bayesian estimation; Fokker Planck equation; maximum path entropy; mean squares estimation; Nonlinear filtering; stochastic systems

Indexed keywords

ELECTRIC FILTERS; PROBABILITY; STATISTICAL METHODS;

BAYESIAN ESTIMATION; MAXIMUM ENTROPY PRINCIPLE; NONLINEAR FILTERING;

SIGNAL FILTERING AND PREDICTION;

EID: 0025588825     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/0165-1684(90)90102-5     Document Type: Article

References (15)

1. A Bayesian approach to problems in stochastic estimation and control
2. Information theory and statistical mechanics I, II
3. Information theory and statistical mechanics I, II
4. Simple general method to analyze the moment stability and sensitivity of nonlinear systems with or without delay
5. Analysis of moment stability and sensitivity of nonlinear stochastic distributed systems. A practical approach via a distributed Fokker-Planck equation
6. Filtering and identification in stochastic processes and time series. New approaches via path entropy
7. On the dynamical equations of conditional probability density functions, with application to optimal stochastic control theory
8. On the differential equation satisfied by conditional probability of Markov processes
9. Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy