Title :
Maximum likelihood estimation of bias in discrete linear systems
Author :
Sage, A.P. ; Lin, J.L.
Author_Institution :
SMU Institute of Technology, Dallas, Texas
Abstract :
This paper presents the use of maximum likelihood estimation, optimization theory, and discrete invariant imbedding in the development of algorithms for the maximum likelihood estimation of bias coefficients in discrete linear systems with stochastic inputs and disturbances.
Keywords :
Control systems; Linear systems; Maximum likelihood estimation; Prediction algorithms; Predictive models; Q measurement; Random processes; Recursive estimation; State estimation; Stochastic systems;
Conference_Titel :
Adaptive Processes (9th) Decision and Control, 1970. 1970 IEEE Symposium on
Conference_Location :
Austin, TX, USA
DOI :
10.1109/SAP.1970.270029
