Title :
Generalized Chandrasekhar algorithms: Time-varying models
Author_Institution :
State University of New York at Buffalo, Amherst, New York
Abstract :
Generalized Chandrasekhar algorithms are obtained that are applicable to time-varying models as well as time-invariant ones. Backward and forward-time differentiations are introduced that readily provide the generalized Chandrasekhar algorithms as well as several interesting interpretations of these results.
Keywords :
Boundary conditions; Covariance matrix; Noise measurement; Optimal control; Q measurement; Riccati equations;
Conference_Titel :
Decision and Control including the 14th Symposium on Adaptive Processes, 1975 IEEE Conference on
Conference_Location :
Houston, TX, USA
DOI :
10.1109/CDC.1975.270607
