Title :
Realization and reduction of Markovian models from nonstationary data
Author_Institution :
Tel-Aviv University, Tel-Aviv, Isreal
fDate :
12/1/1981 12:00:00 AM
Abstract :
The realization of Markovian models for nonstationary processes generated by time invariant linear systems is considered. A model is obtained by constructing an orthogonal finite-step predictor for the process. Optimal model approximation by order reduction is naturally defined in this framework. The construction and reduction of Markovian models from multiple data records and the numerical considerations involved are illustrated by examples.
Keywords :
Linear systems, stochastic; Markov processes; Nonstationary stochastic processes; Realization theory; Stochastic systems, linear; Helium; Linear systems; Observability; Predictive models; Singular value decomposition; Stochastic processes; Stochastic resonance; Time invariant systems; Time varying systems; White noise;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1981.1102811
