Physical Langevin model and the time-series model in systems far from equilibrium
- 1 January 1982
- journal article
- research article
- Published by American Physical Society (APS) in Physical Review A
- Vol. 25 (1) , 496-507
- https://doi.org/10.1103/physreva.25.496
Abstract
To bridge the gap between a physical Langevin equation and a stochastic equation used in the time-series analysis, and to clarify the physical foundations of the latter, the time-series model from the Langevin equation is derived with the aid of two manipulations—elimination of irrelevant variables and projection of state variables upon a space spanned by observed quantities. The order of the two manipulations is shown to be important to find an equation called the Kalman filter in control theory. All the results are summarized in a concise schematic diagram which relates various models and equations established so far in different fields.Keywords
This publication has 15 references indexed in Scilit:
- Hidden State Variables and AR-MA Formulation of Reactor NoiseJournal of Nuclear Science and Technology, 1980
- Hidden State-Variables and a Non-Markoffian Formulation of Reactor NoiseJournal of Nuclear Science and Technology, 1976
- Reactor Noise Theory based on System Size ExpansionJournal of Nuclear Science and Technology, 1976
- A new look at the statistical model identificationIEEE Transactions on Automatic Control, 1974
- Irreversible Circulation of FluctuationProgress of Theoretical Physics, 1974
- Fluctuation and relaxation of macrovariablesJournal of Statistical Physics, 1973
- Statistical approach to computer control of cement rotary kilnsAutomatica, 1972
- Statistical predictor identificationAnnals of the Institute of Statistical Mathematics, 1970
- Transport, Collective Motion, and Brownian MotionProgress of Theoretical Physics, 1965
- Memory Effects in Irreversible ThermodynamicsPhysical Review B, 1961