Title :
A Gauss-Markov model formulation for the estimation of ARMA model of time-varying signals and systems
Author :
Malladi, Krishna Mohan ; Kumar, Ratnam V Raja ; Rao, K. Veerabhadra
Author_Institution :
Signal Process. Div., Res. Centre Imarat, Hyderabad, India
Abstract :
A Gauss-Markov model is formulated to estimate the model of a non-stationary signal. The time-varying parameters of the model are modelled as stochastic processes. A time-varying ARMA model is considered to represent the non-stationary process. Furthermore, in this work, a unified method for the optimal estimation of both the time-varying parameters and their corresponding stochastic model parameters is presented. This method utilises the proposed Gauss-Markov model for the estimation process through the extended Kalman filter (EKF)
Keywords :
Gaussian processes; Kalman filters; Markov processes; autoregressive moving average processes; parameter estimation; signal processing; time-varying systems; ARMA model; EKF; Gauss-Markov model formulation; extended Kalman filter; nonstationary process; nonstationary signal; optimal estimation; stochastic processes; time-varying parameters; time-varying signals; time-varying systems; Gaussian noise; Gaussian processes; Kalman filters; Seismology; Signal processing; Speech processing; State estimation; Stochastic processes; Stochastic resonance; Time varying systems;
Conference_Titel :
Time-Frequency and Time-Scale Analysis, 1998. Proceedings of the IEEE-SP International Symposium on
Conference_Location :
Pittsburgh, PA
Print_ISBN :
0-7803-5073-1
DOI :
10.1109/TFSA.1998.721510
