Title :
Some observations about centralized linear prediction
Author :
Therrien, Charles W.
Author_Institution :
Dept. of Electr. & Comput. Eng., Naval Postgraduate Sch., Monterey, CA, USA
Abstract :
A new formula for the coefficients of the prediction error filter for noncausal symmetric (centralized) linear prediction is presented. It is shown that when the signal is AR, the centralized filter reduces to a scaled product of the optimal forward and backward prediction error filters for the process. The result appears to be unique for linear prediction. For example, the symmetric noncausal Wiener filter for estimating a signal in noise has no such realization in terms of optimal causal filters.
Keywords :
autoregressive processes; circuit feedback; error analysis; feedforward; filtering theory; noise; prediction theory; AR signal; centralized filter; centralized linear prediction; filter coefficients; noise; noncausal symmetric linear prediction; optimal backward prediction error filter; optimal causal filters; optimal forward prediction error filter; scaled product; symmetric noncausal Wiener filter; Computer errors; Equations; Filtering; Nonlinear filters; Predictive models; Signal processing; Wiener filter;
Conference_Titel :
Signals, Systems, and Computers, 1999. Conference Record of the Thirty-Third Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-7803-5700-0
DOI :
10.1109/ACSSC.1999.832373
