scholarly journals Discrete-Time Minimum-Mean-Square-Error Filtering

10.5772/39250 ◽  
2012 ◽  
Author(s):  
Garry Einicke
Keyword(s):  
Mean Square Error ◽  
Discrete Time ◽  
Minimum Mean Square Error ◽  
Mean Square ◽  
Error Filtering

Generalized Levinson–Durbin Sequences and Binomial Coefficients

Integers ◽  
2009 ◽  
Vol 9 (2) ◽  
Author(s):  
Paul Shaman
Keyword(s):  
Stochastic Process ◽  
Sample Size ◽  
Mean Square Error ◽  
Discrete Time ◽  
Minimum Mean Square Error ◽  
Stationary Stochastic Process ◽  
Binomial Coefficients ◽  
Stationary Processes ◽  
Mean Square ◽  
Special Case

AbstractThe Levinson–Durbin recursion is used to construct the coefficients which define the minimum mean square error predictor of a new observation for a discrete time, second-order stationary stochastic process. As the sample size varies, the coefficients determine what is called a Levinson–Durbin sequence. A generalized Levinson–Durbin sequence is also defined, and we note that binomial coefficients constitute a special case of such a sequence. Generalized Levinson–Durbin sequences obey formulas which generalize relations satisfied by binomial coefficients. Some of these results are extended to vector stationary processes.

scholarly journals Linear minimum mean-square error filtering for evoked responses: application to fetal MEG

2006 ◽  
Vol 53 (5) ◽  
pp. 959-963 ◽  
Author(s):  
Mingli Chen ◽  
B.D. Van Veen ◽  
R.T. Wakai
Keyword(s):  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Evoked Responses ◽  
Mean Square ◽  
Error Filtering
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