DocumentCode
944271
Title
Recursion formulas for growing memory digital filters
Author
Blum, Marvin
Volume
4
Issue
1
fYear
1958
fDate
3/1/1958 12:00:00 AM
Firstpage
24
Lastpage
30
Abstract
A growing memory digital filter is defined by considering the input
-output
relationship in the form
where
is the weighting sequence of a linear time varying digital filter. Contained herein are a derivation of an optimum growing memory smoothing and prediction filter in the least squares sense for polynomial input functions, (of degree =
) and a theorem on the class of time invariant sequence
, which are solutions of a difference equation of tiite order, and an application of the theorem to the synthesis of sampled correlated noise by digital processes, using recursion formulas. The recursion formulation represents a practical solution to the generation of a correlated noise sequence on line during simulation studies on digital computers.
-output
relationship in the form
where
is the weighting sequence of a linear time varying digital filter. Contained herein are a derivation of an optimum growing memory smoothing and prediction filter in the least squares sense for polynomial input functions, (of degree =
) and a theorem on the class of time invariant sequence
, which are solutions of a difference equation of tiite order, and an application of the theorem to the synthesis of sampled correlated noise by digital processes, using recursion formulas. The recursion formulation represents a practical solution to the generation of a correlated noise sequence on line during simulation studies on digital computers.Keywords
Digital filters; Application software; Autocorrelation; Computational modeling; Computer simulation; Difference equations; Digital filters; Integral equations; Least squares approximation; Least squares methods; Polynomials; Smoothing methods; Taylor series;
fLanguage
English
Journal_Title
Information Theory, IRE Transactions on
Publisher
ieee
ISSN
0096-1000
Type
jour
DOI
10.1109/TIT.1958.1057439
Filename
1057439
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