DocumentCode :
1092153
Title :
A note on covariance-invariant digital filter design and autoregressive moving average spectrum analysis
Author :
Kinkel, John F. ; Perl, Joseph ; Scharf, Louis L. ; Stubberud, Allen R.
Author_Institution :
Irvine Avenue, Newport Beach, CA
Volume :
27
Issue :
2
fYear :
1979
fDate :
4/1/1979 12:00:00 AM
Firstpage :
200
Lastpage :
202
Abstract :
Consider an autoregressive-moving average (ARMA) discrete-time sequence {x_{k}} with covariance sequence {R_{k}} . Equations are given for the solution of the AR coefficients {a_{k}}\\min{1}\\max {n} in terms of the covariances {R_{k}}\\min{0}\\max {2n-1} , and subsequent solution for the MA coefficients {b_{k}}\\min{1}\\max {n} in terms of the AR coefficients and the covariances {R_{k}}\\min{0}\\max {n-1} . The results are derived and presented somewhat differently than usual to complement the results of [1] for the synthesis of covariance-invariant digital filters. In the context of spectrum analysis, the results provide a means of performing ARMA spectrum analysis on data that arise as sampled data from a rational continuous-time process [2]. An important result, originally derived in [2], shows that the ARMA spectrum can be obtained without actually solving the nonlinear factorization problem for the MA coefficients.
Keywords :
Acoustic pulses; Covariance matrix; Data analysis; Digital filters; Equations; Performance analysis; Probability; Speech analysis; Statistics; Transfer functions;
fLanguage :
English
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
0096-3518
Type :
jour
DOI :
10.1109/TASSP.1979.1163220
Filename :
1163220
Link To Document :
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