Referenced Items are not available for this document.
A family of algorithms is developed for adaptive parameter estimation of constrained autoregressive moving-average (ARMA) signals in the presence of noise. These algorithms utilize a priori information about the signal's properties, such as its spectral type (for example, low-pass, bandpass, etc.) or a spatial-domain characteristic. Special applications include modeling of autoregressions (AR) and signals of known spectral type in the presence of noise, signal deconvolution, image deblurring and multipath parameter estimation. Selected results of simulations are included to demonstrate the performance of the algorithms
Published in:
Acoustics, Speech and Signal Processing, IEEE Transactions on
(Volume:36
,
Issue:
8
)
Date of Publication: Aug 1988
- Page(s):
- 1282 - 1291
- ISSN :
- 0096-3518
- INSPEC Accession Number:
- 3252439
- Digital Object Identifier :
- 10.1109/29.1656
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Aug 1988
- Sponsored by :
- IEEE Signal Processing Society
About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
