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Maximum-Likelihood Estimation of Delta-Domain Model Parameters From Noisy Output Signals.
- Source :
-
IEEE Transactions on Signal Processing . Aug2008 Part 1 of 2, Vol. 56 Issue 8, p3765-3770. 6p. 4 Graphs. - Publication Year :
- 2008
-
Abstract
- Fast sampling is desirable to describe signal transmission through wide-bandwidth systems. The delta-operator provides an ideal discrete-time modeling description for such fast-sampled systems. However, the estimation of delta-domain model parameters is usually biased by directly applying the delta-transformations to a sampled signal corrupted by additive measurement noise. This problem is solved here by expectation-maximization, where the delta-transformations of the true signal are estimated and then used to obtain the model parameters. The method is demonstrated on a numerical example to improve on the accuracy of using a shift operator approach when the sample rate is fast. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1053587X
- Volume :
- 56
- Issue :
- 8
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Signal Processing
- Publication Type :
- Academic Journal
- Accession number :
- 33542893
- Full Text :
- https://doi.org/10.1109/TSP.2008.920443