Search: onr:"swepub:oai:lup.lub.lu.se:9f368b0f-b7a2-4b20-8798-32e79c55681c" >
Optimal Cepstrum Sm...
Optimal Cepstrum Smoothing
-
- Sandberg, Johan (author)
- Lund University,Lunds universitet,Matematisk statistik,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Mathematical Statistics,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH
-
- Sandsten, Maria (author)
- Lund University,Lunds universitet,Statistical Signal Processing Group,Forskargrupper vid Lunds universitet,Matematisk statistik,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Lund University Research Groups,Mathematical Statistics,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH
-
(creator_code:org_t)
- Elsevier BV, 2012
- 2012
- English.
-
In: Signal Processing. - : Elsevier BV. - 0165-1684. ; 92:5, s. 1290-1301
- Related links:
-
http://dx.doi.org/10...
-
show more...
-
https://lup.lub.lu.s...
-
https://doi.org/10.1...
-
show less...
Abstract
Subject headings
Close
- Abstract in UndeterminedThe cepstrum of a random process has proven to be a useful tool in a wide range of applications. The common cepstrum estimator based on the periodogram suffers from large variance, and, to a smaller degree, from bias. The variance can be reduced by smoothing. However, the smoothing may be performed in four different domains: the covariance, the spectral, the log-spectral, and the cepstral domain. We present the mean square error (MSE) optimal smoothing kernels in each domain for estimation of the cepstrum. The lower MSE bound of each of the four families of estimators are compared. We also demonstrate how the four MSE optimal estimators differ in robustness.
Subject headings
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Keyword
- Cepstrum
- Smoothing
Publication and Content Type
- art (subject category)
- ref (subject category)
Find in a library
To the university's database