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Approximate Optimal Periodogram Smoothing for Cepstrum Estimation using a Penalty Term

In English

Författare

Summary, in English

The cepstrum of a random process is useful in many applications. The cepstrum is usually estimated from the periodogram. To reduce the mean square error (MSE) of the estimator, the periodogram may be smoothed with a kernel function. We present an explicit expression for a kernel function which is approximatively MSE optimal for cepstrum estimation. A penalty term has to be added to the minimization problem, but we demonstrate how the weighting of the penalty term can be chosen. The performance of the estimator is evaluated on simulated processes. Since the MSE optimal smoothing kernel depends on the true covariance function, we give an example of a simple data driven method.

Avdelning/ar

Publiceringsår

2010

Språk

Engelska

Sidor

363-367

Publikation/Tidskrift/Serie

Proceedings of the EUSIPCO, European Signal Processing Conference 2010

Dokumenttyp

Konferensbidrag

Förlag

EURASIP

Ämne

  • Probability Theory and Statistics

Conference name

18th European Signal Processing Conference (EUSIPCO-2010)

Conference date

2010-08-23 - 2010-08-27

Conference place

Aalborg, Denmark

Status

Published

Forskningsgrupp

  • Statistical Signal Processing Group

ISBN/ISSN/Övrigt

  • ISSN: 2076-1465