SPECTRUM ANALYSIS USING A NEW AUTOCORRELATION MEASURE.

Dendrinos, M; Carayannis, G

dc.contributor.author	Dendrinos, M	en
dc.contributor.author	Carayannis, G	en
dc.date.accessioned	2014-03-01T02:40:53Z
dc.date.available	2014-03-01T02:40:53Z
dc.date.issued	1988	en
dc.identifier.issn	07367791	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30261
dc.subject	Eigenvalues	en
dc.subject	Frequency Estimation	en
dc.subject	Reflection Coefficient	en
dc.subject	Singular Value Decomposition	en
dc.subject	Spectral Analysis	en
dc.subject	Spectrum Analysis	en
dc.subject.other	SIGNAL FILTERING AND PREDICTION	en
dc.subject.other	FREQUENCY ESTIMATION	en
dc.subject.other	LATTICE AUTOCORRELATION MEASURE (LAM)	en
dc.subject.other	LATTICE METHOD	en
dc.subject.other	PISARENKO HARMONIC RETRIEVAL	en
dc.subject.other	SINGULAR-VALUE DECOMPOSITION	en
dc.subject.other	SPECTRUM ANALYSIS	en
dc.title	SPECTRUM ANALYSIS USING A NEW AUTOCORRELATION MEASURE.	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICASSP.1988.197143	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICASSP.1988.197143	en
heal.publicationDate	1988	en
heal.abstract	An autocorrelation measure of a single-frame which is not derived directly from the data is defined. A lattice method is first used to compute the frame-reflection coefficients. Then the predictor coefficients are computed, and the normal equations result in a new set of autocorrelation lags named the lattice autocorrelation measure (LAM). LAM is shown to be more accurate than the conventional Bartlett autocorrelation measure, especially in case of few samples and low SNR. The application of LAM in eigenvalues spectral analysis gives better estimates than conventional autocorrelation, mainly in the central frequency range. The use of the LAM in overdetermined autocorrelation matrices analyzed by singular-value decomposition leads to an improvement in the frequency estimation of very close harmonics in the cases of short signal frames.	en
heal.publisher	IEEE, New York, NY, USA	en
heal.journalName	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings	en
dc.identifier.doi	10.1109/ICASSP.1988.197143	en
dc.identifier.spage	2468	en
dc.identifier.epage	2471	en