Autoregression and cepstrum-domain filtering

Signal Processing

Volumn 76, Issue 1, 1999, Pages 93-97

  Martin, R J ^a,b  

^a UNIVERSITY OF SOUTH AUSTRALIA   (Australia)

^b BNP PARIBAS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CORRELATION METHODS; MATHEMATICAL MODELS; POLES AND ZEROS; REGRESSION ANALYSIS;

CEPSTRUM-DOMAIN FILTERING; HOMOMORPHIC SIGNAL PROCESSING;

SIGNAL FILTERING AND PREDICTION;

EID: 0032632781     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-1684(98)00249-7     Document Type: Article

References (9)

1. B.P. Bogert, W.R.J. Healy, J.W. Tukey, The quefrency analysis of time series for echoes: cepstrum, pseudo autocovariance, cross cepstrum and saphe cracking, in: M. Rosenblatt (Ed.), Time Series Analysis, Wiley, New York, 1963.
2. S.M. Kay, S.L. Marple, Spectrum analysis: A modern perspective, Proc. IEEE 69 (1981) 1380-1419.
3. T. Landers, Maximum entropy cepstral analysis, in: Proc. RADC Spectral Estimation Workshop, 1978, pp. 245-257.
4. J. Makhoul, Linear prediction: A tutorial review, Proc. IEEE 63 (1975) 561-580.
5. S.L. Marple, Digital Spectral Analysis with Applications, Prentice-Hall, Englewood Cliffs, NJ, 1987.
6. R.J. Martin, M.J. Kearney, Remote sea-current sensing using HF radar: An autoregressive approach, IEEE J. Oceanic Eng. 22 (1997) 151-155.
7. C.L. Nikias, A.P. Petropulu, Higher-Order Spectra Analysis: A Nonlinear Signal Processing Framework, Prentice-Hall, Englewood Cliffs, NJ, 1993, Chapter 5.
8. J.G. Proakis, D.G. Manolakis, Digital Signal Processing, Macmillan, New York, 1992, Chapter 5.5.4.
9. J.-Y. Tourneret, B. Lacaze, On the statistics of estimated reflection and cepstrum coefficients of an autoregressive process, Signal Processing 43 (1995) 253-267.