Detection of signals in nonstationary random noise via stationarization and stationarity test

IEEE Workshop on Statistical Signal Processing Proceedings

Volumn 2005, Issue , 2005, Pages 587-590

  Ijima, Hiroshi ^a   Okui, Ryo ^a   Ohsumi, Akira ^a  

^a KYOTO INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; DIRECT NUMERICAL SIMULATION; SPURIOUS SIGNAL NOISE; STATISTICAL METHODS;

RANDOM NOISE; STATIONARITY TEST; STATIONARIZATION;

SIGNAL DETECTION;

EID: 33947162484     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ssp.2005.1628663     Document Type: Conference Paper

References (8)

1. W. J. Fitzgerald, R. L. Smith, A. T. Walden, and P. C. Young (Eds.): Nonlinear and Nonstationary Signal Processing, Cambridge Univ. Press, Cambrigde, 2000.
2. A. Ohsumi, H. Ijima, and T. Sodeoka: High Resolution Detector for Signals in Random Noise Using Wavelet-based Wigner Distribution, Proc. 25th IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP2000), Istanbul, Turkey, June 2000, pp. 596-599.
3. H. Ijima, A. Ohsumi, I. Djurović, H. Sato, and H. Ôkura: Parameter Estimation of Signals in Random Noise: An Approach Using Pseudo-Wigner Distribution, Trans. IEICE, Ser.A, vol. J86-A, no. 11 (2003), pp. 1158-1169 (in Japanese).
4. M. B. Priestley: Spectral Analysis and Time Series, Academic Press, New York, 1981.
5. Y. Okabe: On Stochastic Difference Equations for the Multi-dimensional Weakly Stationary Time Series, in Prospect of Algebraic Analysis (Eds: M. Kashihara and T. Kawai), Academic Press, New York, 1981, pp. 601-645.
6. 2O-Langevin Equations and Its Applications to Data Analysis (I): Stationary Analysis, Hokkaido Math. J., vol.20 (1991), pp. 45-90.
7. Y. Okabe: Langevin Equation and Causality Analysis, Sûgaku (Mathematics), vol.43, no.4 (1991), pp.322-346 (in Japanese).
8. G. E. P. Box and D. A. Pierce: Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models, J. Amer. Statist. Assoc., vol.65, no. 332 (1970), pp. 1509-1526.