Abstract
In this paper, an algorithm for eliminating extreme values and reducing the estimation variance of an integrated trispectrum under low signal-to-noise ratio and short data sample conditions is presented. An analysis of the results of simulations using this algorithm and comparison with the conventional power spectrum and integrated trispectrum methods are presented.
Similar content being viewed by others
References
L. M. Garth, H. V. Poor, Detection of non-Gaussian signals: A paradigm for modern statistical signal processing, Proc. IEEE, 82(1994)7, 1060–1095.
J. M. Mendel, Tutorial on higher-order statistics (spectra) in signal processing and system theory: Theoretical results and some applications, Proc. IEEE, 79(1991)3, 278–305.
T. F. Andre, R. D. Nowak, B. D. Van Veen, Low-rank estimation of higher order statistics, IEEE Trans. on Signal Processing, 45(1997)3, 673–685.
C. L. Nikias, J. M. Mendel, Signal processing with higher-order spectra, IEEE Signal Processing Magazine, 10(1993)7, 10–37.
J. K. Tugnait, Detection of non-Gaussian signals using integrated polyspectrum, IEEE Trans. on Signal Processing, 42(1994)11, 3137–3149.
Y. Shen, Y. Liu, Elimination of wild values in complex data for threshold estimation of signal detection, Modern Radar, 21(1999)3, 39–43, (in Chinese).
Author information
Authors and Affiliations
Additional information
Supported by the National Natural Science Foundation of China under Grant No.60072027
About this article
Cite this article
Liang, Z., Liu, X. & Liu, Y. An elimination algorithm of extreme values for integrated trispectrum. J. of Electron.(China) 19, 146–151 (2002). https://doi.org/10.1007/s11767-002-0026-y
Issue Date:
DOI: https://doi.org/10.1007/s11767-002-0026-y