Stochastic time-frequency analysis using the analytic signal: Why the complementary distribution matters

被引:42
作者
Schreier, PJ [1 ]
Scharf, LL
机构
[1] Univ Colorado, Dept Elect & Comp Engn, Boulder, CO 80309 USA
[2] Colorado State Univ, Dept Elect & Comp Engn, Ft Collins, CO 80523 USA
[3] Colorado State Univ, Dept Stat, Ft Collins, CO 80523 USA
关键词
complementary correlation; improper complex random process; interference reduction; nonstationary analytic signal; time-frequency distribution;
D O I
10.1109/TSP.2003.818911
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We challenge the perception that we live in a "proper world where complex random signals can always be assumed to be proper (also called circularly symmetric). Rather, we stress the fact that the analytic signal constructed from a nonstationary real signal is in general improper, which means that its complementary correlation function is nonzero. We explore the consequences of this finding in the context of stochastic time-frequency analysis in Cohen's class. There, the analytic signal plays a prominent role because it reduces interference terms. However, the usual time-frequency representation (TFR) based on the analytic signal gives only an incomplete signal description. It must be augmented by a complementary TFR whose properties are developed in detail in this paper. We show why it is still advantageous to use the pair of standard and complementary TFRs of the analytic signal rather than the TFR of the corresponding real signal.
引用
收藏
页码:3071 / 3079
页数:9
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