Title :
Second-order statistics of complex signals
Author :
Picinbono, Bernard ; Bondon, Pascal
Author_Institution :
Lab. des Signaux et Syst., CNRS, Gif-sur-Yvette, France
fDate :
2/1/1997 12:00:00 AM
Abstract :
The second-order statistical properties of complex signals are usually characterized by the covariance function. However, this is not sufficient for a complete second-order description, and it is necessary to introduce another moment called the relation function. Its properties, and especially the conditions that it must satisfy, are analyzed both for stationary and nonstationary signals. This leads to a new perspective concerning the concept of complex white noise as well as the modeling of any signal as the output of a linear system driven by a white noise. Finally, this is applied to complex autoregressive signals, and it is shown that the classical prediction problem must be reformulated when the relation function is taken into consideration
Keywords :
autoregressive processes; prediction theory; signal processing; statistical analysis; white noise; complex autoregressive signals; complex signals; complex white noise; linear system; nonstationary signals; prediction problem; relation function; second-order statistical properties; stationary nonstationary signals; Bonding; Linear systems; Narrowband; Radio frequency; Radiofrequency identification; Sampling methods; Signal analysis; Statistics; Transfer functions; White noise;
Journal_Title :
Signal Processing, IEEE Transactions on