Title :
On the identifiability of a quadratic stochastic system
Author_Institution :
Lab. des Signaux et Systemes, CNRS, Gif-sur-Yvette, France
Abstract :
Quadratic systems are the simplest nonlinear time-invariant systems and correspond to the second term of the Volterra expansion. Such systems appear in various fields of signal processing, in particular in detection and estimation. The author studies the identifiability of a discrete and finite extent quadratic stochastic system, driven by a sequence of independent, identically distributed random variables. When the input is available, the system is identified using cross-cumulants between the input and the output. When the input is unobservable, only the output cumulants up to the third-order are considered.
Keywords :
identification; nonlinear systems; signal processing; statistical analysis; stochastic systems; cross-cumulants; identifiability; independent identically distributed random variables; nonlinear time-invariant systems; output cumulants; quadratic stochastic system; signal processing; Bonding; Echo cancellers; Gaussian processes; Kernel; Noise cancellation; Nonlinear systems; Random variables; Signal processing; Statistics; Stochastic systems;
Conference_Titel :
Higher-Order Statistics, 1993., IEEE Signal Processing Workshop on
Conference_Location :
South Lake Tahoe, CA, USA
Print_ISBN :
0-7803-1238-4
DOI :
10.1109/HOST.1993.264599