Title :
Identification of cubic systems using higher order moments of i.i.d. signals
Author :
Tseng, Ching-Hsiang ; Powers, Edward J.
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas Univ., Austin, TX, USA
fDate :
7/1/1995 12:00:00 AM
Abstract :
A simple method for estimating the Volterra kernels of cubic systems with a zero-mean i.i.d. input is presented. This method significantly reduces the computational complexity of Volterra kernel estimation compared to the non-i.i.d. and non-Gaussian input case
Keywords :
Volterra series; computational complexity; nonlinear systems; parameter estimation; signal processing; Volterra kernel estimation; Volterra kernels; computational complexity; cubic systems; higher order moments; identification; iid signals; independent identically distributed input; zero-mean iid input; Communication channels; Computational complexity; Delay effects; Echo cancellers; Equations; Kernel; Signal processing; Signal processing algorithms; Sparse matrices; Symmetric matrices;
Journal_Title :
Signal Processing, IEEE Transactions on
