Title :
Fast two-dimensional adaptive IIR algorithms
Author :
Soni, Robert A. ; Jenkins, W. Kenneth
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL, USA
Abstract :
Several new two-dimensional adaptive infinite-impulse response (IIR) filtering algorithms are derived and simulated. These new algorithms are based upon the one-dimensional version of the algorithm developed by Fan and Jenkins (1986). This algorithm was shown to experimentally possess the ability to converge to the global minimum of the mean square error (MSE) even in cases where the MSE surface is ill-conditioned. In addition, further enhancements to this new algorithm were made to improve convergence rate performance. An estimate of the Hessian is incorporated into the adaptive filter coefficient update expressions. Least Mean Square (LMS), Recursive Least Square (RLS), Gauss-Newton (GN), and Fast Quasi-Newton (FQN) forms of the two-dimensional Fan-Jenkins algorithm are formulated and compared via simulation for several examples
Keywords :
Hessian matrices; IIR filters; Newton method; adaptive filters; convergence of numerical methods; filtering theory; least mean squares methods; recursive estimation; 2D Fan-Jenkins algorithm; Gauss-Newton form; IIR filtering algorithms; LMS; MSE; RLS; adaptive filter coefficient update; convergence rate performance; fast 2D adaptive IIR algorithms; fast quasi-Newton form; global minimum; infinite-impulse response; least mean square form; mean square error; recursive least square form; two-dimensional IIR algorithms; Adaptive filters; Convergence; Filtering algorithms; Finite impulse response filter; IIR filters; Least squares methods; Mean square error methods; Newton method; Recursive estimation; Signal processing algorithms;
Conference_Titel :
Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-3073-0
DOI :
10.1109/ISCAS.1996.541822
