An iterative quadratic technique for designing minimum phase filters

Author

Rasmussen, James L. ; Etter, Delores M.

Author_Institution

Dept. of Electr. & Comput. Eng., Colorado Univ., Boulder, CO, USA

Volume

1

fYear

1994

fDate

31 Oct-2 Nov 1994

Firstpage

309

Abstract

An adaptive convex filter (ACF) consists of a parallel bank of three fixed second-order filters. The output of each fixed filter is multiplied by a constrained weight. The fixed filters are chosen such that the ACF will always be minimum phase. Higher order filters are implemented by cascading ACF stages but this cascaded system does not have a quadratic error surface when updated using traditional algorithms. We present an algorithm that has a quadratic error surface for the ACF and converges to the global minimum

Keywords

adaptive filters; adaptive signal processing; band-pass filters; cascade networks; convergence of numerical methods; filtering theory; iterative methods; adaptive convex filter; cascaded system; constrained weight; convergence; fixed second-order filters; global minimum; higher order filters; iterative quadratic technique; minimum phase filters design; parallel filter bank; quadratic error surface; updating algorithms; Adaptive filters; Convolution; Error correction; Finite impulse response filter; Hydrogen; IIR filters; System identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 1994. 1994 Conference Record of the Twenty-Eighth Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

0-8186-6405-3

Type

conf

DOI

10.1109/ACSSC.1994.471466

Filename

471466