Recursive implementation of statistically-optimal null filters

Author

Agarwal, Rajeev ; Plotkin, E.I. ; Swamy, M.N.S.

Author_Institution

Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que., Canada

Volume

2

fYear

1996

fDate

12-15 May 1996

Firstpage

245

Abstract

Statistically-optimal null filters (SONFs), based on the combination of the maximum output SNR and the least-squares criteria, have been recently presented in literature. Orthogonality of the basis functions used in the series representation of the signal in question plays a key role in the implementation of such filters. In this paper, we first present the globally-optimal SONF, wherein the orthogonalization procedure is not necessary and then show how it can be implemented recursively. Simulation results are presented comparing the Gram-Schmidt (GS)-orthogonalized SONF, recursive SONF and the constrained notch filter (CNF). Ability of the SONFs to process short duration signals is emphasized

Keywords

circuit optimisation; least squares approximations; notch filters; recursive filters; Gram-Schmidt SONF; basis function orthogonality; constrained notch filter; globally-optimal SONF; least-squares criteria; maximum output SNR; recursive SONF; series representation; short duration signals; statistically-optimal null filters; Matched filters; Niobium; Noise figure; Parametric statistics; Signal processing; Signal to noise ratio;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ISCAS.1996.540398

Filename

540398