A systolic architecture for spectrometric data correction based on Kalman-spline and LMS filters

Author

Sakkay, Kamal ; Massicotte, Daniel ; Barwicz, Andrzej

Author_Institution

Dept. of Electr. Eng., Quebec Univ., Trois-Rivieres, Que., Canada

Volume

1

fYear

1998

fDate

24-28 May 1998

Firstpage

357

Abstract

This paper presents a VLSI implementation of a systolic array architecture for spectrometric measurement data correction using Kalman-spline and LMS filters. The simplicity and regularity of such architecture make it very attractive for VLSI implementation. The design of the processing element and the decision block is explicitly addressed. Synthetic data is used to validate the design and evaluate performance with respect to computing time and accuracy

Keywords

Kalman filters; VLSI; digital arithmetic; digital filters; least mean squares methods; spectrometers; splines (mathematics); systolic arrays; DSP56001; Kalman-spline filter; LMS filter; VLSI implementation; accuracy; computing time; decision block; digital signal processing; matrix arithmetic; performance evaluation; processing element; regular architecture; spectrometric data correction; synthetic data; systolic array architecture; Approximation algorithms; Convolution; Filtering; Kalman filters; Least squares approximation; Signal processing algorithms; Spectroscopy; Spline; State estimation; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 1998. IEEE Canadian Conference on

Conference_Location

Waterloo, Ont.

ISSN

0840-7789

Print_ISBN

0-7803-4314-X

Type

conf

DOI

10.1109/CCECE.1998.682758

Filename

682758