Title :
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
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;
Conference_Titel :
Electrical and Computer Engineering, 1998. IEEE Canadian Conference on
Conference_Location :
Waterloo, Ont.
Print_ISBN :
0-7803-4314-X
DOI :
10.1109/CCECE.1998.682758
