Comparison of four parallel algorithms for systolic array processing

Author

Tang, D.Q. ; Yeh, H.-G.

Author_Institution

Dept. of Electr. Eng., California State Univ., Long Beach, CA, USA

Volume

2

fYear

1993

fDate

19-21 May 1993

Firstpage

666

Abstract

Four parallel algorithms for solving least square estimation problems are studied. They are the recursive modified Gram-Schmidt (RMGS) algorithm, the a priori error recursive modified Gram-Schmidt (PERGS) algorithm, and the Given rotation with and without using square root operator (GRWSR and GRWOSR) algorithms. These algorithms based on orthogonal transformation provide a complete solution to the least squares estimation problem. They are highly reliable and have a highly modular structure suitable for systolic array implementation. The designed VLSI systolic array chip can provide a high throughput

Keywords

VLSI; digital signal processing chips; least squares approximations; parallel algorithms; recursive estimation; software reliability; structured programming; systolic arrays; VLSI systolic array chip; least squares estimation; modular structure; orthogonal transformation; parallel algorithms; recursive modified Gram-Schmidt algorithm; rotation; square root operator; systolic array processing; throughput; Adaptive filters; Adaptive signal processing; Array signal processing; Equations; Least squares approximation; Matrices; Parallel algorithms; Signal processing algorithms; Systolic arrays; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications, Computers and Signal Processing, 1993., IEEE Pacific Rim Conference on

Conference_Location

Victoria, BC

Print_ISBN

0-7803-0971-5

Type

conf

DOI

10.1109/PACRIM.1993.407273

Filename

407273