Title :
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
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;
Conference_Titel :
Communications, Computers and Signal Processing, 1993., IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
0-7803-0971-5
DOI :
10.1109/PACRIM.1993.407273