Novel HW architecture based on FPGAs oriented to solve the eigen problem

Authors:
Ignacio Bravo;Manuel Mazo;José Luis Lázaro;Pedro Jiménez;Alfredo Gardel;Marta Marrón
Affiliations:
Electronics Department, University of Alcala, Alcalá de Henares, Madrid, Spain;Electronics Department, University of Alcala, Alcalá de Henares, Madrid, Spain;Electronics Department, University of Alcala, Alcalá de Henares, Madrid, Spain;Electronics Department, University of Alcala, Alcalá de Henares, Madrid, Spain;Electronics Department, University of Alcala, Alcalá de Henares, Madrid, Spain;Electronics Department, University of Alcala, Alcalá de Henares, Madrid, Spain
Venue:
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Year:
2008

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Abstract

A hardware solution is presented to obtain the eigenvalues and eigenvectors of a real and symmetrical matrix using field-programmable gate arrays (FPGAs). Currently, this system is used to compute the eigenvalues and eigenvectors in covariance matrices for applications in digital image processing that make use of the principal component analysis (PCA) technique. The proposed solution in this paper is based on the Jacobi method, but in comparison with other related works, it presents a different architecture that remarkably improves execution time, while reducing the number of consumed resources of the FPGA.