<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ignacio Bravo</style></author><author><style face="normal" font="default" size="100%">Manuel Mazo</style></author><author><style face="normal" font="default" size="100%">Jose L. Lazaro</style></author><author><style face="normal" font="default" size="100%">Pedro Jimenez</style></author><author><style face="normal" font="default" size="100%">Alfredo Gardel</style></author><author><style face="normal" font="default" size="100%">Marta Marron</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Novel HW architecture based on FPGAs oriented to solve the eigen problem</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Transactions on very large scale integration (VLSI) systems</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">CORDIC</style></keyword><keyword><style  face="normal" font="default" size="100%">eigenvalue</style></keyword><keyword><style  face="normal" font="default" size="100%">eigenvector</style></keyword><keyword><style  face="normal" font="default" size="100%">field-programmable gate array (FPGA)</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2008</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&amp;arnumber=4668632&amp;isnumber=4668626</style></url></web-urls><related-urls><url><style face="normal" font="default" size="100%">https://geintra-uah.org/system/files/novelHWEigen2008.pdf</style></url></related-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Estados Unidos</style></pub-location><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">1722-1725</style></pages><language><style face="normal" font="default" size="100%">English</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span class=&quot;sectionHeaders&quot;&gt;Abstract&lt;/span&gt;&lt;br /&gt;
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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><accession-num><style face="normal" font="default" size="100%">1.010</style></accession-num><call-num><style face="normal" font="default" size="100%">ENGINEERING, ELECTRICAL &amp; ELECTRONIC</style></call-num></record></records></xml>