<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Carlos Matos</style></author><author><style face="normal" font="default" size="100%">Manuel Duarte Ortigueira</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fractional Filters: An Optimization Approach</style></title><secondary-title><style face="normal" font="default" size="100%">Emerging Trends in Technological Innovation</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">IFIP Advances in Information and Communication Technology</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://oa.uninova.pt/4755/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">314</style></volume><pages><style face="normal" font="default" size="100%">361–366</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The design and optimization of fractional filters is considered in this paper. Some of the classic filter architectures are presented and their performances relatively to an ideal amplitude spectrum evaluated. The fractional filters are designed using the differential evolution optimization algorithm for computing their parameters. To evaluate the performances of all the filters the quadratic error between the computed amplitude is calculated against an ideal (goal) response. The fractional filters have a better behavior, both in the pass and reject-band.&lt;/p&gt;
</style></abstract><notes><style face="normal" font="default" size="100%">n/a</style></notes></record></records></xml>