<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Joshi, Aniruddha</style></author><author><style face="normal" font="default" size="100%">Rajshekhar</style></author><author><style face="normal" font="default" size="100%">Chandran, S.</style></author><author><style face="normal" font="default" size="100%">Phadke, S.</style></author><author><style face="normal" font="default" size="100%">Jayaraman, Valadi K.</style></author><author><style face="normal" font="default" size="100%">Kulkarni, B. D.</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Pal, S. K.</style></author><author><style face="normal" font="default" size="100%">Bandyopadhyay, Sanjoy</style></author><author><style face="normal" font="default" size="100%">Biswas, S.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Arrhythmia classification using local Holder exponents and support vector machine</style></title><secondary-title><style face="normal" font="default" size="100%">1st International Conference on Pattern Recognition and Machine Intelligence</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">LECTURE NOTES IN COMPUTER SCIENCE</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Springer-Verlag Berlin, Heidelberger Platz 3, D-14197 Berlin, Germany</style></publisher><pub-location><style face="normal" font="default" size="100%"> Statist Inst. Kolkata, India</style></pub-location><volume><style face="normal" font="default" size="100%">3776</style></volume><pages><style face="normal" font="default" size="100%">242-247</style></pages><isbn><style face="normal" font="default" size="100%">3-540-30506-8</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We propose a novel hybrid Holder-SVM detection algorithm for arrhythmia classification. The Holder exponents are computed efficiently using the wavelet transform modulus maxima (WTMM) method. The hybrid system performance is evaluated using the benchmark MIT-BIH arrhythmia database. The implemented model classifies 160 of Normal sinus rhythm, 25 of Ventricular bigeminy, 155 of Atrial fibrillation and 146 of Nodal (A-V junctional) rhythm with 96.94% accuracy. The distinct scaling properties of different types of heart rhythms may be of clinical importance.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">1st International Conference on Pattern Recognition and Machine Intelligence, Statist Inst Kolkata, Kolkata, INDIA, DEC 20-22, 2005</style></notes></record></records></xml>