Classification of Arrhythmia Types Using Cartesian Genetic Programming Evolved Artificial Neural Networks

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{conf/eann/AhmadKM13,

• author = "Arbab Masood Ahmad and Gul Muhammad Khan and Sahibzada Ali Mahmud",
• title = "Classification of Arrhythmia Types Using Cartesian Genetic Programming Evolved Artificial Neural Networks",
• editor = "Lazaros S. Iliadis and Harris Papadopoulos and Chrisina Jayne",
• booktitle = "Proceedings of 14th International Conference on Engineering Applications of Neural Networks (EANN 2013), Part {I}",
• year = "2013",
• volume = "383",
• series = "Communications in Computer and Information Science",
• pages = "282--291",
• address = "Halkidiki, Greece",
• month = sep # " 13-16",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, cartesian genetic programming, CGPANN, artificial neural network, neuro-evolution, CVD, cardiac arrhythmias, classification, fiducial points, LBBB beats, RBBB beats",
• isbn13 = "978-3-642-41012-3",
• bibdate = "2014-01-25",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/eann/eann2013-1.html#AhmadKM13",
• URL = "http://dx.doi.org/10.1007/978-3-642-41013-0",
• DOI = "doi:10.1007/978-3-642-41013-0_29",
• abstract = "Cartesian Genetic programming Evolved Artificial Neural Network (CGPANN) is explored for classification of different types of arrhythmia and presented in this paper. Electrocardiography (ECG) signal is preprocessed to acquire important parameters and then presented to the classifier. The parameters are calculated from the location and amplitudes of ECG fiducial points, determined with a new algorithm inspired by Pan-Tompkins's algorithm [14]. The classification results are satisfactory and better than contemporary methods introduced in the field.",

}

Genetic Programming entries for Arbab Masood Ahmad Gul Muhammad Khan Sahibzada Ali Mahmud

Citations