@inproceedings{1cdb1186d9a246359edc695d601e1bf7,
title = "Detection and Classification of ECG Chaotic Components Using ANN Trained by Specially Simulated Data",
abstract = "This paper presents the use of simulated ECG signals with known chaotic and random noise combination for training of an Artificial Neural Network (ANN) as a classification tool for analysis of chaotic ECG components. Preliminary results show about 85% overall accuracy in the ability to classify signals into two types of chaotic maps - logistic and Henon. Robustness to random noise is also presented. Future research in the form of raw data analysis is proposed, and further features analysis is needed.",
keywords = "Artificial Neural Networks, Deterministic chaos, ECG",
author = "Polina Kurtser and Ofer Levi and Vladimir Gontar",
note = "Copyright: Copyright 2013 Elsevier B.V., All rights reserved.; 2012 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2012 ; Conference date: 26-10-2012 Through 28-10-2012",
year = "2012",
doi = "10.1007/978-3-642-32909-8_20",
language = "אנגלית",
isbn = "9783642329081",
series = "Communications in Computer and Information Science",
pages = "193--202",
editor = "Shigang Yue and Lazaros Iliadis",
booktitle = "Engineering Applications of Neural Networks - 13th International Conference, EANN 2012, Proceedings",
}