Title :
Adaptive noise canceller for magnetocardiography
Author :
Tiporlini, Valentina ; Nguyen, Nghia ; Alameh, Kamal
Author_Institution :
Electron Sci. Res. Inst., Edith Cowan Univ., Joondalup, WA, Australia
Abstract :
This paper discusses the use of adaptive noise cancellation in magnetocardiography system within unshielded environment using three algorithms: Least-Mean Squared (LMS) algorithm; normalized LMS (nLMS) algorithm and Genetic Algorithms (GA). Simulation results show that for low signal-to-noise ratio (SNR) values, the GA algorithm outperforms the other algorithms, displaying an improvement in SNR of 51.155 dB and completely suppressing the noise sources at 60 Hz and at low frequencies. However, the convergence time of the GA algorithm is longer due to the high computational complexity.
Keywords :
computational complexity; genetic algorithms; least mean squares methods; magnetocardiography; adaptive noise canceller; computational complexity; frequency 60 Hz; genetic algorithms; least mean squared algorithm; magnetocardiography; normalized LMS algorithm; Indexes; Least squares approximation; Signal to noise ratio; Adaptive noise cancellation; Genetic algorithms; Least-Mean Squared algorithms; Magnetocardiography; Telehealth;
Conference_Titel :
High Capacity Optical Networks and Enabling Technologies (HONET), 2011
Conference_Location :
Riyadh
Print_ISBN :
978-1-4577-1170-1
DOI :
10.1109/HONET.2011.6149770