Two New Approaches of Independent Component Analysis
作者： V. Salai Selvam , S. Shenbagadevi , V. Padhma , D. Sujatha , R. Sharmila
DOI: 10.1007/978-3-642-29216-3_55
关键词:
摘要: In many practical applications or experiments the signals of interest are often recorded at a sampling rate much higher than required Nyquist (twice signal bandwidth interest), resulting redundant and irrelevant information in data. This causes ICA process to “concede” some source components consume more processing time memory. The methods proposed overcome these problems. performances first evaluated using inference-to-signal ratios (ISRs) correlations (CRs) between simulated their estimates obtained by direct application speed convergence (SOC) ICA. Then tested real scalp EEG records as well.
springer.com
sci-hub.st 参考文章(19)
Hans-Georg Stark, Wavelets and Signal Processing: An Application-Based Introduction ,(2005)
Nadia Mammone, Bruno Azzerboni, Francesco Carlo Morabito, Fabio La Foresta, A New Approach Based On Wavelet-ICA Algorithms For Fetal Electrocardiogram Extraction the european symposium on artificial neural networks. pp. 193- 198 ,(2005)
Aapo Hyvärinen, The Fixed-Point Algorithm and Maximum Likelihood Estimation forIndependent Component Analysis Neural Processing Letters. ,vol. 10, pp. 1- 5 ,(1999) , 10.1023/A:1018647011077
John G. Proakis, Dimitris G. Manolakis, Digital Signal Processing: Principles, Algorithms, and Applications ,(1992)
Bruno Azzerboni, Giovanni Finocchio, Maurizio Ipsale, Fabio La Foresta, Francesco Carlo Morabito, A New Approach to Detection of Muscle Activation by Independent Component Analysis and Wavelet Transform italian workshop on neural nets. pp. 109- 116 ,(2002) , 10.1007/3-540-45808-5_11
Pierre Comon, Christian Jutten, Handbook of Blind Source Separation: Independent Component Analysis and Applications Academic Press. pp. 831- ,(2010)
Nick Yeung, Rafal Bogacz, Clay B. Holroyd, Jonathan D. Cohen, Detection of synchronized oscillations in the electroencephalogram: An evaluation of methods Psychophysiology. ,vol. 41, pp. 822- 832 ,(2004) , 10.1111/J.1469-8986.2004.00239.X
Sergiy Vorobyov, Andrzej Cichocki, Blind noise reduction for multisensory signals using ICA and subspace filtering, with application to EEG analysis. Biological Cybernetics. ,vol. 86, pp. 293- 303 ,(2002) , 10.1007/S00422-001-0298-6
M. Unser, T. Blu, Wavelet theory demystified IEEE Transactions on Signal Processing. ,vol. 51, pp. 470- 483 ,(2003) , 10.1109/TSP.2002.807000
V. S. Selvam, S. Shenbagadevi, Brain tumor detection using scalp eeg with modified Wavelet-ICA and multi layer feed forward neural network international conference of the ieee engineering in medicine and biology society. ,vol. 2011, pp. 6104- 6109 ,(2011) , 10.1109/IEMBS.2011.6091508