Abstract
This paper presents a novel method for independent component analysis (ICA) with reference signal. Instead of choosing the initial weight vector randomly as in other algorithms, our method employs the maximum correlation criterion to select the initial weight vector deliberately and uses FastICA to find the desired solution. No extra parameters are involved in ICA with reference by our method which is superior to some other algorithms.
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Mi, JX., Gui, J. (2010). A Method for ICA with Reference Signals. In: Huang, DS., Zhang, X., Reyes GarcÃa, C.A., Zhang, L. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2010. Lecture Notes in Computer Science(), vol 6216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14932-0_20
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DOI: https://doi.org/10.1007/978-3-642-14932-0_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14931-3
Online ISBN: 978-3-642-14932-0
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