Abstract
This paper derives a new algorithm that performs independent component analysis (ICA) by optimizing the contrast function of the RADICAL algorithm. The core idea of the proposed optimization method is to combine the global search of a good initial condition with a gradient-descent algorithm. This new ICA algorithm performs faster than the RADICAL algorithm (based on Jacobi rotations) while still preserving, and even enhancing, the strong robustness properties that result from its contrast.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
References
Comon, P.: Independent Component Analysis, a new concept (Special issue on Higher-Order Statistics). In: Signal Processing, vol. 36(3), pp. 287–314. Elsevier, Amsterdam (1994)
Learned-Miller, E.G., Fisher III, J.W.: ICA using spacings estimates of entropy. Journal of Machine Learning Research 4, 1271–1295 (2003)
Cover, T.M., Thomas, J.A.: Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing). Wiley-Interscience, Chichester (2006)
Liebermeister, W.: Linear modes of gene expression determined by independent component analysis. Bioinformatics 18, 51–60 (2002)
Absil, P.-A., Mahony, R., Sepulchre, R.: Optimization Algorithms on Matrix Manifolds. Princeton University Press (to appear)
Journée, M., Teschendorff, A.E., Absil, P.-A., Sepulchre, R.: Geometric optim. methods for ICA applied on gene expression data. In: Proc. of ICASSP (2007)
Cardoso, J.-F.: High-order contrasts for independent component analysis. Neural Computation 11(1), 157–192 (1999)
Hyvärinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. John Wiley & Sons, Chichester (2001)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Journée, M., Absil, PA., Sepulchre, R. (2007). Optimization on the Orthogonal Group for Independent Component Analysis. In: Davies, M.E., James, C.J., Abdallah, S.A., Plumbley, M.D. (eds) Independent Component Analysis and Signal Separation. ICA 2007. Lecture Notes in Computer Science, vol 4666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74494-8_8
Download citation
DOI: https://doi.org/10.1007/978-3-540-74494-8_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74493-1
Online ISBN: 978-3-540-74494-8
eBook Packages: Computer ScienceComputer Science (R0)