Abstract
This work explains a new method for blind separation of a linear mixture of sources, based on geometrical considerations concerning the observation space. This new method is applied to a mixture of several sources and it obtains the estimated coefficients of the unknown mixture matrix A and separates the unknown sources. In this work, the principles of the new method and a description of the algorithm are shown.
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Rodríguez-Álvarez, M., Rojas Ruiz, F., Martín-Clemente, R., Rojas Ruiz, I., Puntonet, C.G. (2004). Geometrical ICA-Based Method for Blind Separation of Super-Gaussian Signals. In: Puntonet, C.G., Prieto, A. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2004. Lecture Notes in Computer Science, vol 3195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30110-3_45
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DOI: https://doi.org/10.1007/978-3-540-30110-3_45
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