Abstract
The so called “super-exponential” algorithms (SEA’s) are attractive algorithms for solving blind signal processing problems. The conventional SEA’s, however, have such a drawback that they are very sensitive to Gaussian noise. To overcome this drawback, we propose a new SEA. While the conventional SEA’s use the second- and higher-order cumulants of observations, the proposed SEA uses only the higher-order cumulants of observations. Since higher-order cumulants are insensitive to Gaussian noise, the proposed SEA is robust to Gaussian noise, which is referred to as a robust super-exponential algorithm (RSEA). The proposed RSEA is implemented as an adaptive algorithm, which is referred to as an adaptive robust super-exponential algorithm (ARSEA). To show the validity of the ARSEA, some simulation results are presented.
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© 2004 Springer-Verlag Berlin Heidelberg
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Ito, M., Ohata, M., Kawamoto, M., Mukai, T., Inouye, Y., Ohnishi, N. (2004). Adaptive Robust Super-exponential Algorithms for Deflationary Blind Equalization of Instantaneous Mixtures. 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_48
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DOI: https://doi.org/10.1007/978-3-540-30110-3_48
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