Abstract
Observed signals are usually recorded as linear mixtures of original sources. Our purpose is to separate observed signals into original sources. To analyse observed signals, it is important to use several wavelet functions having different characteristics and compare their continuous wavelet transforms. The notion of the continuous multiwavelet transform and its essentials are introduced. An application to blind image separation is presented.
This work was partially supported by JSPS. KAKENHI (C)26400199 and JSPS. KAKENHI (C)16K05216 of Japan.
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The author would like to thank the anonymous referees for their valuable comments and useful suggestions to improve this paper.
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Ashino, R., Mandai, T., Morimoto, A. (2017). Continuous Multiwavelet Transform for Blind Signal Separation. In: Wong, M., Zhu, H. (eds) Pseudo-Differential Operators: Groups, Geometry and Applications. Trends in Mathematics. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-47512-7_12
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DOI: https://doi.org/10.1007/978-3-319-47512-7_12
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