Abstract
The purpose of blind source separation is to separate and to estimate the original sources from the sensor array, without knowing the transmission channel characteristics. Besides methods based on independent component analysis which is one of the most powerful tools for blind source separation, several methods based on time-frequency analysis have been proposed. One of them is the quotient signal estimation method which can estimate the unknown number of sources. The notion of the continuous multiwavelet transform is introduced and three types of multiwavelets are presented. A new method using continuous multiwavelet transform, position-scale information matrices and self-organizing maps, is presented and applied to image source separations with noise. The performance of three multiwavelets are compared.
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Acknowledgements
Thanks are due to the anonymous reviewers whose deep and extensive comments greatly contributed to improve this article. This work was partially supported by JSPS.KAKENHI (C)20540168, (C)20540193, (C)22540130, (C)23540135 of Japan.