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It has been reported in the literature that cellular neural networks (CNN) are effective as associative memories and they have been applied to many kinds of pattern recognition tasks. Flexibility of their design can be increased by expanding the output function from being 2-valued to being multi-valued. As a design method for associative memories, SVD (singular value decomposition) is popular, but...
Cellular neural networks (CNNs) are one type of interconnected neural network and differ from the well-known Hopfield model in that each cell has a piecewise linear output characteristic. In this paper, we present a multi-valued CNN model in which each nonlinear element consists of a multi-valued output function. The function is defined by a linear combination of piecewise linear functions. We conduct...
Independent Component Analysis (ICA) is a useful method for blind source separation of two signals or more. We have previously proposed a new method combining ICA with the complex discrete wavelet transform (CDWT). In this case, the voice and the noise were separated using a new method. At that time, we used the simulation signal. In this study, we analyze measured biological signals by using this...
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