Abstract:This paper presents a new neural architecture suitable for digital signal processing applications. The architecture, based on adaptable multidimensional activation functions, allows to collect information from the previous network layer in aggregate form. In other words the number of network connections (structural complexity) can be very low respect to the problem complexity. This fact, as experimentally demonstrated in the paper, improve the network generalization capabilities and speed up the convergence of… Show more
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