Basic Learning Characteristics of Digital Spike Maps
نویسندگان
چکیده
Abstract—This paper studies learning algorithm of the digital spike maps. The map is equivalent to a simple one-dimensional cellular automaton and can generate various digital spike-trains. In order to approximate a class of spike-trains, we present a learning algorithm with selforganizing function. Performing a basic numerical experiment, we have clarified that the map can learn a typical class of teacher signals. The results contribute to bridge between spiking neural systems and digital dynamical systems.
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تاریخ انتشار 2010