パルス形ハードウェアカオスニューロンモデルを用いた嗅覚中枢の振動パターン生成

概要

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Oscillatory patterns of electrical activity are a ubiquitous feature in nervous systems. Oscillatory patterns play an important role in the processing of sensory information pattern recognition. For example, earlier reports describe that the oscillatory patterns in the olfactory center of the land slug are changed by odor stimuli to the tentacles. Olfactory processing has also been studied in relation to rabbits and land slugs through the construction and use of mathematical neural network models. However, a large-scale model is necessary for the study of a model which has sensory information recognition by the oscillatory pattern. Therefore, the construction of a hardware model that can generate oscillatory patterns is desired because nonlinear operations can be processed at higher speeds than the mathematical model. We are studying about the neural network using hardware neuron models to construct the olfactory center model of the living organisms. In the present study, we discuss about the oscillatory pattern generation of the olfactory center using pulse-type hardware chaotic neuron models. Our model shows periodic, quasi-periodic and chaotic oscillations such as the olfactory center of living organisms by changing the synaptic connection weights.