Chaotic dynamics matching for learning to identify biological signals by higher order artificial neural circuit

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Chaotic dynamics matching which can be applied for a dynamics of the control systems with high-speed and flexibly according to the condition and the task based on the chaos theory is proposed. It achieves the control and learning system based on biological signals. The following results were achieved. Stable method of chaotic dynamics matching which is effective to continuous-time signal as biological signals was shown. Systematic design procedure of learning to identify signals based on higher order spike neuron was shown and the effectiveness was clarified.