Explicit construction of recurrent neural networks effectively approximating discrete dynamical systems

• URL: http://arxiv.org/abs/2409.19278v1
• Date: Sat, 28 Sep 2024 07:59:45 GMT
• Title: Explicit construction of recurrent neural networks effectively approximating discrete dynamical systems
• Authors: Chikara Nakayama, Tsuyoshi Yoneda,
• Abstract summary: We consider arbitrary bounded discrete time series originating from dynamical system with recursivity. We provide an explicit construction of recurrent neural networks which effectively approximate the corresponding discrete dynamical systems.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We consider arbitrary bounded discrete time series originating from dynamical system with recursivity. More precisely, we provide an explicit construction of recurrent neural networks which effectively approximate the corresponding discrete dynamical systems.

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