Reservoir Computing as a Nonlinear Transfer Function Framework

• Collaborators: Andrew Flynn, Francesco Sorrentino
• September 2026 - Present

Characterizing transfer functions for nonlinear systems is challenging due to their complex and input-dependent input-output relationships. In this research, we aim to develop a reservoir computing framework that learns a generalized transfer function for nonlinear systems and can represent their dynamics across diverse and previously unseen input signals.

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