Resonance for Analog Recurrent Neural Network

There is a strong interest in using physical waves for artificial neuralcomputing because of their unique advantages in fast speed and intrinsicparallelism. Resonance, as a ubiquitous feature across many wave systems, is anatural candidate for analog computing in temporal signals. We demonstrate thatresonance can be used to construct stable and scalable recurrent neural networks.By including resonators with different lifetimes, the computing system developsboth short-term and long-term memories simultaneously

Automated summary

There is a strong interest in using physical waves for artificial neural computing due to their fast speed and intrinsic parallelism. Resonance, a common feature in many wave systems, is a natural choice for analog computing in temporal signals. This study demonstrates that resonance can be utilized to construct stable and scalable recurrent neural networks. By incorporating resonators with different lifetimes, the computing system can develop both short-term and long-term memories simultaneously.