Recurrent Neural Networks (RNNs) are a type of neural network architecture designed to handle sequential data by introducing recurrent connections. RNNs are well-suited for tasks such as natural language processing and time series prediction.
We experimentally demonstrated the real-time operation of a photonic neuron with a self-connection, a prerequisite for integrated recurrent neural networks (RNNs). After studying two applications, we propose a photonics-assisted platform for time series prediction and classification.
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