A Mott Insulator-Based Oscillator Circuit for Reservoir Computing

In this work, we use a Cr-doped V2O3 based Mott oscillator circuit to build a reservoir computing system that has much smaller model size than an equivalent LSTM. In contrast to an LSTM, our reservoir computing system can be trained very efficiently and on-line, with very low latency. We demonstrate close to state-of-the-art performance with three benchmark tasks: speech recognition, handwritten digit recognition, and HDD channel decoding. We show that our Mott circuit-based reservoir computing system brings significant reduction in power consumption and inference speed compared to CPU, GPU, or FPGA based systems.