Performance improvement of in-materio reservoir computing by noise injection

Abstract

Computation performance of in-materio reservoir device was evaluated by varying intensity of noise injection. Materials for the reservoir device was synthesized using a α-Fe2O3/titanium bismuth oxide composite by using the sol–gel method. The prepared samples were characterized by conducting X-ray diffractmetry, transmission electron microscopy, and energy dispersive X-ray spectroscopy to confirm presence of α-Fe2O3, TiO2, and Bi4Ti3O12 nanoparticles. The I–V and V–t curves show nonlinearity, and phase differences between input and output signals, and the fast Fourier transform of the V–t curve showed high harmonics at the input sine wave with 11 Hz of frequency. In the waveform prediction task, the prediction accuracy was improved only when a small intensity of white noise voltage was superimposed to the input information signal.