Author

L. Minati

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Preprint Oct 2026

Quantum extreme learning for forecasting experimental chaotic electronic circuits

Quantum reservoir computing and its special case, quantum extreme learning, are powerful tools for predicting classical discrete time-series with quantum devices. Forecasting continuous signals, however, requires careful discretization as oversampling artificially boosts short-term accuracy but fails over realistic int...

Mohammad Sharifian, Qing-Yu Li, Chiranjib Mukhopadhyay et al. · 0 citations

Open access Jul 2026

Brain-inspired reservoir computing framework for complex time-series prediction

A brain-inspired neural network-based echo state network (BINN-ESN) that uses a modified continuous coupled neural network (MCCNN) as the neural model, which is inspired by the mammalian visual cortex for time-series prediction.

Pei Ma, Xu-Bin Wang, Hanshuo Qiu et al. · iScience · 0 citations

Jul 2026

Enhancing epileptic seizure detection via augmentation of electroencephalography (EEG) signals using a single-transistor chaotic oscillator

This data augmentation improves the dimensionality of the EEG dataset, thus improving feature extraction and classification accuracy for various sub-bands of EEG signals, including delta, theta, alpha, beta, and raw signals.

Zeric Njitacke Tabekoueng, Longxiang Fu, Yi Zhang et al. · Nonlinear dynamics · 0 citations