Parallel physical reservoir computing (RC) overcomes some obstacles of the single RC,
including issues related to large-scale processing and limited performance. In this work, we …

Reservoir computing is a machine learning algorithm for processing time dependent data
which is well suited for experimental implementation. Tuning the hyperparameters of the …

An approach for simultaneous modulation format identification (MFI) and optical signal-to-
noise ratio (OSNR) monitoring in digital coherent optical communications is proposed based …

We propose and numerically demonstrate a novel performance enhancement optical
reservoir computing (RC) system based on a three-loop mutual coupling electro-optical …

Reservoir computing capitalizes on the high-dimensional responses of a nonlinear
dynamical system, it creates a high-dimensional temporal expansion of the input signal …

In this paper, a novel performance enhancement reservoir computing (RC) system based on
the combination of vertical-cavity surface emitting laser (VCSEL) optical feedback and …

An optical amplification-free deep reservoir computing (RC)-assisted high-baudrate intensity
modulation direct detection (IM/DD) system is experimentally demonstrated using a 100G …

In this article, we propose and numerically demonstrate a novel security performance
enhancement electro-optical (EO) phase chaotic communication (ENRCP) system based on …

Reservoir Computing (RC), an evolution from Recurrent Neural Networks (RNN), not only
represents a unique machine learning paradigm, but also serves as a neuromorphic …

Current perception and monitoring systems, such as human recognition, are affected by
several environmental factors, such as limited light intensity, weather changes, occlusion of …