Reservoir computing, originally referred to as an echo state network or a liquid state machine, is a braininspired paradigm for processing temporal information. It involves learning a "read-out" interpretation for nonlinear transients developed by high-dimensional dynamics when the latter is excited by the information signal to be processed. This novel computational paradigm is derived from recurrent neural network and machine learning techniques. It has recently been implemented in photonic hardware for a dynamical system, which opens the path to ultrafast brain-inspired computing. We report on a novel implementation involving an electro-optic phase-delay dynamics designed with off-the-shelf optoelectronic telecom devices, thus providing the targeted wide bandwidth. Computational efficiency is demonstrated experimentally with speech-recognition tasks. State-of-the-art speed performances reach one million words per second, with very low word error rate. Additionally, to record speed processing, our investigations have revealed computing-efficiency improvements through yet-unexplored temporalinformation-processing techniques, such as simultaneous multisample injection and pitched sampling at the read-out compared to information "write-in".

Relaxation oscillation frequency is produced when a laser is operated in the low laser threshold current region. In this operation region, a semiconductor laser shows a smooth curve, where we can observe uncertainty into defining the onset of laser oscillation. Relaxation oscillations in the laser intensity can be seen as sidebands on both sides of the main laser line. In this context, a communication system by using a relaxation oscillation frequency as an information carrier is proposed in this paper. The experimental setup is based on operation principle of direct detection, where the obtained microwave signal at the output of a fast photodetector is located on C band and it is modulated with an analog NTSC TV signal.

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