Abstract
In this work, we perform the numerical investigation of the performance of the small optical reservoir computing (RC) systems with four neurons using the commercial software for optical fiber communication system. The small optical RC system consists of the components of the optical fiber communication. The nonlinear function which is required in RC is provided by the erbium-doped optical fiber amplifiers (EDFA). We demonstrate that the EDFA should be operated in the saturated or non-linear regime to obtain a better performance of the small optical RC system. The performance of the small optical RC systems for different topological neuron structures is investigated. The results show that the interconnection between the neurons could offer a better performance than the systems without interconnection between the neurons. Moreover, the input signals with different noise levels are launched into the systems. The results show that the small optical RC system can classify the noisy input optical waveforms even when the signal-to-noise ratio is as low as − 2.55 dB.
Highlights
In Refs.[12,18], a non-trivial classification task is applied in the optical RC system using amplifiers and semiconductor optical amplifiers (SOA), respectively, to recognize the rectangular and triangular waveforms
As the power of the input optical signals of the small optical RC systems is higher than 7 W, the normalized root mean square error (NRMSE) is almost constant where the erbium-doped fiber amplifier (EDFA) operates in the saturated regime
The small optical reservoir computing system based on optical fiber communication system has been proposed
Summary
In Refs.[12,18], a non-trivial classification task is applied in the optical RC system using amplifiers and semiconductor optical amplifiers (SOA), respectively, to recognize the rectangular and triangular waveforms. To study the performance of the small optical RC system for the different operation regimes in EDFA, the power of the input optical signal of the laser is varied from 0.5 to 15 W.
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