Abstract
Abstract
Optical neuoromorphic technologies enable neural network-based signal processing through a specifically designed hardware and may confer advantages in speed and energy. However, the advances of such technologies in bandwidth and/or dimensionality are often limited by the constraints of the underlying material. Optical fiber presents a well-studied low-cost solution with unique advantages for low-loss high-speed signal processing. The fiber echo state network analogue (FESNA), fiber-based neuromorphic processor, has been the first technology suitable for multichannel high bandwidth (including THz) and dual-quadrature signal processing. Here we propose the multidimensional FESNA (MD-FESNA) processing by utilizing multi-mode fiber non-linearity. Thus, the developed MD-FESNA is the first neuromorphic technology which augments all aforementioned advantages of FESNA with multidimensional spatio-temporal processing. We demonstrate the performance and flexibility of the technology on the example of prediction tasks for hyperchaotic systems. These results will pave the way for a high-speed neuromorphic processing of multidimensional tasks, hardware for spatio-temporal neural networks and open new application venues for fiber-based spatio-temporal multiplexing.
Funder
Royal Academy of Engineering
Subject
Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials
Cited by
10 articles.
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