title: Photonic nonlinear transient computing with multiple-delay wavelength dynamics.
abstract: We report on the experimental demonstration of a hybrid optoelectronic neuromorphic computer based on a complex nonlinear wavelength dynamics including multiple delayed feedbacks with randomly defined weights. This neuromorphic approach is based on a new paradigm of a brain-inspired computational unit, intrinsically differing from Turing machines. This recent paradigm consists in expanding the input information to be processed into a higher dimensional phase space, through the nonlinear transient response of a complex dynamics excited by the input information. The computed output is then extracted via a linear separation of the transient trajectory in the complex phase space. The hyperplane separation is derived from a learning phase consisting of the resolution of a regression problem. The processing capability originates from the nonlinear transient, resulting in nonlinear transient computing. The computational performance is successfully evaluated on a standard benchmark test, namely, a spoken digit recognition task.
authors.affiliation: UMR CNRS FEMTO-ST 6174/Optics Department, University of Franche-Comté, 16 Route de Gray, 25030 Besançon Cedex, France.
authors.forename: Romain
authors.initials: R
authors.lastname: Martinenghi
authors.forename: Sergei
authors.initials: S
authors.lastname: Rybalko
authors.forename: Maxime
authors.initials: M
authors.lastname: Jacquot
authors.forename: Yanne K
authors.initials: YK
authors.lastname: Chembo
authors.forename: Laurent
authors.initials: L
authors.lastname: Larger
mesh_terms: D001921:Brain / Q000502:physiology; D009415:Nerve Net; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D055095:Optics and Photonics