Poster + Paper
8 November 2024 Spoken digit recognition using optoelectronic reservoir computing based on semiconductor laser with optical feedback
Author Affiliations +
Conference Poster
Abstract
Reservoir Computing (RC) is an Artificial Neural Network (ANNs) that simulates human brain behavior and thinking. As a new type of ANNs, RC does not require training for its reservoir layer, only for the output weights. This simple training method enables RC to be implemented in a physical way. This article successfully builds a time-delayed optical feedback RC system based on semiconductor lasers using the nonlinear characteristics of optics. The system adopts the idea of time division multiplexing, uses the delay loop of optical feedback to construct a reservoir, and sets up a large number of virtual nodes in the feedback loop to replace traditional reservoir nodes. Finally, we successfully implemented spoken digit recognition tasks through this RC system.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Jianglong Zhuang, Guizheng Guan, and Bin Liu "Spoken digit recognition using optoelectronic reservoir computing based on semiconductor laser with optical feedback", Proc. SPIE 13233, Semiconductor Lasers and Applications XIV, 1323315 (8 November 2024); https://doi.org/10.1117/12.3036266
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KEYWORDS
Matrices

Semiconductor lasers

Education and training

Laser optics

Reservoir computing

Transient nonlinear optics

Data processing

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