Demonstration of a distributed feedback laser diode working as a graded-potential-signaling photonic neuron and its application to neuromorphic information processing
Тип публикации: Journal Article
Дата публикации: 2020-05-09
scimago Q1
wos Q1
БС1
SJR: 1.479
CiteScore: 12.6
Impact factor: 7.6
ISSN: 1674733X, 18691919
General Computer Science
Краткое описание
We find that a commonly-used distributed feedback laser diode (DFB-LD) can work as a graded-potential-signaling photonic neuron. Through theoretical and experimental demonstration, DFB-LDs are proved useful for three graded-potential-signaling-based neuromorphic processing applications of the pattern recognition, the single-wavelength implementation of spike timing dependent plasticity (STDP), and the sound azimuth measurement. The pattern recognition with a full-width-at-half-maximum (FWHM) of 1 μs is realized in the experiment.
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Ma B., Zou W. Demonstration of a distributed feedback laser diode working as a graded-potential-signaling photonic neuron and its application to neuromorphic information processing // Science China Information Sciences. 2020. Vol. 63. No. 6. 160408
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Ma B., Zou W. Demonstration of a distributed feedback laser diode working as a graded-potential-signaling photonic neuron and its application to neuromorphic information processing // Science China Information Sciences. 2020. Vol. 63. No. 6. 160408
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TY - JOUR
DO - 10.1007/s11432-020-2887-6
UR - https://doi.org/10.1007/s11432-020-2887-6
TI - Demonstration of a distributed feedback laser diode working as a graded-potential-signaling photonic neuron and its application to neuromorphic information processing
T2 - Science China Information Sciences
AU - Ma, Bowen
AU - Zou, Weiwen
PY - 2020
DA - 2020/05/09
PB - Science in China Press
IS - 6
VL - 63
SN - 1674-733X
SN - 1869-1919
ER -
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@article{2020_Ma,
author = {Bowen Ma and Weiwen Zou},
title = {Demonstration of a distributed feedback laser diode working as a graded-potential-signaling photonic neuron and its application to neuromorphic information processing},
journal = {Science China Information Sciences},
year = {2020},
volume = {63},
publisher = {Science in China Press},
month = {may},
url = {https://doi.org/10.1007/s11432-020-2887-6},
number = {6},
pages = {160408},
doi = {10.1007/s11432-020-2887-6}
}