TY  - JOUR
SP  - 5563
Y1  - 2020/10/15/
EP  - 5573
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
IS  - 20
VL  - 38
A1  - Parsonson, CWF
A1  - Shabka, Z
A1  - Chlupka, WK
A1  - Goh, B
A1  - Zervas, G
JF  - Journal of Lightwave Technology
UR  - https://doi.org/10.1109/JLT.2020.3004645
PB  - IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
N2  - Novel approaches to switching ultra-fast semiconductor optical amplifiers using artificial intelligence algorithms (particle swarm optimisation, ant colony optimisation, and a genetic algorithm) are developed and applied both in simulation and experiment. Effective off-on switching (settling) times of 542 ps are demonstrated with just 4.8% overshoot, achieving an order of magnitude improvement over previous attempts described in the literature and standard dampening techniques from control theory.
AV  - public
KW  - Ant colony optimisation
KW  -  artificial intelligence
KW  -  data centre networks
KW  -  genetic algorithm
KW  -  optical interconnects
KW  -  optical networks
KW  -  optical switching
KW  -  particle swarm optimisation
KW  -  semiconductor optical amplifiers
ID  - discovery10113485
TI  - Optimal Control of SOAs With Artificial Intelligence for Sub-Nanosecond Optical Switching
ER  -