scholarly journals Measurement of optical intensity fluctuation over an 118 km turbulent path

2008 ◽  
Vol 16 (10) ◽  
pp. 6963 ◽  
Author(s):  
Yijun Jiang ◽  
Jing Ma ◽  
Liying Tan ◽  
Siyuan Yu ◽  
Wenhe Du
Keyword(s):  
Intensity Fluctuation ◽  
Optical Intensity

scholarly journals All-optical intensity fluctuation magnification using Kerr effect

2020 ◽  
Vol 28 (3) ◽  
pp. 3789 ◽  
Author(s):  
Benoit Vanus ◽  
Chams Baker ◽  
Liang Chen ◽  
Xiaoyi Bao
Keyword(s):  
Kerr Effect ◽  
Intensity Fluctuation ◽  
Optical Intensity ◽  
All Optical

scholarly journals Optical Axons for Electro-Optical Neural Networks

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6119
Author(s):  
Mircea Hulea ◽  
Zabih Ghassemlooy ◽  
Sujan Rajbhandari ◽  
Othman Isam Younus ◽  
Alexandru Barleanu
Keyword(s):  
Neural Networks ◽  
Optical Signal ◽  
Sensor Data ◽  
Line Of Sight ◽  
Optical Intensity ◽  
Digital Signals ◽  
Link Length ◽  
Optical Neural Networks ◽  
Analogue Signals ◽  
Neural Unit

Recently, neuromorphic sensors, which convert analogue signals to spiking frequencies, have been reported for neurorobotics. In bio-inspired systems these sensors are connected to the main neural unit to perform post-processing of the sensor data. The performance of spiking neural networks has been improved using optical synapses, which offer parallel communications between the distanced neural areas but are sensitive to the intensity variations of the optical signal. For systems with several neuromorphic sensors, which are connected optically to the main unit, the use of optical synapses is not an advantage. To address this, in this paper we propose and experimentally verify optical axons with synapses activated optically using digital signals. The synaptic weights are encoded by the energy of the stimuli, which are then optically transmitted independently. We show that the optical intensity fluctuations and link’s misalignment result in delay in activation of the synapses. For the proposed optical axon, we have demonstrated line of sight transmission over a maximum link length of 190 cm with a delay of 8 μs. Furthermore, we show the axon delay as a function of the illuminance using a fitted model for which the root mean square error (RMS) similarity is 0.95.

Influence of intensity fluctuation on exercise metabolism

2007 ◽  
Vol 100 (3) ◽  
pp. 253-260 ◽  
Author(s):  
Jie Kang ◽  
Gerald T. Mangine ◽  
Nicholas A. Ratamess ◽  
Avery D. Faigenbaum ◽  
Jay R. Hoffman
Keyword(s):  
Intensity Fluctuation ◽  
Exercise Metabolism
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