DocumentCode
1609255
Title
A multi-layer perseptron network model for a quantum-well laser diode
Author
Celebi, Fatih V. ; Danisman, Kenan
Author_Institution
Fac. of Eng., Baskent Univ., Ankara, Turkey
fYear
2006
Firstpage
1
Lastpage
4
Abstract
This study presents a different approach to compute the modal peak gain, differential modal refractive index change, and the linewidth enhancement factor (alpha parameter) of an InGaAs deep quantum-well laser sample from a single model. Each of these optical quantities requires many calculations with the use of different theories, assumptions, and estimations in addition to strong background knowledge. The approach is based on artificial neural networks (ANNs) which are capable of representing complex input/output relationship. The model results agree well with the measured data from an InGaAs quantum-well (QW) laser sample.
Keywords
III-V semiconductors; gallium arsenide; indium compounds; multilayer perceptrons; optical computing; quantum well lasers; InGaAs; artificial neural networks; differential modal refractive index; linewidth enhancement factor; multilayer perceptron network model; quantum-well laser diode; Artificial neural networks; Diodes; Estimation theory; Indium gallium arsenide; Optical computing; Optical refraction; Optical variables control; Quantum computing; Quantum well lasers; Refractive index;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing & Informatics, 2006. ICOCI '06. International Conference on
Conference_Location
Kuala Lumpur
Print_ISBN
978-1-4244-0219-9
Electronic_ISBN
978-1-4244-0220-5
Type
conf
DOI
10.1109/ICOCI.2006.5276510
Filename
5276510
Link To Document