Neural computation of alpha parameter with the use of differential gain, wavelength, and number of quantum wells

Fatih V. Celebi; Kenan Danisman; Remzi Yildirim

doi:10.1117/12.523297

25 March 2004 Neural computation of alpha parameter with the use of differential gain, wavelength, and number of quantum wells

Fatih V. Celebi, Kenan Danisman, Remzi Yildirim

Author Affiliations +

Proceedings Volume 5277, Photonics: Design, Technology, and Packaging; (2004) https://doi.org/10.1117/12.523297
Event: Microelectronics, MEMS, and Nanotechnology, 2003, Perth, Australia

Abstract

A different method to determine α (Alpha) parameter for different number of Quantum-wells is presented. The Levenberg-Marquardt algorithm is used to train the Artificial Neural Networks (ANNs) which has a quadratic speed of convergence. Both the computed and the test results are in very good agreement with the experimental results reported elsewhere.

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Fatih V. Celebi, Kenan Danisman, and Remzi Yildirim "Neural computation of alpha parameter with the use of differential gain, wavelength, and number of quantum wells", Proc. SPIE 5277, Photonics: Design, Technology, and Packaging, (25 March 2004); https://doi.org/10.1117/12.523297

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