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RF-LNA circuit synthesis by genetic algorithm-specified artificial neural network

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Dumesnil, Etienne, Nabki, Frederic et Boukadoum, Mounir. 2015. « RF-LNA circuit synthesis by genetic algorithm-specified artificial neural network ». In 2014 21st IEEE International Conference on Electronics, Circuits and Systems (ICECS) (Marseille, France, Dec. 7-10, 2014), pp. 758-761. Institute of Electrical and Electronics Engineers Inc..
Compte des citations dans Scopus : 1.

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Abstract

A genetic algorithm (GA) was used to determine the optimal architecture and input parameters of a feed-forward artificial neural network (ANN), the purpose of which was to synthesize a radio-frequency, low noise amplifier (RF-LNA) circuit. The parameters (chromosomes) processed by the GA included: i) the LNA performance specifications and design constraints; ii) the type of ANN to use multi-layer perceptron (MLP) or radial-basis function (RBF) network; iii) the ANN parameters to set. For two different sets of design parameters, the input/output matching network components and transistor geometries, the GA found ANN solutions capable of predicting their values with success rates above 99 %.

Item Type: Conference proceeding
Professor:
Professor
Nabki, Frédéric
Affiliation: Autres
Date Deposited: 13 Jul 2016 18:05
Last Modified: 15 Dec 2016 21:52
URI: https://espace2.etsmtl.ca/id/eprint/13216

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