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The Backtracking Search for the Optimal Design of Low-Noise Amplifiers

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Computational Intelligence in Analog and Mixed-Signal (AMS) and Radio-Frequency (RF) Circuit Design

Abstract

The backtracking search algorithm (BSA) was recently developed. It is an evolutionary algorithm for real-valued optimization problems. The main feature of BSA vis-à-vis other known evolutionary algorithms is that it has a single control parameter. It has also been shown that it has a better convergence behavior. In this chapter, the authors deal with the application of BSA to the optimal design of RF circuits, namely low-noise amplifiers. BSA performance, viz. robustness and speed, are checked against the widely used particle swarm optimization technique, and other published approaches. ADS simulation results are given to show the viability of the obtained results.

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Author information

Authors and Affiliations

  1. National School of Electronics and Telecommunications of Sfax, University of Sfax, Sfax, Tunisia

    Amel Garbaya & Mourad Fakhfakh

  2. High School of Sciences and Technologies of Hammam Sousse, University of Sousse, Sousse, Tunisia

    Mouna Kotti

  3. Laboratoire LiSSi (EA 3956), Université Paris-Est Créteil, Vitry-sur-Seine, Créteil, France

    Patrick Siarry

Authors
  1. Amel Garbaya
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  2. Mouna Kotti
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  3. Mourad Fakhfakh
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  4. Patrick Siarry
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Corresponding author

Correspondence to Amel Garbaya .

Editor information

Editors and Affiliations

  1. Department of Electronics, ENET'Com, University of Sfax, Sfax, Tunisia

    Mourad Fakhfakh

  2. Dept. of Electronics, INAOE, Tonantzintla, Puebla, Mexico

    Esteban Tlelo-Cuautle

  3. Laboratory LiSSi (EA 3956), Université Paris-Est Créteil, Vitry-sur-Seine, France

    Patrick Siarry

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Garbaya, A., Kotti, M., Fakhfakh, M., Siarry, P. (2015). The Backtracking Search for the Optimal Design of Low-Noise Amplifiers. In: Fakhfakh, M., Tlelo-Cuautle, E., Siarry, P. (eds) Computational Intelligence in Analog and Mixed-Signal (AMS) and Radio-Frequency (RF) Circuit Design. Springer, Cham. https://doi.org/10.1007/978-3-319-19872-9_14

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  • DOI: https://doi.org/10.1007/978-3-319-19872-9_14

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-19872-9

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