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An Advanced Clonal Selection Algorithm with Ad-Hoc Network-Based Hypermutation Operators for Synthesis of Topology and Sizing of Analog Electrical Circuits

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Artificial Immune Systems (ICARIS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5132))

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Abstract

In electronics, there are two major classes of circuits, analog and digital electrical circuits. While digital circuits use discrete voltage levels, analog circuits use a continuous range of voltage. The synthesis of analog circuits is known to be a complex optimization task, due to the continuous behaviour of the output and the lack of automatic design tools; actually, the design process is almost entirely demanded to the engineers. In this research work, we introduce a new clonal selection algorithm, the elitist Immune Programming, (eIP) which uses a new class of hypermutation operators and a network-based coding. The eIP algorithm is designed for the synthesis of topology and sizing of analog electrical circuits; in particular, it has been used for the design of passive filters. To assess the effectiveness of the designed algorithm, the obtained results have been compared with the passive filter discovered by Koza and co-authors using the Genetic Programming (GP) algorithm. The circuits obtained by eIP algorithm are better than the one found by GP in terms of frequency response and number of components required to build it.

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Peter J. Bentley Doheon Lee Sungwon Jung

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Ciccazzo, A., Conca, P., Nicosia, G., Stracquadanio, G. (2008). An Advanced Clonal Selection Algorithm with Ad-Hoc Network-Based Hypermutation Operators for Synthesis of Topology and Sizing of Analog Electrical Circuits. In: Bentley, P.J., Lee, D., Jung, S. (eds) Artificial Immune Systems. ICARIS 2008. Lecture Notes in Computer Science, vol 5132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85072-4_6

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  • DOI: https://doi.org/10.1007/978-3-540-85072-4_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85071-7

  • Online ISBN: 978-3-540-85072-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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