Nominal-Yield-Area Tradeoff in Automatic Synthesis of Analog Circuits: A Genetic Programming Approach using Immune-Inspired Operators

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@InProceedings{Conca:2009:AHS,
  author =       "Piero Conca and Giuseppe Nicosia and 
                 Giovanni Stracquadanio and Jon Timmis",
  title =        "Nominal-Yield-Area Tradeoff in Automatic Synthesis of
                 Analog Circuits: A Genetic Programming Approach using
                 Immune-Inspired Operators",
  booktitle =    "NASA/ESA Conference on Adaptive Hardware and Systems
                 (AHS-2009)",
  year =         "2009",
  editor =       "Tughrul Arslan and Didier Keymeulen",
  pages =        "399--406",
  address =      "San Francisco, California, USA",
  month =        jul # " 29-" # aug # " 1",
  keywords =     "genetic algorithms, genetic programming, AIS, ElP,
                 Pareto Front, analog circuit automatic synthesis,
                 analog circuit design, circuit reliability, elitist
                 immune programming, evolutionary algorithm, frequency
                 response, genetic programming approach, immune-inspired
                 operators, industrial components series, low-pass
                 filter synthesis, nominal-yield-area tradeoff, Pareto
                 optimisation, analogue circuits, circuit CAD, circuit
                 reliability, frequency response, low-pass filters",
  DOI =          "doi:10.1109/AHS.2009.32",
  abstract =     "The synthesis of analog circuits is a complex and
                 expensive task; whilst there are various approaches for
                 the synthesis of digital circuits, analog design is
                 intrinsically more difficult since analog circuits
                 process voltages in a continuous range. In the field of
                 analog circuit design, the genetic programming approach
                 has received great attention, affording the possibility
                 to design and optimize a circuit at the same time.
                 However, these algorithms have limited industrial
                 relevance, since they work with ideal components.
                 Starting from the well known results of Koza and
                 co-authors, we introduce a new evolutionary algorithm,
                 called elitist Immune Programming (EIP), that is able
                 to synthesize an analog circuit using industrial
                 components series in order to produce reliable and low
                 cost circuits. The algorithm has been used for the
                 synthesis of low-pass filters; the results were
                 compared with the genetic programming, and the analysis
                 shows that EIP is able to design better circuits in
                 terms of frequency response and number of components.
                 In addition we conduct a complete yield analysis of the
                 discovered circuits, and discover that EIP circuits
                 attain a higher yield than the circuits generated via a
                 genetic programming approach, and, in particular, the
                 algorithm discovers a Pareto Front which respects
                 nominal performance (sizing), number of components
                 (area) and yield (robustness).",
  notes =        "Co-located with Design Automation Conference
                 (DAC-2009) http://www.see.ed.ac.uk/~ahs2009/ Also known
                 as \cite{5325428}",
}

Genetic Programming entries for Piero Conca Giuseppe Nicosia Giovanni Stracquadanio Jon Timmis

Citations