%0 Book Section %1 Aggarwal:2006:GPTP %A Aggarwal, Varun %A O'Reilly, Una-May %B Genetic Programming Theory and Practice IV %C Ann Arbor %D 2006 %E Riolo, Rick L. %E Soule, Terence %E Worzel, Bill %I Springer %K algorithms, circuit genetic geometric models, posynomial programming programming, regression, sizing, symbolic %P - %T Design of Posynomial Models for Mosfets: Symbolic Regression Using Genetic Algorithms %U http://people.csail.mit.edu/unamay/publications-dir/gptp06.pdf %V 5 %X Starting from a broad description of analogue circuit design in terms of topology design and sizing, we discuss the difficulties of sizing and describe approaches that are manual or automatic. These approaches make use of blackbox optimisation techniques such as evolutionary algorithms or convex optimization techniques such as geometric programming. Geometric programming requires posynomial expressions for a circuit's performance measurements. We show how a genetic algorithm can be exploited to evolve a polynomial expression (i.e. model) of transistor (i.e. mosfet) behaviour more accurately than statistical techniques in the literature. %& 7 %@ 0-387-33375-4

@incollection{Aggarwal:2006:GPTP, abstract = {Starting from a broad description of analogue circuit design in terms of topology design and sizing, we discuss the difficulties of sizing and describe approaches that are manual or automatic. These approaches make use of blackbox optimisation techniques such as evolutionary algorithms or convex optimization techniques such as geometric programming. Geometric programming requires posynomial expressions for a circuit's performance measurements. We show how a genetic algorithm can be exploited to evolve a polynomial expression (i.e. model) of transistor (i.e. mosfet) behaviour more accurately than statistical techniques in the literature.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Ann Arbor}, author = {Aggarwal, Varun and O'Reilly, Una-May}, biburl = {https://www.bibsonomy.org/bibtex/2612339d955c5e836cdbcfa6fde1a0700/brazovayeye}, booktitle = {Genetic Programming Theory and Practice {IV}}, chapter = 7, editor = {Riolo, Rick L. and Soule, Terence and Worzel, Bill}, interhash = {f7b6b77f67f90184292c971e809d52ca}, intrahash = {612339d955c5e836cdbcfa6fde1a0700}, isbn = {0-387-33375-4}, keywords = {algorithms, circuit genetic geometric models, posynomial programming programming, regression, sizing, symbolic}, month = {11-13 May}, notes = {part of \cite{Riolo:2006:GPTP} Published Jan 2007 after the workshop}, pages = {-}, publisher = {Springer}, series = {Genetic and Evolutionary Computation}, size = {19 pages}, timestamp = {2008-06-19T17:35:15.000+0200}, title = {Design of Posynomial Models for Mosfets: Symbolic Regression Using Genetic Algorithms}, url = {http://people.csail.mit.edu/unamay/publications-dir/gptp06.pdf}, volume = 5, year = 2006 }