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Combinational Circuit Design with Estimation of Distribution Algorithms

Combinational Circuit Design with Estimation of Distribution Algorithms

Sergio Ivvan Valdez Peña, Arturo Hernández Aguirre, Salvador Botello Rionda, Cyntia Araiza Delgado
Copyright: © 2010 |Pages: 17
ISBN13: 9781605667058|ISBN10: 1605667056|ISBN13 Softcover: 9781616924188|EISBN13: 9781605667065
DOI: 10.4018/978-1-60566-705-8.ch012
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MLA

Valdez Peña, Sergio Ivvan, et al. "Combinational Circuit Design with Estimation of Distribution Algorithms." Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering, edited by Raymond Chiong, IGI Global, 2010, pp. 281-297. https://doi.org/10.4018/978-1-60566-705-8.ch012

APA

Valdez Peña, S. I., Aguirre, A. H., Rionda, S. B., & Delgado, C. A. (2010). Combinational Circuit Design with Estimation of Distribution Algorithms. In R. Chiong (Ed.), Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering (pp. 281-297). IGI Global. https://doi.org/10.4018/978-1-60566-705-8.ch012

Chicago

Valdez Peña, Sergio Ivvan, et al. "Combinational Circuit Design with Estimation of Distribution Algorithms." In Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering, edited by Raymond Chiong, 281-297. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-60566-705-8.ch012

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Abstract

The authors introduce new approaches for the combinational circuit design based on Estimation of Distribution Algorithms. In this paradigm, the structure and data dependencies embedded in the data (population of candidate circuits) are modeled by a conditional probability distribution function. The new population is simulated from the probability model thus inheriting the dependencies. The authors explain the procedure to build an approximation of the probability distribution through two approaches: polytrees and Bayesian networks. A set of circuit design experiments is performed and a comparison with evolutionary approaches is reported.

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