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Una-May O'Reilly. Terry, Michael A. (Michael Allen) Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2006-07-13T15:18:43Z 2006-07-13T15:18:43Z 2005 2005 http://hdl.handle.net/1721.1/33368 62521782 Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005. Includes bibliographical references (p. 57-60). This thesis describes the design and implementation of the Genetic Programming Intrinsic Circuit (GPIC) design system. Inspired by a number of recent advances in the field of Evolvable Hardware, the intended purpose of GPIC is to automate the design of analog circuits with minimal domain knowledge, computational resources, and cost using Genetic Programming with candidate solutions implemented in real hardware. This system has been constructed out of commercially available hardware and software, and the components were integrated through the development of a modular device-independent software system. The fitness evaluations of the candidate solutions of the Genetic Programming module are realized through a C interface to a National Instruments Data Acquisition Card. This Genetic Programming approach to analog circuit design decreases the fitness evaluation time of previous approaches by substituting expensive circuit simulation for real-time hardware testing. Since performing fitness evaluations in simulation is limited by the known model for a given environment, intrinsic testing provides additional benefit through the inherent incorporation of any unknown environmental conditions during tests. This feature is especially important for autonomous systems in unknown environments, and systems that must perform well in extreme environments. by Michael A. Terry. M.Eng. 60 p. 3204369 bytes 3206778 bytes application/pdf application/pdf eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Evolving circuits on a field programmable analog array using genetic programming Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="53625f2d-9f65-4502-a7a0-3d74eb50f3fa"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Evolving circuits on a field programmable analog array using genetic programming</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2005</PublicationDate> <Authors> <Author> <DisplayName>Terry, Michael A. (Michael Allen)</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>This thesis describes the design and implementation of the Genetic Programming Intrinsic Circuit (GPIC) design system. Inspired by a number of recent advances in the field of Evolvable Hardware, the intended purpose of GPIC is to automate the design of analog circuits with minimal domain knowledge, computational resources, and cost using Genetic Programming with candidate solutions implemented in real hardware. This system has been constructed out of commercially available hardware and software, and the components were integrated through the development of a modular device-independent software system. The fitness evaluations of the candidate solutions of the Genetic Programming module are realized through a C interface to a National Instruments Data Acquisition Card. This Genetic Programming approach to analog circuit design decreases the fitness evaluation time of previous approaches by substituting expensive circuit simulation for real-time hardware testing. Since performing fitness evaluations in simulation is limited by the known model for a given environment, intrinsic testing provides additional benefit through the inherent incorporation of any unknown environmental conditions during tests. This feature is especially important for autonomous systems in unknown environments, and systems that must perform well in extreme environments.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>