Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7621
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dc.contributor.authorCheang, Sin Manen_US
dc.contributor.authorLee, Kin Hongen_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.date.accessioned2023-03-28T03:37:41Z-
dc.date.available2023-03-28T03:37:41Z-
dc.date.issued2004-
dc.identifier.citationEuropean Conference on Genetic Programming, 2004, pp. 23 - 34.en_US
dc.identifier.isbn978-354021346-8-
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7621-
dc.description.abstractGenetic Parallel Programming (GPP) is a novel Genetic Programming paradigm. The GPP Accelerating Phenomenon, i.e. parallel programs are easier to be evolved than sequential programs, opens up a new approach to evolve solution programs in parallel forms. Based on the GPP paradigm, we developed a combinational digital circuit learning system, the GPP+MLP system. An optimal Multiple Logic Unit Processor (MLP) is designed to evaluate genetic parallel programs. To show the effectiveness of the proposed GPP+MLP system, four multi-output Binary arithmetic circuits are used. Experimental results show that both the gate counts and the propagation gate delays of the evolved_circuits are less than conventional designs. For example, in a 3-bit multiplier experiment, we obtained a combinational digital circuit with 26 two-input logic gates in 6 gate levels. It utilizes 4 gates less than a conventional design. © Springer-Verlag 2004.en_US
dc.language.isoenen_US
dc.publisherSpringer Verlagen_US
dc.titleDesigning optimal combinational digital circuits using a multiple logic unit processoren_US
dc.typeConference Paperen_US
dc.relation.conferenceEuropean Conference on Genetic Programmingen_US
dc.identifier.doi10.1007/978-3-540-24650-3_3-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
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