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State assignment for sequential circuits using multi-objective genetic algorithm.

Al-Jassani, ban Adil, Urquhart, Neil B and Almaini, A E A (2011) State assignment for sequential circuits using multi-objective genetic algorithm. IET Computers & Digital Techniques, 5 (4). pp. 296-305. ISSN 1751-8601

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    Abstract/Description

    In this study, a new approach using a multi-objective genetic algorithm (MOGA) is proposed to determine the optimal state assignment with less area and power dissipations for completely and incompletely specified sequential circuits. The goal is to find the best assignments which reduce the component count and switching activity. The MOGA employs a Pareto ranking scheme and produces a set of state assignments, which are optimal in both objectives. The ESPRESSO tool is used to optimise the combinational parts of the sequential circuits. Experimental results are given using a personal computer with an Intel CPU of 2.4 GHz and 2 GB RAM. The algorithm is implemented using C++ and fully tested with benchmark examples. The experimental results show that saving in components and switching activity are achieved in most of the benchmarks tested compared with recent published research.

    Item Type: Article
    Print ISSN: 1751-8601
    Electronic ISSN: 1751-861X
    Uncontrolled Keywords: multiobjective genetic algorithm; component count; switching activity; Pareto ranking scheme; state assignments; ESPRESSO tool; combinational parts; power dissipations; incompletely specified sequential circuits; completely specified sequential circuits
    University Divisions/Research Centres: Edinburgh Napier University, Institute for Informatics and Digital Innovation
    Dewey Decimal Subjects: 600 Technology > 620 Engineering > 621 Electronic & mechanical engineering > 621.3 Electrical & electronic engineering
    Library of Congress Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
    Item ID: 4423
    Depositing User: Computing Research
    Date Deposited: 31 May 2011 11:47
    Last Modified: 29 Nov 2012 10:01
    URI: http://researchrepository.napier.ac.uk/id/eprint/4423

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