Evolutionary algorithms for synthesis and optimisation of sequential logic circuits.

Ali, Belgasem (2003) Evolutionary algorithms for synthesis and optimisation of sequential logic circuits. PhD thesis, Edinburgh Napier University.

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    Considerable progress has been made recently 1n the understanding of
    combinational logic optimization. Consequently a large number of university
    and industrial Electric Computing Aided Design (ECAD) programs are now
    available for optimal logic synthesis of combinational circuits. The progress
    with sequential logic synthesis and optimization, on the other hand, is
    considerably less mature.
    In recent years, evolutionary algorithms have been found to be remarkably
    effective way of using computers for solving difficult problems. This thesis is,
    in large part, a concentrated effort to apply this philosophy to the synthesis
    and optimization of sequential circuits.
    A state assignment based on the use of a Genetic Algorithm (GA) for the
    optimal synthesis of sequential circuits is presented. The state assignment
    determines the structure of the sequential circuit realizing the state machine
    and therefore its area and performances. The synthesis based on the GA
    approach produced designs with the smallest area to date. Test results on
    standard fmite state machine (FS:M) benchmarks show that the GA could
    generate state assignments, which required on average 15.44% fewer gates
    and 13.47% fewer literals compared with alternative techniques.
    Hardware evolution is performed through a succeSSlOn of
    changes/reconfigurations of elementary components, inter-connectivity and
    selection of the fittest configurations until the target functionality is reached.
    The thesis presents new approaches, which combine both genetic algorithm
    for state assignment and extrinsic Evolvable Hardware (EHW) to design
    sequential logic circuits. The implemented evolutionary algorithms are able to
    design logic circuits with size and complexity, which have not been
    demonstrated in published work.
    There are still plenty of opportunities to develop this new line of research for
    the synthesis, optimization and test of novel digital, analogue and mixed
    circuits. This should lead to a new generation of Electronic Design
    Automation tools.

    Item Type: Thesis (PhD)
    Additional Information: Appendices on CD not included
    Uncontrolled Keywords: Combinational logic optimisation; Electric Computing Aided Design; evolutionary algorithms; synthesis; sequential circuits; genetic algorithms;
    University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Engineering and the Built Environment
    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: 4338
    Depositing User: Mrs Lyn Gibson
    Date Deposited: 14 Apr 2011 14:48
    Last Modified: 14 Apr 2011 14:48

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