Journal ArticleDOI
State assignment of finite state machines using a genetic algorithm
A.E.A. Almaini,Julian F. Miller,P. Thomson,S. Billina +3 more
- Vol. 142, Iss: 4, pp 279-286
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TLDR
In this article, the use of genetic algorithms for the generation of optimal state assignments for synchronous finite state machines (FSM) is proposed, and the resulting state assignments are better than or at least as good as those produced by SPECTRAL, NOVA and MUSTANG and also closed partition assignments.Abstract:
The use of genetic algorithms for the generation of optimal state assignments for synchronous finite state machines (FSM) is proposed. Results are presented to show that, in all examples attempted, the resulting state assignments are better than or at least as good as those produced by SPECTRAL, NOVA and MUSTANG and also closed partition assignments. On average, the genetic algorithm produced assignments with 33% less logic than the best produced by other algorithms.read more
Citations
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Journal ArticleDOI
Metaheuristics: A bibliography
Ibrahim H. Osman,Gilbert Laporte +1 more
TL;DR: This bibliography provides a classification of a comprehensive list of 1380 references on the theory and application of metaheuristics that have had widespread successes in attacking a variety of difficult combinatorial optimization problems that arise in many practical areas.
Journal ArticleDOI
Genetic algorithm based state assignment for power and area optimisation
Yinshui Xia,A E A Almaini +1 more
TL;DR: In this article, two cost functions are introduced and a genetic algorithm is used to optimise the cost functions, and experimental results show a significant reduction of switching activity without area penalty or with smaller area penalty than previous publications.
Journal ArticleDOI
Binary particle swarm optimization (BPSO) based state assignment for area minimization of sequential circuits
TL;DR: An improved binary particle swarm optimization (BPSO) algorithm is proposed and its effectiveness in solving the state assignment problem in sequential circuit synthesis targeting area optimization is demonstrated.
Journal ArticleDOI
Evolutionary Algorithms and Theirs Use in the Design of Sequential Logic Circuits
TL;DR: An approach based on an evolutionary algorithm to design synchronous sequential logic circuits with minimum number of logic gates is suggested and the obtained results compare favourably against those produced by manual methods and other methods based on heuristic techniques.
Proceedings ArticleDOI
GALLOP: genetic algorithm based low power FSM synthesis by simultaneous partitioning and state assignment
TL;DR: This paper presents a GA based approach for simultaneous partitioning and state assignment of finite state machines with power reduction as the objective and results obtained compare favorably with previous works on FSM partitioning, low power state assignment as well as using GA for partitioning alone.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Journal ArticleDOI
NOVA: state assignment of finite state machines for optimal two-level logic implementation
TL;DR: The problem of encoding the states of a synchronous finite state machine so that the area of a two-level implementation of the combinational logic is minimized is addressed using algorithms based on a novel theoretical framework that offers advantages over previous approaches to develop effective heuristics.
Journal ArticleDOI
MUSTANG: state assignment of finite state machines targeting multilevel logic implementations
TL;DR: The authors present state-assignment algorithms that heuristically maximize the number of common cubes in the encoded network to maximize theNumber of literals in the resulting combinational logic network after multilevel logic optimization.
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Genetic algorithm based state assignment for power and area optimisation
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