JACIII Vol.11 No.9 pp. 1122-1127
doi: 10.20965/jaciii.2007.p1122


Computational Intelligence in Circuit Synthesis

Cecília Reis and J. A. Tenreiro Machado

Institute of Engineering of Porto / GECAD, Rua Dr. António Bernardino de Almeida, Porto, Portugal

March 13, 2007
June 14, 2007
November 20, 2007
computational intelligence, evolutionary algorithms, swarm intelligence, logic circuits design
This paper is devoted to the synthesis of combinational logic circuits through computational intelligence or, more precisely, using evolutionary computation techniques. Are studied two evolutionary algorithms, the Genetic and the Memetic Algorithm (GAs, MAs) and one swarm intelligence algorithm, the Particle Swarm Optimization (PSO). GAs are optimization and search techniques based on the principles of genetics and natural selection. MAs are evolutionary algorithms that include a stage of individual optimization as part of its search strategy, being the individual optimization in the form of a local search. The PSO is a population-based search algorithm that starts with a population of random solutions called particles. This paper presents the results for digital circuits design using the three above algorithms. The results show the statistical characteristics of this algorithms with respect to the number of generations required to achieve the solutions. The article analyzes also a new fitness function that includes an error discontinuity measure, which demonstrated to improve significantly the performance of the algorithm.
Cite this article as:
C. Reis and J. Machado, “Computational Intelligence in Circuit Synthesis,” J. Adv. Comput. Intell. Intell. Inform., Vol.11 No.9, pp. 1122-1127, 2007.
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