| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 1.94 MB | Adobe PDF |
Advisor(s)
Abstract(s)
This paper is devoted to the synthesis of combinational logic circuits through computacional intelligence or, more precisely, using 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 os genetics and natural selection. MAs are evolutionary algorithms that include a stage of individual optimization as part of its search algorithm that starts with 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 generatons required to archieve the solutions. The article analyzes also a new fitness, function that includes an error discontinuity measure, which demonstrated to improved significantly the performance of the algorithm.
Description
Keywords
Computational intelligence Evolutionary algorithms Swarm intelligence Logic circuits design