Generation of a Reconfigurable Logical Cell Using Evolutionary Computation

Abstract

In nature, an interesting topic is about how a cell can be reconfigured in order to achieve a different task. Another interesting topic is about the learning process that seems to be a trial and error process. In this work, we present mechanisms about how to produce a reconfigurable logical cell based on the tent map. The reconfiguration is realized by modifying its internal parameters generating several logical functions in the same structure. The logical cell is built with three blocks: the initial condition generating function, the tent map, and the output function. Furthermore, we propose a reconfigurable structure based on a chaotic system and an evolutionary algorithm is used in order to tune the parameters of the cell via trial and error process.