Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Modeling QCA for area minimization in logic synthesis
Proceedings of the 13th ACM Great Lakes symposium on VLSI
The effects of a new technology on the design, organization, and architectures of computing systems
The effects of a new technology on the design, organization, and architectures of computing systems
Towards Designing Robust QCA Architectures in the Presence of Sneak Noise Paths
Proceedings of the conference on Design, Automation and Test in Europe - Volume 2
Modeling quantum dot devices in Cell-DEVS environment
Proceedings of the 2008 Spring simulation multiconference
Design and simulation of a QCA 2 to 1 multiplexer
ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
A comparative analysis and design of quantum-dot cellular automata memory cell architecture
International Journal of Circuit Theory and Applications
Multi-objective optimization of QCA circuits with multiple outputs using genetic programming
Genetic Programming and Evolvable Machines
| Hi-index | 14.98 |
CMOS technology miniaturization limits have promoted research on new alternatives which can keep the technologically advanced level of the last decades. Quantum-dot Cellular Automata (QCA) is a new technology in the nanometer scale that has been considered as one of these alternatives. QCA have a large potential in the development of circuits with high space density and low heat dissipation and allow the development of faster computers with lower power consumption. Differently from conventional technologies, QCA do not codify information by means of electric current flow, but rather by the configuration of electrical charges in the interior of the cells. The Coulomb interaction between cells is responsible for the flow of information. This paper proposes the use of computational intelligence techniques in the simulation and in the automatic synthesis of QCA circuits. The first results show that these techniques may play an important role in this research area since they are capable of simulating efficiently and fast, synthesizing optimized circuits with a reduced number of cells. Such optimization reduces the possibility of failures and guarantees higher speed.