Feed forward neural network approach for reversible logic circuit simulation in QCA

Abstract

Quantum dot Cellular Automata (QCA) is becoming a new paradigm in nanoscale computing. Artificial Neural Network model is a promising model to design and simulate QCA circuits. This study proposes a new approach to design, model and simulate small circuit as well as large circuit. Feed Forward Neural Network (FFNN) model is used to design and simulate the reversible circuit as well as conservative circuit. The simulation result of this proposed FFNN model gives better result than exhaustive simulation of QCADesigner.