Design of a New Optimized Universal Logic Gate for Quantum-Dot Cellular Automata

Abstract

In this paper, the design of a novel efficient QCA-based universal logic gate (ULG) is presented. Compact and efficient implementation layout with only one clock phase delay and also the implementation of the 13 standard functions without extra ULG or gate are the advantages of the proposed ULG. The results show that the proposed ULG is an efficient tool in designing any QCA circuit. Also, an accurate artificial neural network (ANN) model of the proposed ULG is presented. This model can be simply imported into any circuit simulators such as HSPICE, MATLAB Simulink and etc., for modeling and simulation of QCA circuits at the Gate level with high precision in a short time.

KEYWORDS:

• Artificial neural network
• Modeling
• QCADesigner
• Quantum-dot cellular automata
• Simulation
• Universal logic gate

Additional information

Notes on contributors

Mohsen Hayati

Mohsen Hayati received the BE degree in electronics and communication engineering from Nagarjuna University, Andhra Pradesh, India, in 1985, and the ME and PhD degrees in electronics engineering from Delhi University, Delhi, India, in 1987 and 1992, respectively. He joined the Electrical Engineering Department, Razi University, Kermanshah, Iran, as an assistant pofessor in 1993. Currently, he is a professor with the Electrical Engineering Department, Faculty of Engineering, Razi University. He has published more than 215 papers in international, domestic journals, and conferences. His current research interests include microwave and millimeter wave devices and circuits, application of computational intelligence, artificial neural networks, fuzzy systems, neuro-fuzzy systems, electronic circuit synthesis, modeling and simulations.

Abbas Rezaei

Abbas Rezaei, assistant professor of electrical engineering in Kermanshah University of Technology. Abbas Rezaei received the BSc, MSc and PhD in electronics engineering from Razi University, Kermanshah, Iran, in 2005, 2009 and 2013, respectively. His current research interests include computational intelligence, microstrip devices and nanotechnology. Email: [email protected]; [email protected]