An efficient design of serial and parallel memory using Quantum dot cellular automata

Author(s):  
Sandip Kumar Roy ◽  
Preeta Sharan ◽  
Nalini R. ◽  
T. Srinivas
Optik ◽  
2016 ◽  
Vol 127 (15) ◽  
pp. 6172-6182 ◽  
Author(s):  
Trailokya Nath Sasamal ◽  
Ashutosh Kumar Singh ◽  
Anand Mohan

2018 ◽  
Vol 57 (11) ◽  
pp. 3419-3428 ◽  
Author(s):  
Ali Newaz Bahar ◽  
Radhouane Laajimi ◽  
Md. Abdullah-Al-Shafi ◽  
Kawsar Ahmed

2019 ◽  
Vol 21 ◽  
pp. 100252 ◽  
Author(s):  
Azath Mubarakali ◽  
Jayabrabu Ramakrishnan ◽  
Dinesh Mavaluru ◽  
Amria Elsir ◽  
Omer Elsier ◽  
...  

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Ismail Gassoumi ◽  
Lamjed Touil ◽  
Bouraoui Ouni ◽  
Abdellatif Mtibaa

Optimization for power is one of the most important design objectives in modern digital image processing applications. The DCT is considered to be one of the most essential techniques in image and video compression systems, and consequently a number of extensive works had been carried out by researchers on the power optimization. On the other hand, quantum-dot cellular automata (QCA) can present a novel opportunity for the design of highly parallel architectures and algorithms for improving the performance of image and video processing systems. Furthermore, it has considerable advantages in comparison with CMOS technology, such as extremely low power dissipation, high operating frequency, and a small size. Therefore, in this study, the authors propose a multiplier-less DCT architecture in QCA technology. The proposed design provides high circuit performance, very low power consumption, and very low dimension outperform to the existing conventional structures. The QCADesigner tool has been utilized for QCA circuit design and functional verification of all designs in this work. QCAPro, a very widespread power estimator tool, is applied to estimate the power dissipation of the proposed circuit. The suggested design has 53% improvement in terms of power over the conventional solution. The outcome of this work can clearly open up a new window of opportunity for low power image processing systems.


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