DocumentCode :
3863205
Title :
Analog memristor based neuromorphic crossbar circuit for image recognition
Author :
Lingfeng Xu;Chuandong Li;Ling Chen
Author_Institution :
College of Electronic and Information Engineering, Southwest University, Chongqing, China
fYear :
2015
Firstpage :
155
Lastpage :
160
Abstract :
Since its discovery, memristor has been well studied by researchers from all around the world, and its application in recognition proves to be very promising. In this paper, we modify a memristor crossbar circuit from an existing work to recognize 8 × 8 pixel binary images. We use analog memristors instead of binary memristors to complete the circuit. The simulated recognition rate is 82.5% in average, and we step further by carrying out a Monte Carlo simulation to analyze the performances of the circuit under different memristance variations and statistical distributions. We find that as the memristance variation rises up, the recognition rate under Gaussian distribution drops quickly, while the performance under uniform distribution is relatively stable. In the final part, we provide some outlooks and remarks on the possible improvements of the circuit.
Keywords :
"Memristors","Capacitors","Mathematical model","MOSFET circuits","Discharges (electric)","Neuromorphics","Integrated circuit modeling"
Publisher :
ieee
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2015 Sixth International Conference on
Print_ISBN :
978-1-4799-1715-0
Type :
conf
DOI :
10.1109/ICICIP.2015.7388161
Filename :
7388161
Link To Document :
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