基于模拟忆阻器的图像识别神经形态交叉电路

Lingfeng Xu, Chuandong Li, Ling Chen
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引用次数: 6

摘要

自发现以来,忆阻器受到了世界各国研究者的广泛研究,在识别领域的应用前景十分广阔。在本文中,我们在现有工作的基础上改进了一个记忆电阻交叉栅电路来识别8 × 8像素的二值图像。我们使用模拟忆阻器代替二进制忆阻器来完成电路。模拟识别率平均为82.5%,并通过蒙特卡罗仿真进一步分析了电路在不同忆阻变化和统计分布下的性能。我们发现,随着忆阻变化的增大,高斯分布下的识别率下降很快,而均匀分布下的识别率相对稳定。最后,我们对电路的改进提出了一些展望和意见。
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Analog memristor based neuromorphic crossbar circuit for image recognition
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.
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