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The Circuit Realization of a Neuromorphic Computing System with Memristor-Based Synapse Design

机译:基于忆阻器突触设计的神经形态计算系统的电路实现

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Conventional CMOS technology is slowly approaching its physical limitations and researchers are increasingly utilizing nanotechnology to both extend CMOS capabilities and to explore potential replacements. Novel me-mristive systems continue to attract growing attention since their reported physical realization by HP in 2008. Unique characteristics like non-volatility, re-configurability, and analog storage properties make memristors a very promising candidate for the realization of artificial neural systems. In this work, we propose a memristor-based design of bidirectional transmission excitation/inhibition synapses and implement a neuromorphic computing system based on our proposed synapse designs. The robustness of our system is also evaluated by considering the actual manufacturing variability with emphasis on process variation.
机译:传统的CMOS技术正逐渐接近其物理局限性,研究人员越来越多地利用纳米技术来扩展CMOS功能并探索潜在的替代品。自从HP于2008年报告其物理实现以来,新型忆阻系统一直受到越来越多的关注。诸如非易失性,可重新配置性和模拟存储特性之类的独特特性使忆阻器成为实现人工神经系统的非常有希望的候选者。在这项工作中,我们提出了一种基于忆阻器的双向传输激发/抑制突触的设计,并基于我们提出的突触设计实现了神经形态计算系统。我们的系统的鲁棒性也通过考虑实际制造的可变性来评估,重点是工艺变化。

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