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A Neuromorphic Design Using Chaotic Mott Memristor with Relaxation Oscillation

机译:使用混沌Mott Memitristor进行松弛振荡的神经形态设计

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The recent proposed nanoscale Mott memristor features negative differential resistance and chaotic dynamics. This work proposes a novel neuromorphic computing system that utilizes Mott memristors to simplify peripheral circuitry. According to the analytic description of chaotic dynamics and relaxation oscillation, we carefully tune the working point of Mott memristors to balance the chaotic behavior weighing testing accuracy and training efficiency. Compared with conventional designs, the proposed design accelerates the training by 1.893× averagely and saves 27.68% and 43.32% power consumption with 36.67% and 26.75% less area for single-layer and two-layer perceptrons, respectively.
机译:最近提出的纳米级Mott忆阻器具有负差分电阻和混沌动态。这项工作提出了一种新型神经形态计算系统,其利用MOTT忆阻器来简化外围电路。根据混沌动力学和弛豫振荡的分析描述,我们仔细调整了Mott忆内函数的工作点,平衡了称重测试精度和培训效率的混沌行为。与传统设计相比,建议的设计平均加速了培训1.893×,分别节省了27.68%和43.32%的功耗,分别具有36.67%和26.75%的单层和两层摄影群。

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