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Design of Artificial Neuron Network with Synapse Utilizing Hybrid CMOS Transistors with Memristor for Low Power Applications

机译:利用混合CMOS晶体管利用映射与低功耗应用的人工神经元网络设计

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Neural networks are mimetic with biological neuron which are employed on digital computers. These networks are designed with CMOS technology using 0.45 mu m in cadence virtuoso. The scaling of CMOS limits parameters like power consumption, area and parallelism. To overcome the limitations, a nanoscale, nonvolatile Memristor device is used to design the synapses. The proposed network is designed for neuron synapse networks implemented with a memristor device. This network is compared with neuron linked with CMOS synapse. The proposed network has low power consumption, high spike frequency, and low delay value. The spike frequency of Memristor synapse increases by 65.51% when compared with the existing CMOS synapse and power consumption is reduced to 52.79%. The delay is reduced to 0.294 mu s. The simulation results are carried using Specter.
机译:神经网络与在数字计算机上使用的生物神经元模仿。这些网络采用CMOS技术设计,在Cadence Virtuoso中使用0.45亩。 CMOS的缩放限制了功耗,区域和并行度等参数。为了克服限制,使用纳米级非易失性映射器设备来设计突触。所提出的网络专为用忆阻器设备实现的神经元Synapse网络而设计。将该网络与与CMOS Synapse相关联的神经元进行比较。所提出的网络具有低功耗,高峰值频率和低延迟值。与现有的CMOS Synapse相比,映射器Synaps的峰值频率增加了65.51%,并且功耗降至52.79%。延迟减少到0.294亩。模拟结果使用幽灵携带。

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