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EEPROM as an analog storage device, with particular applications in neutral networks

机译:EEPROM作为模拟存储设备,特别适用于中性网络

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The use of EEPROM as a compact, high-precision, nonvolatile, and reconfigurable analog storage element is investigated, with particular consideration given to the modifiable weight storage and analog multiplication problems in the hardware implementation of a neural network. Industry-standard digital EEPROM cells can be programmed to any analog value of threshold voltage, but programming characteristics of different devices on the same chip vary. The programming window of a single device also narrows with cycling. These phenomena necessitate the use of a feedback-based programming scheme. Stressing at high temperature suggests that charge retention is good even at 175 degrees C. The linear variation of threshold voltage with temperature implies that temperature compensation of EEPROM is no more complicated than its conventional MOSFET counterpart. The drain current in the saturation region is found to be a quadratic function of drain voltage when the floating-gate-to-drain overlap capacitance is adequately large. A differential circuit that uses this property to generate the multiplication function required of neural net synapses is proposed.
机译:研究了将EEPROM用作紧凑,高精度,非易失性和可重新配置的模拟存储元件,并特别考虑了神经网络的硬件实现中可修改的权重存储和模拟乘法问题。可以将行业标准的数字EEPROM单元编程为阈值电压的任何模拟值,但是同一芯片上不同设备的编程特性会有所不同。单个设备的编程窗口也随着循环而变窄。这些现象需要使用基于反馈的编程方案。高温下的应力表明,即使在175摄氏度时,电荷保持性能也很好。阈值电压随温度的线性变化意味着EEPROM的温度补偿并不比其传统MOSFET复杂。当浮栅漏重叠电容足够大时,发现饱和区中的漏电流是漏电压的二次函数。提出了一种利用该特性来生成神经网络突触所需的乘法函数的差分电路。

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