DEEP NEURAL NETWORK TRAINING WITH NATIVE DEVICES
    111.
    发明申请
    DEEP NEURAL NETWORK TRAINING WITH NATIVE DEVICES 审中-公开
    深层神经网络训练与本体设备

    公开(公告)号:US20170061281A1

    公开(公告)日:2017-03-02

    申请号:US14837798

    申请日:2015-08-27

    CPC classification number: G06N3/084 G06N3/0635

    Abstract: An artificial neural network and methods for performing computations on an artificial neural network include multiple neurons, including a layer of input neurons, one or more layers of hidden neurons, and a layer of output neurons. Arrays of weights are configured to accept voltage pulses from a first layer of neurons and to output current to a second layer of neurons during a feed forward operation. Each array of weights includes multiple resistive processing units having respective settable resistances.

    Abstract translation: 用于在人造神经网络上执行计算的人造神经网络和方法包括多个神经元,包括一层输入神经元,一层或多层隐藏神经元,以及一层输出神经元。 配重数组被配置为接受来自第一神经元层的电压脉冲,并且在前馈操作期间将电流输出到第二层神经元。 每个权重阵列包括具有各自可设置电阻的多个电阻处理单元。

    Solar cell characteristics determination
    113.
    发明授权
    Solar cell characteristics determination 有权
    太阳能电池特性测定

    公开(公告)号:US09400306B2

    公开(公告)日:2016-07-26

    申请号:US13968004

    申请日:2013-08-15

    Abstract: An apparatus for determining solar cell characteristics includes a quantum efficiency measurement tool configured to measure an external quantum efficiency of the solar cell and a reflectivity measurement tool configured to measure the reflectivity of the solar cell. The apparatus also includes a capacitance measurement tool configured to measure the capacitance of the solar cell and a processor configured to calculate a diffusion length of the solar cell based on the measured quantum efficiency, reflectivity and capacitance of the solar cell.

    Abstract translation: 一种用于确定太阳能电池特性的装置包括:量子效率测量工具,被配置为测量太阳能电池的外部量子效率;以及反射率测量工具,被配置为测量太阳能电池的反射率。 该装置还包括:电容测量工具,被配置为测量太阳能电池的电容;以及处理器,被配置为基于所测量的量子效率,太阳能电池的反射率和电容来计算太阳能电池的扩散长度。

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