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    • 1. 发明授权
    • Low-voltage, very-low-power conductance mode neuron
    • 低电压,极低功率的电导模式神经元
    • US06269352B1
    • 2001-07-31
    • US09461674
    • 1999-12-14
    • Vito FabbrizioGianluca ColliAlan Kramer
    • Vito FabbrizioGianluca ColliAlan Kramer
    • G06F1518
    • G06N3/063G06N3/0635
    • A neural network including a number of synaptic weighting elements, and a neuron stage; each of the synaptic weighting elements having a respective synaptic input connection supplied with a respective input signal; and the neuron stage having inputs connected to the synaptic weighting elements, and being connected to an output of the neural network supplying a digital output signal. The accumulated weighted inputs are represented as conductances, and a conductance-mode neuron is used to apply nonlinearity and produce an output. The synaptic weighting elements are formed by memory cells programmable to different threshold voltage levels, so that each presents a respective programmable conductance; and the neuron stage provides for measuring conductance on the basis of the current through the memory cells, and for generating a binary output signal on the basis of the total conductance of the synaptic elements.
    • 包括许多突触加权元素和神经元阶段的神经网络; 每个突触加权元件具有被提供有相应输入信号的相应突触输入连接; 并且神经元级具有连接到突触加权元件的输入,并且连接到提供数字输出信号的神经网络的输出端。 累积的加权输入被表示为电导,并且使用电导模式神经元来应用非线性并产生输出。 突触加权元件由可编程为不同阈值电压电平的存储器单元形成,使得每个呈现相应的可编程电导; 并且神经元级基于通过存储器单元的电流提供测量电导,并且用于基于突触元件的总电导产生二进制输出信号。
    • 2. 再颁专利
    • Low-voltage, very-low-power conductance mode neuron
    • 低电压,极低功率的电导模式神经元
    • USRE41658E1
    • 2010-09-07
    • US10631323
    • 2003-07-31
    • Vito FabbrizioGianluca ColliAlan Kramer
    • Vito FabbrizioGianluca ColliAlan Kramer
    • G06G7/00G06N3/00G06N3/02G06E1/00G06E3/00G06F15/16
    • G06N3/063G06N3/0635
    • A neural network including a number of synaptic weighting elements, and a neuron stage; each of the synaptic weighting elements having a respective synaptic input connection supplied with a respective input signal; and the neuron stage having inputs connected to the synaptic weighting elements, and being connected to an output of the neural network supplying a digital output signal. The accumulated weighted inputs are represented as conductances, and a conductance-mode neuron is used to apply nonlinearity and produce an output. The synaptic weighting elements are formed by memory cells programmable to different threshold voltage levels, so that each presents a respective programmable conductance; and the neuron stage provides for measuring conductance on the basis of the current through the memory cells, and for generating a binary output signal on the basis of the total conductance of the synaptic elements.
    • 包括许多突触加权元素和神经元阶段的神经网络; 每个突触加权元件具有被提供有相应输入信号的相应突触输入连接; 并且神经元级具有连接到突触加权元件的输入,并且连接到提供数字输出信号的神经网络的输出端。 累积的加权输入被表示为电导,并且使用电导模式神经元来应用非线性并产生输出。 突触加权元件由可编程为不同阈值电压电平的存储器单元形成,使得每个呈现相应的可编程电导; 并且神经元级基于通过存储器单元的电流提供测量电导,并且用于基于突触元件的总电导产生二进制输出信号。
    • 5. 发明授权
    • Low-voltage, very-low-power conductance mode neuron
    • 低电压,极低功率的电导模式神经元
    • US6032140A
    • 2000-02-29
    • US731426
    • 1996-10-15
    • Vito FabbrizioGianluca ColliAlan Kramer
    • Vito FabbrizioGianluca ColliAlan Kramer
    • G06G7/60G06F15/18G06N3/06G06N3/063
    • G06N3/063G06N3/0635
    • A neural network including a number of synaptic weighting elements, and a neuron stage; each of the synaptic weighting elements having a respective synaptic input connection supplied with a respective input signal; and the neuron stage having inputs connected to the synaptic weighting elements, and being connected to an output of the neural network supplying a digital output signal. The accumulated weighted inputs are represented as conductances, and a conductance-mode neuron is used to apply nonlinearity and produce an output. The synaptic weighting elements are formed by memory cells programmable to different threshold voltage levels, so that each presents a respective programmable conductance; and the neuron stage provides for measuring conductance on the basis of the current through the memory cells, and for generating a binary output signal on the basis of the total conductance of the synaptic elements.
    • 包括许多突触加权元素和神经元阶段的神经网络; 每个突触加权元件具有被提供有相应输入信号的相应突触输入连接; 并且神经元级具有连接到突触加权元件的输入,并且连接到提供数字输出信号的神经网络的输出端。 累积的加权输入被表示为电导,并且使用电导模式神经元来应用非线性并产生输出。 突触加权元件由可编程为不同阈值电压电平的存储器单元形成,使得每个呈现相应的可编程电导; 并且神经元级基于通过存储器单元的电流提供测量电导,并且用于基于突触元件的总电导产生二进制输出信号。