首页> 外国专利> INPUT AND DIGITAL OUTPUT MECHANISMS FOR ANALOG NEURAL MEMORY IN A DEEP LEARNING ARTIFICIAL NEURAL NETWORK

INPUT AND DIGITAL OUTPUT MECHANISMS FOR ANALOG NEURAL MEMORY IN A DEEP LEARNING ARTIFICIAL NEURAL NETWORK

机译:深度学习人工神经网络中模拟神经记忆的输入和数字输出机制

摘要

Numerous embodiments for reading a value stored in a selected memory cell in a vector-by-matrix multiplication (VMM) array in an artificial neural network are disclosed. In one embodiment, an input comprises a set of input bits that result in a series of input pulses applied to a terminal of the selected memory cell, further resulting in a series of output signals that are summed to determine the value stored in the selected memory cell. In another embodiment, an input comprises a set of input bits, where each input bit results in a single pulse or no pulse being applied to a terminal of the selected memory cell, further resulting in a series of output signals which are then weighted according to the binary bit location of the input bit, and where the weighted signals are then summed to determine the value stored in the selected memory cell.
机译:公开了用于在人工神经网络中的矢量逐矩阵乘法(VMM)阵列中存储在所选存储单元中的许多实施例。在一个实施例中,输入包括一组输入比特,该输入位导致施加到所选存储器单元的终端的一系列输入脉冲,进一步导致一系列求和的输出信号,以确定存储在所选存储器中的值细胞。在另一个实施例中,输入包括一组输入比特,其中每个输入位导致单个脉冲或没有脉冲被施加到所选择的存储器单元的终端,进一步导致一系列输出信号,然后根据其加权然后,输入位的二进制比特位置,以及加权信号求和以确定存储在所选择的存储器单元中的值。

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