首页> 外国专利> CONVOLUTIONAL LAYERS FOR NEURAL NETWORKS USING PROGRAMMABLE NANOPHOTONICS

CONVOLUTIONAL LAYERS FOR NEURAL NETWORKS USING PROGRAMMABLE NANOPHOTONICS

机译:使用可编程纳光学的神经网络卷积层

摘要

Aspects of the present application relate to techniques for computing convolutions and cross-correlations of input matrices. A first technique is based on the transformation of convolution operations into a matrix-vector product. A second technique is based on two-dimensional matrix multiplication. A third technique is based on the convolution theorem, which states that convolutions correspond to multiplications in a transform space. Embodiments include methods for computing convolutions of a filter matrix and an input data matrix; apparatuses for computing convolutions of a filter matrix and an input data matrix; and a non-transitory computer readable medium programmed with instructions that, when executed by a processor perform a method for computing convolutions of a filter matrix and an input data matrix.
机译:本申请的方面涉及用于计算输入矩阵的卷积和互相关的技术。第一种技术是基于将卷积运算转换为矩阵向量积的。第二种技术基于二维矩阵乘法。第三种技术基于卷积定理,它指出卷积对应于变换空间中的乘法。实施例包括用于计算滤波器矩阵和输入数据矩阵的卷积的方法。用于计算滤波器矩阵和输入数据矩阵的卷积的设备;以及编程有指令的非暂时性计算机可读介质,所述指令在由处理器执行时执行用于计算滤波器矩阵和输入数据矩阵的卷积的方法。

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