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A Bit-Parallel Representation of Activation Functions for Fast Neural Networks

机译:快速神经网络的激活函数的位并行表示

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摘要

A procedure for constructing a neuron with fast calculation of the activation function by the tabular-algorithmic method is suggested. The effect is achieved by means of a bit-parallel representation of the result of computation of a nonlinear function oriented to the operation of group summation. The approach can be applied to activation functions of various forms, including logistical and sigmoid rational functions. The creation of a fast neuron requires hardware implementation of a nonlinear function on the basis of ROM, registers, hardware logic, and adders.
机译:提出了一种通过表格算法快速计算激活函数的神经元的方法。通过以面向组求和操作的非线性函数的计算结果的位并行表示来实现该效果。该方法可以应用于各种形式的激活函数,包括逻辑和S形有理函数。快速神经元的创建需要基于ROM,寄存器,硬件逻辑和加法器的非线性功能的硬件实现。

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