Sigmoid函数的分段非线性拟合法及其FPGA实现

发布时间：2018-03-06 05:14

  本文选题：分段非线性逼近法　切入点：Sigmoid函数　出处：《电子技术应用》2017年08期 　论文类型：期刊论文

【摘要】：使用分段非线性逼近算法计算超越函数,以神经网络中应用最为广泛的Sigmoid函数为例,结合函数自身对称的性质及其导数不均匀的特点提出合理的分段方法,给出分段方式同逼近多项式阶数对逼近结果精度的影响。完成算法在FPGA上的硬件实现,给出一种使用三阶多项式处理Sigmoid函数的拟合结果及流水线架构,处理精度达到10-5数量级,最大频率达到127.327 MHz,满足了高速、高精度的处理要求。
[Abstract]:The piecewise nonlinear approximation algorithm is used to calculate transcendental function. Taking Sigmoid function, which is widely used in neural network, as an example, a reasonable piecewise method is proposed according to the property of symmetry of function itself and its uneven derivative. The effect of piecewise method and order of approximation polynomial on the precision of approximation results is given. The hardware implementation of the algorithm on FPGA is given, and a fitting result of Sigmoid function using third-order polynomial and pipeline structure are given. The processing accuracy reaches 10-5 orders of magnitude. The maximum frequency is 127.327 MHz, which meets the requirements of high speed and high precision processing.
【作者单位】： 合肥工业大学微电子设计研究所;
【分类号】：O174;TN791
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本文编号：1573467