Implementation of neural network with approximations functions

被引：0

作者：

Hnatiuc, M ^{[1
]}

Lamarque, G ^{[1
]}

机构：

[1] Tech Univ Gh Asachi Iasi, Iasi, Romania

来源：

SCS 2003: INTERNATIONAL SYMPOSIUM ON SIGNALS, CIRCUITS AND SYSTEMS, VOLS 1 AND 2, PROCEEDINGS | 2003年

关键词：

non-linear functions; gauss function; sigmoid function; neural network;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The purpose of this work is to simulate a neural network with non-linear activation functions. The non-linear functions are simulated in Microsoft Visual Studio C++ 6.0 to observe the precision and to implement on the programmable logic devices. This network is realized to accept very small input values. The multiplication between input values and weight values is realized with the add-logarithm and exponential functions. One approximates all the non-linear functions with linear functions using shift-add blocks.

引用

页码：553 / 556

页数：4

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