FPGA implementation of neural network for linearization of thermistor characteristics

D. Sonowal, M. Bhuyan
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引用次数: 8

Abstract

This paper presents an FPGA (Field Programmable Gate Array) implementation of an artificial neural network (ANN) for linearization of nonlinear characteristics of a thermistor. A feed forward ANN is used for linearization. The network is trained in MATLAB with back propagation algorithm; weights and biases are determined and then implemented in Spartan-III FPGA. Subroutines are developed for single precision floating point arithmetic in IEEE-754 format.
用FPGA实现热敏电阻特性线性化的神经网络
本文提出了一种现场可编程门阵列(FPGA)实现热敏电阻非线性特性线性化的人工神经网络(ANN)。采用前馈人工神经网络进行线性化。在MATLAB中使用反向传播算法对网络进行训练;确定权重和偏置,然后在Spartan-III FPGA上实现。开发了IEEE-754格式的单精度浮点运算子程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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