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BP神经网络拟合平稳跟踪眼震信号
引用本文:王长元,郭蓉.BP神经网络拟合平稳跟踪眼震信号[J].科技信息,2010(1).
作者姓名:王长元  郭蓉
作者单位:西安工业大学计算机科学与工程学院;
摘    要:在前庭功能检查中,要对平稳跟踪信号进行分析,必须先对实验者的跟踪数据信号进行曲线拟合。由于BP神经网络可以实现输入和输出间的任意非线性,使得它在函数逼近上有广泛的应用。因此本文用BP神经网络对平稳跟踪信号进行曲线拟合。对网络的训练方法采用贝叶斯正则化算法。实验表明,拟合的曲线和正弦曲线基本吻合,尽可能的通过了样本点,也排除少数点的干扰。

关 键 词:BP神经网络  平稳跟踪信号  贝叶斯正则化算法  

BP Neural Network Model Based on Video-oculography Signal
WANG Chang-yuan GUO Rong.BP Neural Network Model Based on Video-oculography Signal[J].Science,2010(1).
Authors:WANG Chang-yuan GUO Rong
Institution:WANG Chang-yuan GUO Rong
Abstract:In the vestibular function test, first, we should fit a curve for signals of tracking data ,and the we can analyse signals of smooth pursuit test . As the BP neural network can achieve any non-linear between the input and output, making it has a wide range of applications on the function approximation. Therefore, this paper use BP neural network to fit the signal. And we use Bayesian regularization algorithm as our training method on the network. Experiments show that the fitted curve is similar to the sine...
Keywords:BP neural network  Smooth pursuit test signal  Bayesian regularization algorithm  
本文献已被 CNKI 等数据库收录!
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