Approximating properties of artificial neural network in time domain for the analysis of electromagnetic fields reflected from model of human body surface

O. Dumin, D. Shyrokorad, O. Dumina, V. Katrich, V. Chebotarev
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引用次数: 11

Abstract

The approximating properties of artificial neural network for the problem of determination of thickness a layer of layered medium by means of the analysis of reflected impulse electromagnetic fields are considered. The impulse fields are reflected from the model of human body surface. The normal incidence of plane wave with Gaussian time form on the layered medium with losses is considered. The reflected electromagnetic field is obtained by FDTD method. Initial data for neural network analysis are the values of amplitude of electrical component of reflected field in different moments of time. So, the analysis is performed in time domain directly. As an example, the network is trained to determine the thickness of one of the layers of the medium. The stability of the determination in presence of interferences, experimental errors and instabilities of medium parameters is investigated. The approximating properties of the artificial neural network are considered for the smooth change of the second layer thickness.
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人体体表模型反射电磁场分析的人工神经网络时域逼近特性
考虑了利用反射脉冲电磁场分析确定层状介质厚度问题的人工神经网络的近似性质。脉冲场是由人体表面模型反射出来的。考虑了高斯时间形式的平面波在有损耗的层状介质上的法向入射。利用时域有限差分法获得了反射电磁场。神经网络分析的初始数据是反射场在不同时刻的电分量振幅值。因此,直接在时域内进行分析。作为一个例子,网络被训练来确定介质某一层的厚度。研究了在存在干扰、实验误差和介质参数不稳定的情况下测定的稳定性。考虑了人工神经网络对第二层厚度平滑变化的逼近特性。
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