基于前馈神经网络和CIR指纹识别技术的室内定位

R. Zouari, R. Zayani, R. Bouallègue
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引用次数: 7

摘要

许多室内环境下精确定位的解决方案都是基于通道脉冲响应(CIR)技术,如指纹识别和神经网络(NN)技术的结合。适合没有理论来表示给定问题的神经网络结构。它只能通过实验来完成。然后,本文旨在确定适合室内定位的神经网络结构和相应的算法。为此,对不同的神经网络结构以及各种算法进行了比较和讨论,以确定最合适的算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Indoor localization based on feed-forward Neural Networks and CIR fingerprinting techniques
Many solutions to accurate localization in indoor environments are based on the combination of Channel Impulse Response (CIR), as fingerprinting, and Neural Networks (NN) technique. Suitable there is no theory to indicate the neural network structure for a given problem. It must be done only experimentally. Then, this paper aims to identify the neural network structure and the accompanied algorithm which are suitable for indoor localization. For this purpose, different NN structures accompanied with various algorithms are compared and discussed in order to identify the most appropriate.
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