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Neural Processing Letters

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18-05-2018

One Recurrent Neural Networks Solution for Passive Localization

Authors: Chuang Zhao, Yongjun Zhao

Published in: Neural Processing Letters | Issue 2/2019

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Abstract

A revised recurrent neural networks method for the passive source localization is proposed in this paper. The cost function has been designed which makes the transformation from transmitters’ localization into the outputs of the settled revised recurrent neural networks through spatial partition. The neural networks are chaotic and stable in convergence. The received signal model is constructed firstly. The parameters of the recurrent neural networks have been trained properly according to the scene. The experiments and analysis display that the revised recurrent neural networks solution not only obtains high precision location, but also has high convergence rate.

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Title: One Recurrent Neural Networks Solution for Passive Localization
Authors: Chuang Zhao
Yongjun Zhao
Publication date: 18-05-2018
Publisher: Springer US
Published in: Neural Processing Letters / Issue 2/2019
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI: https://doi.org/10.1007/s11063-018-9856-y

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