Semi-supervised manifold learning based on polynomial mapping for localization in wireless sensor networks

Hao Xu

doi:10.1016/j.sigpro.2020.107570

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Semi-supervised manifold learning based on polynomial mapping for localization in wireless sensor networks

Hao Xu

Year: 2020 Journal: Signal Processing Vol: 172 Pages: 107570-107570 Publisher: Elsevier BV

DOI: 10.1016/j.sigpro.2020.107570

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Keywords:

Wireless sensor network Nonlinear dimensionality reduction Polynomial Embedding Discriminative model Algorithm Kernel (algebra) Computer science Mathematics Artificial intelligence Dimensionality reduction

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Indoor and Outdoor Localization Technologies

Physical Sciences → Engineering → Electrical and Electronic Engineering

Underwater Vehicles and Communication Systems

Physical Sciences → Engineering → Ocean Engineering

Energy Efficient Wireless Sensor Networks

Physical Sciences → Computer Science → Computer Networks and Communications

Semi-supervised manifold learning based on polynomial mapping for localization in wireless sensor networks

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