Decentralized classification in sensor networks via sparse representation and constrained fractional programming-Reference-Cited by-同舟云学术

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Decentralized classification in sensor networks via sparse representation and constrained fractional programming

Published:2024-02 Issue: Volume:145 Page:104322
ISSN:1051-2004
Container-title:Digital Signal Processing
language:en
Short-container-title:Digital Signal Processing

Author:

Ye Zhonghua^ORCID,Zhu Hong,Fang Xueyi

Funder

Aeronautical Science Foundation of China

Key Research and Development Projects of Shaanxi Province

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Signal Processing,Artificial Intelligence,Applied Mathematics,Computer Vision and Pattern Recognition,Statistics, Probability and Uncertainty,Computational Theory and Mathematics

Reference22 articles.

1. Distributed parallel support vector machines in strongly connected networks;Lu;IEEE Trans. Neural Netw.,2008

2. Distributed clustering using wireless sensor networks;Forero;IEEE J. Sel. Top. Signal Process.,2011

3. Distributed optimization and statistical learning via the alternating direction method of multipliers;Boyd;Found. Trends Mach. Learn.,2011

4. Decentralized dimensionality reduction for distributed tensor data across sensor networks;Liang;IEEE Trans. Neural Netw. Learn. Syst.,2016

5. Distributed dictionary learning for sparse representation in sensor networks;Liang;IEEE Trans. Image Process.,2014

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