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Signal reconstruction model of low energy consumption based on distributed compressed sensing

  • Zhaoqing University
  • Harbin Institute of Technology Shenzhen

Research output: Contribution to journalArticlepeer-review

Abstract

The new algorithm designed in the thesis is easy to realize. Fast estimation link is introduced in the early stage, which can reconstruct the unknown signal; in addition, index that can reflect signal probability is applied in the thesis to verify the performance of designed algorithm. However, when the sparsity is relatively big, the performance of algorithm designed in the thesis would decline obviously. How to resolve this problem is the key point in the subsequent study.

Original languageEnglish
Pages (from-to)7973-7977
Number of pages5
JournalJournal of Computational and Theoretical Nanoscience
Volume13
Issue number11
DOIs
StatePublished - 2016
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Distributed compressed sensing
  • Estimation system
  • Low energy consumption
  • Signal reconstruction model

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