Earticle

초록

영어

Correlation of wireless sensor network data is the foundation and premise of using compressive sensing theory to reconstruct the network data as well as the main basis for the design of network data reconstruction algorithm. However, various interferences of network data in practical transmission would result in consistent changes of correlation, thus lead to sharply aggravation of reconstruction performances in the existing compressive sensing theory. In order to improve the reliability and efficiency of compressive sensing of wireless sensor network data, a correlation adaptive reconstruction algorithm for network data is proposed. This algorithm first estimates the correlation of data to be reconstructed through iteration and then restores the data to be restructured using the two-step correlation test method of support elements. Compared to the previous reconstruction methods, correlation adaptive reconstruction method can greatly improve the reconstruction accuracy when the correlation of network data is changing.

목차

Abstract
 1. Introduction
 2. Descriptions of Problems
 3. Proposed Algorithm
 4. Experiments and Simulation
 5. Conclusions
 References

키워드

저자

• Wang Changliang [ ZheJiang Industry Polytechnic College, Shaoxing, Zhejiang, China ]
• Fang Jie [ ZheJiang Industry Polytechnic College, Shaoxing, Zhejiang, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Future Generation Communication and Networking

• 간기

  격월간

• pISSN

  2233-7857

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605