A new lossy compression algorithm for wireless sensor networks using Bayesian predictive coding-Reference-Cited by-同舟云学术

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A new lossy compression algorithm for wireless sensor networks using Bayesian predictive coding

Published:2020-07-10 Issue:8 Volume:26 Page:5981-5995
ISSN:1022-0038
Container-title:Wireless Networks
language:en
Short-container-title:Wireless Netw

Author:

Chen Chen,Zhang Limao^ORCID,Tiong Robert Lee Kong

Funder

Start-Up Grant at Nanyang Technological University, Singapore

Ministère de l'Education Nationale, de la Formation professionnelle, de l'Enseignement Supérieur et de la Recherche Scientifique

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

Link

http://link.springer.com/content/pdf/10.1007/s11276-020-02425-w.pdf

Reference50 articles.

1. Akansu, A. N., Serdijn, W. A., & Selesnick, I. W. (2010). Emerging applications of wavelets: A review. Physical Communication, 3(1), 1–18.

2. Alsheikh, M. A., Lin, S., Niyato, D., & Tan, H.-P. (2016). Rate-distortion balanced data compression for wireless sensor networks. IEEE Sensors Journal, 16(12), 5072–5083.

3. Banerjee, R., & Bit, S. D. (2017). An energy efficient image compression scheme for wireless multimedia sensor network using curve fitting technique. Wireless Networks, 25(1), 167–183.

4. Buratti, C., Conti, A., Dardari, D., & Verdone, R. (2009). An overview on wireless sensor networks technology and evolution. Sensors, 9, 6869–6896.

5. Capo-Chichi, E.P., Guyennet, H., Friedt, J.-M. (2009) K-RLE: A new data compression algorithm for wireless sensor network. In 3rd international conference on sensor technologies and applications, Athens, Glyfada, Greece.

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