A real-time missing data recovery method using recurrent neural network for multiple transmissions

Bor Shing Lin*, Yu Syuan Lin, I. Jung Lee, Bor-Shyh Lin

*此作品的通信作者

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

Data loss and recovery is a critical issue in data transmission. Traditional data recovery methods are impractical for use in real-time systems that require multiple transmissions. To solve this problem, this study proposed a recovery method based on a recurrent neural network, which is then used to build a pre-diction model. When a data gap occurs, the missing data can be recovered immediately using the predicted value. This method distributes the calculation and can immediately recover the data gap. Through a series of experiments, this study optimized different parameters in the neural network, thus optimizing the prediction model.

原文English
主出版物標題Recent Advances in Intelligent Information Hiding and Multimedia Signal Processing - Proceeding of the Fourteenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing
編輯Pei-Wei Tsai, Akinori Ito, Lakhmi C. Jain, Lakhmi C. Jain, Jeng-Shyang Pan, Lakhmi C. Jain
發行者Springer Science and Business Media Deutschland GmbH
頁面99-107
頁數9
ISBN(列印)9783030037444
DOIs
出版狀態Published - 26 11月 2018
事件14th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2018 - Sendai, Japan
持續時間: 26 11月 201828 11月 2018

出版系列

名字Smart Innovation, Systems and Technologies
109
ISSN(列印)2190-3018
ISSN(電子)2190-3026

Conference

Conference14th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2018
國家/地區Japan
城市Sendai
期間26/11/1828/11/18

指紋

深入研究「A real-time missing data recovery method using recurrent neural network for multiple transmissions」主題。共同形成了獨特的指紋。

引用此