Proceedings of the IEEK Conference (대한전자공학회:학술대회논문집)
- 2007.07a
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- Pages.457-458
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- 2007
A method of overcomplete representation for distributed data
분산 자료에 대한 초완비 표현 방법
- Lee, Sang-Cheol (Dept. of Computer Robot, JaiNeung College) ;
- Park, Jong-Woo (Dept. of Computer Robot, JaiNeung College) ;
- Kwak, Chil-Seong (Dept. of Digital Information & Electronics JaiNeung College)
- Published : 2007.07.11
Abstract
This paper propose a method for representing distributed data of sensor networks. The proposed method is based on a general distributed regression framework that models sensor data by fitting a global function to each of the local measurements and explores the possible extensions of distribution regression by using complex signal representations. In order to reduce the amount of processed data and the required communication, the signal model has to be as compact as possible, with the ability to restore the arbitrary measurements. To achieve this requirement, data compression step is included, where the basis function set is changed to an overcomplete set. This have better advantages in case of nonstationary signal modeling than complete base representation.
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