Title :
An improved data streams processing algorithm for sensor networks based on training weights
Author :
Cheng, Wei ; Shi, Haoshan
Author_Institution :
Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´´an, China
Abstract :
In order to enhance the performance of SPIRIT, in this paper we propose an improved multi-streams processing algorithm for data streams processing of sensor networks. The improved algorithm adapts the orthogonalization step and the training step for tracking weights vectors. Simulation experimental results show that compared to the original algorithm, the improved algorithm can reduce the reconstruction error, increase the energy fraction of reconstruction, and decrease the number of hidden variables, so it extract the principal components among streams more effectively.
Keywords :
pattern recognition; principal component analysis; sensor fusion; signal reconstruction; SPIRIT; data stream processing; multistream processing; orthogonalization step; sensor network; stream principal component; training weight; weight vector tracking; Data mining; Discrete Fourier transforms; Electronic mail; Intrusion detection; Monitoring; Principal component analysis; Yttrium; data streams; orthogonalization; sensor networks; training weights;
Conference_Titel :
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6347-3
DOI :
10.1109/ICCET.2010.5485789
