论文信息 - The study on denoising model of time series in big data

The study on denoising model of time series in big data

A model which includes wavelet analysis and windows Fourier transform has been designed to resolve huge time series and interferential data in big data. In the model, the mass data firstly has been clustered as static or dynamic data. The static data has been processed by windows Fourier transform, and the dynamic data has been processed by wavelet analysis. After testing and simulation, the computing speed and denoising effect have been improved.

Xiaoming Guo | Jianming Cui | Xingwang Zhang

[1] Tak-Chung Fu,et al. An evolutionary approach to pattern-based time series segmentation , 2004, IEEE Transactions on Evolutionary Computation.

[2] Chris Rizos,et al. An approach to GPS analysis incorporating wavelet decomposition , 2001 .