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EEMDSpectralAnalysis
- 全称为Ensemble Empirical Mode Decomposition (集合经验模分解)(Wu and Huang, 2009)，是EMD（经验模分解）(Huang et al. 1998 Huang and Wu, 2008)的改进算法，有效的解决了EMD的混频现象。 -Called the Ensemble Empirical Mode Decomposition (a collection of empirical mode decomposition) (Wu and Hua
Neural-Network-Ensemble
- 神经网络集成，集成了最近几年一些关于神经网络发展的文献，适合深入了解的筒子学习-Neural network integration, integration in recent years some of the literature on the development of neural networks, suitable for in-depth understanding of the cheese learning
01._THE_MULTI-DIMENSIONAL_ENSEMBLE_EMPIRICAL_MODE
- A multi-dimensional ensemble empirical mode decomposition (MEEMD) for multi dimensional data (such as images or solid with variable density) is proposed here. The decomposition is based on the applications of ensemble empirical mode decomposition
Ensemble-Classifier-for-Concept-Drift-Data-Stream
- In this era an emerging filed in the data mining is data stream mining. The current research technique of the data stream is classification which mainly focuses on concept drift data. In mining drift data with the single classifier is not sufficient
GSI-3DVar-Based-Ensemble
- 3DVar-Based Ensemble–Variational Hybrid Data Assimilation for NCEP 基于三维变分和集合方法的耦合研究 -GSI 3DVar-Based Ensemble–Variational Hybrid Data Assimilation for NCEP