shipin

IMPARARE IL C++ in 2 ore e mezzo? Modulo-000

SUBTRACTIVE CLUSTERING ALGORITHM

说明：   a simulation describe how the extract the CP factor in wind turbines

《MATLAB外部接口编程》， 超星的文件(" MATLAB external interface programming," the paper Superstar)

对MATLAB的学习这会很有用，大家学习学习(On MATLAB will be useful to learn that we learn from)

Double Density Wavelet Soft

灰色预测GM（1，1）模型的matlab源代码，包括预测模型的建立(Gray prediction GM (1,1) model matlab source code, including the prediction model)

用来做灰色预测的源代码，适用于小样本的预测，精度较高(Used for gray prediction of source code, applies to small sample forecast accuracy)

SPIHT-set partitioning in hierarchical tree algorithm. it is also used for compression. here list of insignificant pixels, list of significant pixels, list of significant sets

A. Fusion at the Feature Extraction Level The data obtained from each sensor is used to compute a feature vector. As the features extracted from one biometric trait are independent of those extracted from the other, it is reasonable to concatenate the two vectors into a single new vector. The primary benefit of feature level fusion is the detection of correlated feature values generated by different feature extraction algorithms and, in the process, identifying a salient set of features that can improve recognition accuracy [14]. The new vector has a higher dimension and represents the identity of the person in a different hyperspace. Eliciting this feature set typically requires the use of dimensionality reduction/selection methods and, therefore, feature level fusion assumes the availability of a large number of training data.