hurst-estimators

MATLAB下的GPS_tool 包括最基本的算法和实例(navigation gps in matlab)

changes one color of text to another color

对正弦信号进行傅里叶变换，并对比不同的信号长度与采样频率对结果的影响(Fourier transform of the sinusoidal signal and contrast the different length of the signal with the sampling frequency results)

minimization of error using adaboost classifier for a program.

rssi定位算法，极大似然估计法，最小二乘法，代码，极大似然估计法(rssi localization algorithm)

moues from video detection

A general technique for the recovery of signicant image features is presented. The technique is based on the mean shift algorithm, a simple nonparametric pro- cedure for estimating density gradients. Drawbacks of the current methods (including robust clustering) are avoided. Feature space of any nature can be processed, and as an example, color image segmentation is dis- cussed. The segmentation is completely autonomous, only its class is chosen by the user. Thus, the same program can produce a high quality edge image, or pro- vide, by extracting all the signicant colors, a prepro- cessor for content-based query systems. A 512  512 color image is analyzed in less than 10 seconds on a standard workstation. Gray level images are handled as color images having only the lightness coordinate(A general technique for the recovery of sig ni cannot image features is presented. The techni que is based on the mean shift algorithm, a simple nonparametric pro-cedure for estimat ing density gradients. Drawbacks of the curren t methods (including robust clustering) are av oided. Feature space of any nature can be proces sed, and as an example, color image segmentation is dis-cussed. The se gmentation is completely autonomous. only its class is chosen by the user. Thus, the same program can produce a high quality edge image, or pro-vide. by extracting all the signi cannot colors, a prepro- cessor for content-based query syste ms. A 512,512 color image is analyzed in less than 10 seconds on a standard workstation. Gray 4ISR l images are handled as color images having only the lightness c)

A self-organizing map (SOM) or self-organizing feature map (SOFM) is a type of artificial neural network (ANN) that is trained using unsupervised learning to produce a low-dimensional (typically two-dimensional)

DFIG的电网侧变换器模型，内含可以设置的理想电网电压正弦波(Over grid voltage sine wave DFIG grid side converter model, you can set the contents of)

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