Simple_Skin_segmentation

给出了关于卡尔曼滤波器的详细说明，是新人学习必备(Given on a detailed description of Kalman filter is a new learning required)

It is the corresponding testing module of the function that is specified in the training phase. test_set is a NxD matrix where N is the number of samples in the test set and D is the dimension of the feature space. true_labels is a Nx1 matrix specifying the class label of each corresponding sample s features (each row) in test_set . adaboost_model is the model that is generated by the function ADABOOST_tr .

说明：  利用costas环实现载波同步的matlab程序，载频10mHz(Costas loop to achieve carrier synchronization using the matlab program, carrier frequency 10mHz)

用傅里叶变换对地震信号进行时频分析，通过修改参数可以深刻的认识傅里叶变换在时频分析中的意义，适合地震信号研究的初学者。(Fourier transform of the seismic signal frequency analysis, parameter changes can be profound understanding of Fourier transform in the time-frequency analysis of significance for the seismic signals of beginners.)

卡尔曼滤波实例分析与仿真源代码，帮你熟悉了解卡尔曼滤波原理和编程方法(Analysis and Simulation of Kalman Filtering source code examples to help you become familiar with the Kalman filter theory and programming methods)

labview for example embrassion

OTSU Gray-level image segmentation using Otsu s method. Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern. 9:62-66 1979). Thresholds are computed to maximize a separability criterion of the resultant classes in gray levels. OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the corresponding Iseg is therefore a binary image. The pixel values for Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ... [Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability criterion within the range [0 1]. Zero is obtained only with images having less than n gray level, whereas one (optimal value) is obtained only with n-valued images.

图像处理经典算法，基于PCA的人脸识别matlab代码(Matlab code of face recognition based on PCA)

matlab 学习资料，对于初学者掌握matlab 使用有很大帮助(matlab )

Simulacion de transmision por multiplexacion de division de frecuencia de cuatro audios.