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用混沌理论和广义回归神经网络进行短期负荷的预测，取得了满意的效果(with Chaos Theory and the general regression neural network for short-term load forecasts, achieved satisfactory results)

南京大学的多类标签KNN分类器，对模式识别十分重要的作用，有着较好的分类效果，可以充分利用类别信息。(Nanjing university class label KNN classifier, the pattern recognition is an important role, has a good classification effect, can make full use of class information.)

一位意大利博士编写的关于online SVR的工具箱，对我启发很大。附加了Powell法优化工具(a matlab toolbox about online SVR and Powell)

说明：  Monte Carlo方法的经典教材，可以帮助你深入学习Monte Carlo方法(Monte Carlo method of classical teaching, I can help you-depth study of Monte Carlo methods)

The JPEG compression scheme is divided into the following stages: 1. Transform the image into an optimal color space. 2. Adjust Aspect Ratio 16:9 3. Digitization Scheme 4:2:0. 4. Apply a Discrete Cosine Transform (DCT) to blocks of pixels, thus removing redundant image data. 5. Quantize each block of DCT coefficients using weighting functions optimized for the human eye. 6. Encode the resulting coefficients (image data) using a Huffman variable word-length algorithm to remove redundancies in the coefficients. 7. Byte Stuffing. 8. Header JFIF 9. JPG Data Store

equalizer for LMS algorithm

In image processing, probably the most familiar is the image brightness and contrast adjustment

递归算法 [1 1 1 1 1 0 1 0 0 0 1 0 0 0 0 1 1 0 0 0 1 1 1 0 0 1 1 1 1 0] t=[0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1] 给权值赋初值 w1=eye(5,10) w2=eye(10,5) wr=eye(10,10)/3 wobias=eye(6,5)/4 wbias=eye(6,10)/3 x=ones(6,10)/3 ww2=zeros(10,5)/6 ww1=zeros(5,10)/6 wwr=zeros(10,10)/6 wwobias=zeros(6,5)/5 wwbias=zeros(6,10)/4 g=[1 1 1 1 1] f=[1 1 1 1 1 1 1 1 1 1] (Recursive algorithm)

基于matlab的语音合成以及移动基频实现变声调(speech synthesis)

关于脉冲压缩的matlab函数实现以及脉冲压缩的回波示意图(Echo schematic diagram of pulse compression matlab function to achieve pulse compression)