SDA

LPC(linear predictive coding)线性预测编码及改进型voice excited LPC源代码(LPC (linear predictive coding) linear predictive coding and improved voice excited LPC source code)

gmsk demodulation source code

纯电动汽车SIMULINK模型（包括驾驶员模型. 电池模型. 电机模型. 车辆和轮胎动力学模型等）(Simlink Model of Electric Automotive, including Driver Model. Battery Model. Electric Motor Model. Vehicle and Tire Dynamics Model and Controller Model.)

Practical_MATLAB_Applications_for_Engineers英文原版(Practical MATLAB Applications for Engineers english edition)

说明：  缨帽变换的简短小程序，在MATLAB7.11.0里环境下运行(Tasseled cap transformation of the short program, run under the environment MATLAB7.11.0)

信息论与编码中LZ系列LZ78编码源文件(LZ series of information theory and coding LZ78 encoding the source file)

MATLAB图像编程设计图像熵源码程序Programming MATLAB image image entropy source program(Programming MATLAB image image entropy source program Programming MATLAB image image entropy source program)

MATLAB FACE DETECTION FANTASTIC

一个人脸识别的小小程序 ，请各位大神们不要太吐槽了。(A face recognition a little program, please God have Do too Tucao the the.)

In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that assigns new examples into one category or the other, making it a non-probabilistic binary linear classifier. An SVM model is a representation of the examples as points in space, mapped so that the examples of the separate categories are divided by a clear gap that is as wide as possible. New examples are then mapped into that same space and predicted to belong to a category based on which side of the gap they fall on.