tictctoe

every possible information u need about matlab and how to use it is present here.I hope u enjoy it as much as i did

用于说话人识别初始化样本的聚类算法 调试成功(Speaker Recognition for initialization of the clustering algorithm samples)

基于结构张量的二维和三维图像增强方法，是由D.Kroon在J.Wickert编写程序基础上改进的程序，包含了五种不同的数值离散方案，包括标准离散、非负离散、隐式离散、旋转不变离散以及优化离散。分别包括matlab和c的程序。(Method of Image Enhancement Based on Structure Tensor.It includes five different schemes. )

pseudo inverse kinematics

现代信号处理的基本模型，能够有效的处理信号(Modern signal processing basic model, to be able to effectively handle the signal )

Image Texture Classification Using Combined Grey Level Co-Occurrence Probabilities and Support Vector Machines Texture refers to properties that represent the surface or structure of an object and is defined as something consisting of mutually related elements. The main focus in this study is to do texture segmentation and classification for texture digital images. Grey level co-occurrence probabilities (GLCP) method is being used to extract features from texture image. Gaussian support vector machines (GSVM) have been proposed to do classification on the extracted features. A popular Brodatz texture album had been chosen to test out the result. In this study, a combined GLCP-GSVM shows an improvement over GLCP in terms of classification accuracy.

Application protector component

基于matlab开发的手势识别,里面有测试代码和图片 还有一个可以运行的.fig文件,可以直接运行的.并且同时分享了matlab的源码,效果很不错,可以学习和参考.相比C++开发的要简单易懂，可以通过代码了解手势识别的方法和原理，可以先学习matlab版的手势识别，再尝试编写C++和opencv版的。(Gesture recognition based on MATLAB development, there are test code and pictures and one can run the.Fig file, can be directly run. And at the same time sharing matlab source code, the effect is very good, you can learn and reference. Compared to the development of C++ is simple and easy to understand, can understand the principle and method of gesture recognition through the code, gesture recognition can learn the matlab version, and then try to write C++ and opencv version.)

说明：  雷达信号处理 雷达作用距离 功率，距离，RCS(Pulse compression simulation MATLAB version, GUI procedures)

This project seeks to implement H.264 (the standard x264 is based on) to run on CUDA. Specifically we attempt to write the motion estimation module in CUDA. Motion estimation is currently the most computationally intensive portion of the H.264 encoding process. Previous attempts to parallelize this algorithm in CUDA showed sizeable speedups but sacrificed quality by ignoring the motion vector prediction (MVp). We demonstrate the viability of a hierarchical (pyramid) motion estimation algorithm in CUDA. This solution addresses the MVp problem while still taking advantage of the CUDA framework.