homography2d

this is a project for os labratoar .the subject is one lane bridge

压控振荡器设计过程的数字计算，无源器件参数(useful programe for the designning of VCO for passive paraameter culculation.)

用c++编的matlab曲线拟合程序,都是老师布置的数值分析作业!希望和大家交流.谢谢网站提供这个平台!(c addendum to the use of curve fitting procedures Matlab, Layout of the teachers are numerical analysis operations. We hope and exchanges. Thank you for providing this platform!)

画一个分形图Julia集的程序，分形图MATLAB环境下编程的(Draw a fractal Julia sets procedures, fractal images programming in MATLAB environment)

这是《Space-Time Codes and MIMO Systems》书中第四章的源程序，包括stbc2x1,2x2,3x1,3x2还有当信道具有相关性时的stbc2x2,4x4等多发多收等的源程序。(This is the "Space-Time Codes and MIMO Systems" source book, Chapter IV, including stbc2x1, 2x2, 3x1, 3x2 as well as when the channel has a relevance stbc2x2, 4x4, etc., etc. overcharged multiple source.)

PWM project design 12 volt inverter circiut DIAGRAM

利用MATLAB对原始数据特征提取（数据降维）((Data dimensionality reduction of raw data feature extraction using MATLAB))

柯尔莫哥洛夫熵（Kolmogorov熵，以下简称K熵）是刻划混沌系统的一个重要的量。在不同类型的动力学系统中，K熵的数值是不同的。本程序可以计算kolmogorov熵(Kolmogorov entropy (hereinafter referred to as K entropy) is an important quantity for describing chaotic systems. In different types of dynamical systems, the K entropy is different. This procedure can calculate Kolmogorov entropy.)

：该文把局部三值模式(Local Ternary Patterns, LTP)纹理特征引入Mean Shift 跟踪算法，提出了基于多 特征的Mean Shift 人脸跟踪算法以解决Mean shift 跟踪算法的鲁棒性问题。通过对LTP 纹理特征的分析、研究， 提出了一个LTP 关键纹理模型，既增强了目标的关键纹理信息，又简化了LTP 纹理模型。在此基础上，提出一 种基于LTP 关键纹理特征和肤色特征的Mean Shift 人脸跟踪算法，有效地解决了Mean Shift 算法的鲁棒性问题。 为进一步提高对快速运动目标的跟踪速度和跟踪性能，该文引入了卡尔曼滤波器对目标进行预测。实验结果表明， 该文的算法在目标定位的准确性和跟踪性能上比Mean Shift 算法均有明显的提高。(: In this paper, the texture characteristics of the local ternary patterns Local Ternary Patterns (LTP) Mean Shift tracking algorithm proposed Mean Shift face tracking algorithm based on multiple features in order to solve the Mean shift tracking algorithm robustness. Texture characteristics of LTP analysis, research, a key LTP texture model, not only enhanced the key goal of texture information, but also simplifies the the LTP texture model. On this basis, based on the LTP key texture features and color characteristics Mean Shift face tracking algorithm, effectively solved the robustness of the Mean Shift algorithm. To further enhance the fast-moving target tracking speed and tracking performance, this paper introduces the Kalman filter to predict the target. The experimental results show that the algorithm of the text in the target positioning accuracy and tracking performance than the Mean Shift algorithm to significantly improve.)

机器人模型构建，运用MATLAB中机器人工具箱进行构建。(Robot modeling, robot using MATLAB toolbox to build.)