一个OQAM系统的OFDM仿真程序

使用matlab编程工具实现canny算子检索图像，程序已通过运行。(Finish retrieve images by canny method using matlab,and it could run.)

采用MORISON方程基于MATLAB计算大直径波浪力(small diameter waveforce)

用于计算庞加莱截面的MATLAB的源程序(MATLAB Program for Making Poincare Section)

matlab GUI串口通信，实时采集数据，曲线显示，接收和发送数据(matlab GUI serial communication, real-time data collection, curve display, receiving and sending data)

外国的一个大牛写的ply格式模型的读写程序，注释很详细，和适合学习(A large foreign cattle write ply format model reading and writing program notes in great detail, and suitable for learning)

非参数检验中K-S检验的matlab实现(Non-parametric test in the KS test matlab implementation)

真的是一个好程序，车牌识别定位程序的部分功能，GPS和INS组合导航程序。( Really is a good program, Part of the license plate recognition locator feature, GPS and INS navigation program.)

BP神经网络的整个训练过程,采用的是通用的平面波展开法,对于初学者具有参考意义，对HARQ系统的吞吐量分析，ICA（主分量分析）算法和程序，多机电力系统仿真及其潮流计算。

带转矩内环的转速磁链闭环矢量控制仿真系统，大家共同学习(The speed with torque inner loop flux vector control simulation system, we learn together)

：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.)