droop

FIR Low pass filter simulation using matlab

这是一本最经典的matlab工具书，中文的，通俗易懂，更适合初学者，而且该PDF比已有的要更加清晰工整。(This is the most classic matlab books, Chinese, user-friendly, more suitable for beginners, and the PDF than the more clear and neat. )

模式识别中的bayes判别分析算法，进行逐步线性回归，小波包分析提取振动信号中的特征频率。( Pattern Recognition bayes discriminant analysis algorithm, Stepwise linear regression, Wavelet packet analysis to extract vibration signal characteristic frequency.)

emd分解中采用对称延拓消除边界效应，供大家参考学习(emd decomposition of symmetric extension used to eliminate the boundary effects)

this code is for REAL-valued signals. An implementation of JADE for both real and complex signals is also available from http://perso.telecom-paristech.fr/~cardoso/guidesepsou.html

说明：  图像浮雕化matlab程序 就好像《康熙大帝》中浮雕效果，对不同图像只要修改文件名(relief images of Matlab programs like the "Emperor Kangxi" relief and the effect of different image file name as long as the changes)

说明：  基于遗传算法的路径优化程序。内有源代码。供大家交流学习。(Path optimization program based on genetic algorithm. It has source code. For everyone to exchange learning.)

著名混沌研究人员许小可的混沌程序资料，GP方法(Well-known researchers chaos chaotic process data Hsiao Ke Xu, GP method)

：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.)

采用meanshift算法，对小目标进行跟踪，并在多种背景条件下对算法进行验证(Meanshift algorithm used for small target tracking, and in a variety of background conditions to verify the algorithm)