基于人群搜索算法的PID参数整定

基于MATLAB建立HFSS的喇叭天线的模型(Modeling of Horn Antenna Based on MATLAB)

课堂代码，相信会对大家有所帮助。大家一起学习。(Class Code)

时间序列数据分析中的梅林变换工具，计算互信息非常有用的一组程序,针对EMD方法的不足。( Time series data analysis Mellin transform tool, Mutual information is useful to calculate a set of procedures, For lack of EMD.)

说明：  李航的统计学习方法原版pdf，很好的机器学习和统计学习教材(statistical learning)

说明：  数据结构与算法-学生成绩管理系统(以顺序表来实现)(Data Structure and Algorithms - Student Performance Management System (implemented in a sequential table))

sql学习必备材料，讲解通俗易懂，很有层次，内容丰富(This book is SQL learning materials and understanding very easy and very hierarchical and riching in content)

这本书在稀疏的多尺度图像和信号处理提出了艺术状态，包括线性多尺度变换，如小波，脊波和曲波变换、非线性、多尺度变换基于中值和数学形态学算子。最近的稀疏性和形态多样性的概念描述和利用各种问题，如去噪，反问题正规化，稀疏信号分解，盲源分离，压缩感知。 这本书的理论和实践研究相结合的领域，如天文学、生物学、物理学、数字媒体应用和取证。最后一章探讨了信号处理中的一个范式转换，表明以前的信息取样和提取的限制可以用非常重要的方法加以克服。 MATLAB和IDL代码伴随这些方法和应用程序重现。 实验并说明了在相关网站上可下载的研究的推理和方法。(This book presents the state of the art in sparse and multiscale image and signal processing, covering linear multiscale transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Recent concepts of sparsity and morphological diversity are described and exploited for various problems such as denoising, inverse problem regularization, sparse signal decomposition, blind source separation, and compressed sensing. This book weds theory and practice in examining applications in areas such as astronomy, biology, physics, digital media, and forensics. A final chapter explores a paradigm shift in signal processing, showing that previous limits to information sampling and extraction can be overcome in very significant ways.)

说明：  传统经验模态分解基于信号的极值点，例如δ(t) 函数就不能用 EMD 来处理，为抑制这一影响，Huang 于 2005 年提出了一种加噪的经验模态分解方法，即集总经验模态分解（Ensemble empirical mode decomposition，EEMD）。其基本原理是在原始信号上加上幅值很小的白噪声，然后做EMD分解，使不同尺度的信号成分映射到相应阶数的IMF 上。(Traditional empirical mode decomposition (EMD) is based on the extremum of signal)

对电容层析成象的ECT断层图象 进行3维显示(Of capacitance tomography images of ECT tomography 3-D display)

说明：  本书采用案例形式，以智能算法为主线，讲解了遗传算法.免疫算法,退火算法.粒子群算法，鱼群算法,蚁群算法和神经网络算法等最常用的智能算法的MATLAB实现，本书共给出30个案例,每个案例都是一个使用智能算法解决问题的具体实例,所有案例均由理论讲解、案例背景.MATLAB程序实现和扩展阅读四个部分组成,并配有完整的程序源码。(This book uses case form and takes intelligent algorithm as the main line to explain the matlab implementation of the most commonly used intelligent algorithms, such as genetic algorithm, immune algorithm, annealing algorithm, particle swarm optimization algorithm, fish swarm algorithm, ant colony algorithm and neural network algorithm. There are 30 cases in this book, and each case is a specific example of using intelligent algorithm to solve problems, All cases are composed of theoretical explanation, case background, matlab program implementation and extended reading, and complete program source code.)