meanshift

在服务选择算法论文中设计的模糊权重优化规划算法的实现(Paper in the service selection algorithm weights the fuzzy optimal planning algorithm implementation)

将序列粗粒化，用于多尺度熵的计算，样本熵是多尺度熵的来源

用matlab实现了3次样条，拉格朗日。辛普生、梯形等数值分析里面的重要内容。代码可用性强，可以直接调用。另外还有实验报告，非常详细的报告。(A 3 times with matlab spline, Lagrange. Simpson, trapezoidal numerical analysis and other important content inside. Code availability strong, can be called directly. There is also experimental report, very detailed report.)

主要介绍了正交振幅调制的相关知识，包括如何识别(Mainly introduced the quadrature amplitude modulation related knowledge, including how to identify)

相位解缠和相位展开matlab程序，，里面还包含多篇介绍该相关解缠算法的文章 (Phase unwrapping and phase to commence the matlab program, which also contains many articles on the unwrapping algorithm article)

《MATLAB神经网络超级学习手册》随书光盘，《MATLAB神经网络超级学习手册》以神经网络结构为主线，以学习算法为副线，结合各种实例，目的是使读者易看懂、会应用。本书是一本简明介绍MATLAB神经网络设计技能的综合性用书。《MATLAB神经网络超级学习手册》深入浅出，实例引导，讲解详实，既可以作为高等院校理工科的研究生、本科生的教材，也可作为广大科研工程技术人员的参考用书。( MATLAB neural network super learning Handbook CD with the book, MATLAB neural network super learning manual to the neural network structure of the main line, as Vice-line learning algorithm, combined with a variety of examples is intended to enable readers to easily understand, will be applied. This book is a brief introduction to MATLAB neural network design skills and comprehensive book. MATLAB neural network super learning Handbook in layman s language, examples guidance, detailed explanation, either as colleges of science and engineering graduate students, undergraduate teaching, but also can be used as a reference the majority of scientific engineering and technical personnel of the book.)

元胞自动机 NaSch模型及其MATLAB代码(Cellular automata NaSch model and its MATLAB code)

matlab程序设计之绘图电子资料matlab Programming for drawing electronic data(matlab Programming for drawing electronic data matlab Programming for drawing electronic data)

对SLAM算法中的EKF-SLAM算法进行改进，并实现仿真程序，与EKF-SLAM V1相比，此算法更快捷，并具有很好的定位结果(Of the SLAM algorithm EKF-SLAM algorithm is improved, and implemented simulation program, compared with the EKF-SLAM V1, this algorithm is more efficient and have good positioning results)

it is very interested in the field of medical image segment