julei

这段代码主要是实现二阶巴特沃斯高通滤波器，本段代码全部用MATLAB语言实现的。(This code is to achieve second-order Butterworth high-pass filter, the above code to achieve the full use of the MATLAB language.)

在GUI中制作标签页,压缩包内提供了程序案例及解释文档(Program examples and explanations documents produced in the GUI tab, compressed package)

功能十分强大的图论工具箱，切实可靠，能用，十分不错。(Graph Theory Toolbox)

Validity Measures for the Fuzzy Cluster

频率域建模，根据类型分为面向模拟滤波器的s域内建模和面向数字滤波器的z域内建模。 (Frequency domain modeling, according to the type of analog filters into the s-oriented domain modeling and digital filter z-oriented domain modeling.)

这个进行形象分解EMD,可以很理解EMD分解,便于学习入门EMD.(The image decomposition for EMD, EMD decomposition can be understood, easy to learn entry-EMD.)

基于MATLAB_Simulink的系统仿真技术与应用 本书首先介绍MATLAB语言的程序设计的基本内容，在此基础上系约介绍了系统仿真所必要的数值计算方法及MATLAB实现，并以Simu1ink为主要工具介绍了系统仿真方法与技巧，包括连续系统、离散系统、随机输入系统和复数系统的仿真，由浅入深介绍了模块封装技术、电力系统模块集、非线性系统设计模块集、S-函数编写与应用、Stateflow有限状态机、虚拟现实工具箱等中高级使用方法，最后还介绍了半实物仿真技术均实时控制技术。本书可作为一般读者学习和掌握MAlLAB／Simulink语言的教科书，也可作为高校理工科各类专业的本科生和研究生系统仿真类课程的教材和参考书，还可供科技工作者、教师作为学习和应用系统仿真分析技术解决实际问题的参考资料。(This book introduces MATLAB programming language, the basic content, in this based on the simulation system presented about the necessary numerical methods and MATLAB implementation, and Simu1ink introduced the system as the main tool for simulation methods and techniques, including the continuous system , discrete systems, stochastic input system and complex system simulation, Deep introduced module packaging technology, power system block set, set of nonlinear system design module, S-function and application of writing, Stateflow finite state machines, virtual reality tools use of boxes and other senior, finally introduced the loop simulation technology are real-time control technology. )

在排序学习算法经常用到的评价指标 NDCG，计算检索的效果好坏(NDCG can be used to evaluate the ranking with multilevel relevance such as irrelevance, half relevance, and relevance. )

code to test the mimo system for the ML and MZ

根据一组样本数据的均值和协方差矩阵随机产生正态分布以及对数正态分布的任意规模的样本数据。(According to a set of sample data mean and covariance matrix randomly generated normal and lognormal distribution of the sample data of any size.)