Applied-Numerical-Methods-Using-MATLAB---Yang-Cao

Introduce how to use matlab to solve many variety problems.

参考文献《基于泰勒级数展开的蜂窝TDOA 定位算法》以及 《基于Chan氏算法和Taylor级数展开法的协同定位方法》对Taylor算法进行仿真；认定基站数目为5个；(The Talyor algorithm in the TDOA location based on the CDMA cell network)

频谱感知中基于自适应阈值的能量检测算法研究 频谱感知能力是认知无线电通信的一个重要前提和关键技术，而能量检测技术作为传统的信号检测方法的基础，具有容易实现，低计算复杂度，不需先验知识等优点，具有重要的研究价值和应用前景。(Energy Detection Algorithm)

说明：  现代通信系统 使用matlab 刘树堂译 中文版pdf(The use of MATLAB in modern communication system)

程序作用是用于典型混沌时间序列的混沌特性分析。(Application for analysis chaotic characteristics of typical chaotic time series.)

重点参考文章！ PA Mazen 2002 Performance analysis of two-hop relayed transmission over rayleigh fading channels 介绍无线中继的文章 比较适合入门的同学 而且内附matlab代码 可以仿真做出全部结果(Key reference articles! PA Mazen 2002 Performance analysis of two-hop relayed transmission over rayleigh fading channels introduce wireless repeater articles for starters students with full simulation matlab code can make all results)

说明：  DOA中的经典，music算法，还有说明，亲测很好用，分享给大家(music DOA in the classic, music algorithm, there are instructions, pro test is very easy to use, share with you)

state space model of system sampling time

北京航空航天大学出版社的matlab从零进阶第四章节的小程序(Matlab Beijing University of Aeronautics and Astronautics Press from zero advanced fourth chapter applet)

说明：  CA算法可以将数量型属性划分成若干个优化的区间，它综合了分层聚类于划分聚类的优点，对于给定的不同的初始类个数，CA算法能随着迭代过程的不断进展改变类的数目，一些竞争力差的类即类的基数小于给定阙值的类将在迭代过程中不断消失，最终得到能够有效体现数据实际分布情况的优化聚类个数。(CA algorithm for quantitative attributes can be divided into a number of the interval optimization, hierarchical clustering which combines the advantages of clustering in the division, for a given number of different types of initial, CA algorithm as the iterative process the continuous progress of change in the number of categories, some categories of poor competitiveness of the base type that is less than the value of a given category Que iterative process will continue to disappear and eventually be able to effectively reflect the actual distribution of data to optimize the number of clustering.)