plotSmithChart

通信系统链路可靠性和节点可靠性的计算并将两者综合(Communication link reliability and node computing system reliability and a combination of both)

有限元薄板结构的分析 刚度方程 matlab程序(Analysis of finite element stiffness equation matlab program sheet structure)

The radiation pattern, intensity and directivity of doplh chebyshev algorithm are shown in this matlab code

智能天线的核心技术之一是波达方向估计,在无线通信中具有重要作用。MUSIC算法是一种经典的DOA估计算法,但因其计算量大、对于相干及小信噪比信号无法分辨等缺陷,故有较多的改进算法被提出。文中研究了求根MUSIC算法、基于空间平滑技术的MUSIC算法、改进MUSIC算法及修正MUSIC算法。通过仿真分析了角度间隔、信噪比、信号相干对改进MUSIC算法分辨率的影响。以上几种改进MUSIC算法进一步发挥了该算法高分辨率的优势,且有利于其在智能天线方面的应用。(One of the core technology of smart antenna is DOA estimation, which plays an important role in wireless communication. MUSIC algorithm is a classic DOA estimation algorithm, but because of its large amount of computation, the coherent and small signal to noise ratio of the signal can not be resolved and other defects, so there are many improved algorithms are proposed. This paper studies the root MUSIC algorithm based on spatial smoothing technique, the improved MUSIC algorithm, MUSIC algorithm and modified MUSIC algorithm. The influence of angle interval, signal to noise ratio and signal coherence on the resolution of the improved MUSIC algorithm is analyzed by simulation. The above improved MUSIC algorithm to further play the advantage of the high resolution of the algorithm, and it is conducive to the application of the smart antenna.)

从混有呼吸噪音的信号中，提取呼吸信号，完成去除呼吸信号的功能(Mixed with noise from the respiratory signal, respiratory signal extraction, complete removal of the function of respiratory signal)

matlab程序画图，常见分形图，function cantor(A,B) c=1 p=0 figure hold on plot([A(2) B(2)],[A(1) B(1)], r* ) while norm(A(1,:)-B(1,:))>=1 C=[] D=[] for i=1:size(A,1) a=A(i,:)+(B(i,:)-A(i,:))/3 b=A(i,:)+2*(B(i,:)-A(i,:))/3 C=[C A(i,:) b] D=[D a B(i,:)] end A=C B=D p=p+1 (matlab program drawing, common fractal images function cantor(A,B) c=1 p=0 figure hold on plot([A(2) B(2)],[A(1) B(1)], r* ) while norm(A(1,:)-B(1,:))>=1 C=[] D=[] for i=1:size(A,1) a=A(i,:)+(B(i,:)-A(i,:))/3 b=A(i,:)+2*(B(i,:)-A(i,:))/3 C=[C A(i,:) b] D=[D a B(i,:)] end A=C B=D p=p+1 )

入门级代码，matlab源代码的第一部分(Entry-level code, matlab source code for the first part of the)

very important for pattern recognition using neural networks

THIS PROGRAMME IS A SOLUTION OF AN EXERCICE OF THE BOOK OF ROBOTICS OF CRAIG.

Matlab工具箱 - 《复分析基础及工程应用 第3版》，这是书中所带工具箱，与Matlab本身的复分析工具箱相背相比，更适用于教学。(Matlab Toolbox- Fundamentals of Complex Analysis with Applications to Engineering and Science the 3rd version,compared with the similar toolbox of matlab,this toolbox is good at teaching.)