Chapter9

该程序用于求解时间延迟t和嵌入维数m，该方法不同于自相关函数法和gp法，可以同时求解出两个量t和m的值，非常方面，在求解lyapunov指数时经常用到该方法(The procedure used to solve the time delay t and the embedding dimension m, the method is different from the self-correlation function gp method can solve the two quantities t and the value of m, the very aspect, often used to solve the lyapunov exponentthe method )

本文通过matlab仿真，比较线性调频信号的FFT和STFT，并研究了信号中混入各种噪声后如何处理。(In this paper, matlab simulation, comparison of the FFT and linear FM signal STFT, and studied all kinds of noise signals mixed How to handle.)

MIMO Channel Capacity has been calculated using ergodic and outage capacity of correlated MIMO channels..

This MATLAB code demonstrates the finite-difference frequency-domainmethod by modeling transmission and reflectance from a photonic crystal.(This MATLAB code demonstrates the finite-difference frequency-domain method by modeling transmission and reflectance from a photonic crystal.)

内点法对非凸非线性规划的解法，求得最优化的解。(Interior point method for solution of non-convex nonlinear programming, to achieve optimum solution.)

说明：  针对Hénon map,找出其稳定点，. 以及在参数确定的情况下绘画出其分岔图，计算李雅普诺夫指数，最后做出时域图 (For Hénon map,1) Find the fixed points of periods one and two for the Hénon map. 2) Investigate the bifurcation diagrams for the Hénon map by plotting the x_n values as a function of α for β = 0.4. 3) Write a Matlab or Maple program to compute the Lyapunov exponents of the Hénon map where α=1.2 and β = 0.4. 4) Use the OGY algorithm to stabilize a point of period one in the Hénon map where α=1.2 and β = 0.4.)

prozgui是一款Linxu下著名的下载工具，基于fltk库。这个包是最新版本，但不含安全补丁。请到prozgui的主页查看相关的安全问题。(prozgui A Linxu is under the famous download tool, based on the FLTK. This package is the latest version, but not security patch. Prozgui invited to the Home Show related security issues.)

This is an archive for background remove images.

matlab下运行有界面，实现对特定图片的处理，可以设定参数值(run a matlab interface to achieve a specific image processing parameters can be set)

经验模态分解工具箱，用于处理复杂信号的特征提取十分有效(Empirical mode decomposition toolbox for dealing with complex signal feature extraction is very effective)