图11-2-6DOG小波时域和频域波形

说明：  matlab中基于瑞利衰落信道的模型仿真(matlab based on Rayleigh fading channel model simulation)

基于Hopfield的神经网络算法的MATLAB编程求解旅行商问题，程序复杂，但是求解效果很好(Hopfield of neural network algorithm based on the MATLAB program for solving the traveling salesman problem, complicated, but works well for solving)

多变量微分方程的PID控制程序，通过调整一个参数使得六个变量都的到控制(PID control procedures for multi-variable differential equations, by controlling a parameter makes the six variables are to control)

a.阅读的图像img_1.tif，img_2.png的文件夹中，并 他们展示于一体，这两个数字分别。 （参考函数：imread, imshow, figure, subplot） b.在matlab，观察从工作区中的图像信息面板 c.分别使用size, imfinfo,whos等功能获得的图像信息 d.添加标题的图像。 （参考函数：title） Ë 。下面的代码实现的M文件编辑器 f=imread(‘img_1.tif’) imshow(f) set(figure(1), NumberTitle , off , Name , my first image’) 观察结果，并确定的功set() f。保存img_1.tif目录“D： imagetest”。如果该文件夹不 存在，请首先创建这个新的文件夹。 （参考函数：imwrite） (a. Read the images img_1.tif, img_2.png given in the folder, and show them in one and two figures respectively. (referenced function: imread, imshow, figure, subplot) b. In matlab, observe the images information from the workspace Panel c. Use size, imfinfo,whos,etc functions to obtain image information respectively. d. Add title to the images. (referenced function: title) e. Implement the following codes in the M-file Editor f=imread(‘img_1.tif’) imshow(f) set(figure(1), NumberTitle , off , Name , my first image’) observe the result, and determine the function of set() f. Save img_1.tif to the directory “d:imagetest”. If the folder does not exist, please create this new folder first. (referenced function: imwrite))

说明：  read from sp3 rinex in matlab

《matlab有限元分析与应用》书后源代码，在matble中运行，对于有限元的初学者很有用。("Matlab Finite Element Analysis and Application" after the source code, in matble run, FEM for beginners useful.)

空时自适应处理（全自由度），包括杂波谱图仿真，最优处理器仿真图等(Space-time adaptive processing (all degrees of freedom), including the clutter spectrum simulation, optimal processor simulation diagrams)

matlab下雅克比在数值计算中有很好的应用!(Jacobian under matlab numerical calculation in a very good application!)

对具有随机噪声的二阶系统的模型辨识(用改进的神经网络MBP算法辨识)(of random noise with the second-order system model (used to improve the neural network algorithm for identification MBP))

说明：  梯度下降法对数据进行分类，并取了四个数据点，对分类进行证明。对梯度下降法有详细的备注。(The gradient descent method classifies the data and takes four data points to prove the classification. There are detailed remarks on gradient descent method.)