GUImatlab

说明：  Ar气在CO2激光作用下的电离matlab程序代码。(co2 laser induced Ar ionzation matlab codes.)

说明：   有一个长度为整数L(1<=L<=10000)的马路，可以想象成数轴上长度为L的一个线段，起点是坐标原点，在每个整数坐标点有一棵树，即在0,1,2，...，L共L+1个位置上有L+1棵树。 现在要移走一些树，移走的树的区间用一对数字表示，如 100 200表示移走从100到200之间（包括端点）所有的树。 可能有M(1<=M<=100)个区间，区间之间可能有重叠。现在要求移走所有区间的树之后剩下的树的个数。 输入： 两个整数L(1<=L<=10000)和M(1<=M<=100)。 接下来有M组整数，每组有一对数字。 输出： 可能有多组输入数据，对于每组输入数据，输出一个数，表示移走所有区间的树之后剩下的树的个数。(Has a length of integer L (1 &lt = L &lt = 10000) of the road, one can imagine a number line segment of length L, the starting point is the coordinate origin, each integer coordinate points in a tree, i.e. 0,1 , 2, ..., L total has L+1 L+1 positions on the tree. Now to remove some trees, tree removed by a range of digitally represented, such as 100 200 represents removed (inclusive) between 100 and 200 all the trees. There may be M (1 &lt = M &lt = 100) intervals, there may be overlap between the intervals. Now, after the number of trees require the removal of all remaining sections of the tree. Input: two integer L (1 &lt = L &lt = 10000) and M (1 &lt = M &lt = 100). Then there is an integer M groups, each with a pair of numbers. Output: there may be multiple sets of input data, for each set of input data, the output of a number indicating the number of the removal of all remaining sections of the tree after tree.)

基于CFA插值特征的图像篡改检测。通过检测不同区域的CFA插值特征来定位篡改区域。(Based on the characteristics of the CFA interpolation image tamper detection. By testing different regional characteristics of CFA interpolation to locate the tampering. )

基于matlab的深度学习算法，可用于深度学习入门(Based on the depth of learning matlab algorithm can be used for deep learning, such as doors)

生成13位GOLD序列，实验中用到了 ，在此分享。(13 GOLD generated sequence, the experiment used, and in this share.)

布莱克斯科尔斯模型，应用于金融工程领域。(Black Scholes Model, to price the European Call Option and plot the graph. The model is highly used in quantitative field.)

boost电路仿真，元件采用的是igbt，用触发脉冲触发的(boost simuliation The components are IGBT and triggered by trigger pulse.)

pv cell modeling SIMULINK PV CIRCUIT MODEL

建立一个径向基神经网络，对非线性函数y=sqrt(x)进行逼近，并作出网络的逼近误差(The establishment of a radial basis function neural network, the nonlinear function y = sqrt (x) to approximate, and make the network approximation error)

绘制3层正弦信号，对之进行小波分解（5层）重构5层逼近信号和细节信号。(Draw 3-layer sinusoidal signals, the wavelet decomposition (5 layer) Reconstruction of 5-layer approximation signal and detail signal.)