Chap_4

VC和MATLAB混合编程 使用MATLAB工具函数计算(VC and hybrid programming using MATLAB tool MATLAB function to calculate)

超完备集合上的稀疏表达算法，K-SVD算法(k-svd)

Learning Automata Algorithms A collection of machine learning programs which contains some of Learning Automata algorithms such as Tsetline, Krinisky, Krylov, LRI, LIP, LRR, LReP, SoftMax, SampleAverage and Random strategy. All of these developed in MATLAB 6.5

给出卫星适当的初始位置和速度，利用其运动微分方程，求出2－3个周期内的轨道，并画出机械能和动量矩的大小随时间变化的曲线。(Given appropriate initial satellite position and velocity, using the equations of motion, find the 2-3 cycle track, and draw mechanical energy and angular momentum of the size of the curve over time.)

灰度共生矩阵和灰度梯度共生矩阵的提取方式，是比较重要的纹理特征提取方法，用matlab实现的(The GLCM and gray gradient co-occurrence matrix extracted, texture feature extraction method, using matlab to achieve)

The basic steps of the edge-based text extraction algorithm are given below 1. Create a Gaussian pyramid by convolving the input image with a Gaussian kernel and successively down-sample each direction by half. (Levels: 4) 2. Create directional kernels to detect edges at 0, 45, 90 and 135 orientations. 3. Convolve each image in the Gaussian pyramid with each orientation filter. 4. Combine the results of step 3 to create the Feature Map. 5. Dilate the resultant image using a sufficiently large structuring element (7x7 [1]) to cluster candidate text regions together. 6. Create final output image with text in white pixels against a plain black background.

隐马尔可夫模型参数的极大似然估计,用来求解HMM的第三个问题(HMM maximum likelihood parameter estimates used to solve the third problem HMM)

说明：  用MATLAB实现雷达回波信号的仿真(Using MATLAB realize radar signal simulation)

power electronics-matlab

在MATLAB中实现图像的局部二值模式处理，运行test函数即可使用。(Achieve a partial image in MATLAB binary mode processing, running test functions can be used.)