MATLAB70ch7

pdf file and matlab code for space time block coding for wireless communications

提取感兴趣区域的演示程序,有GDI界面的,方便实用.(Demo )

用粒子群算法实现的求函数最小值，代码简捷明了，适合刚接触粒子群算法的朋友(Minimum demand function with particle swarm algorithm, the code is simple and clear, for the fourth year Particle Swarm friends)

模式识别工具箱 包含大部分duda的《pattern classification》的习题程序(pattern recognition toolbox)

matlab编程应用100例中的图像应用(matlab Graphics application papers)

ask modulaltion and implemenatation

kalman filter在参数估计中的应用(Kalman filter to estimate the parameters of)

在matlab中用程序语言实现qpsk的仿真与模拟，简单易懂，适合初学者参考。(Matlab programming language used in the simulation and realize QPSK simulation, easy to understand, is suitable for beginners reference. )

粒子群算法是一种智能优化算法，具有良好的全局搜索能力和鲁棒性。(Particle swarm optimization algorithm is an intelligent algorithm, which has a good global search capability and robustness.)

The basic steps of the connected-component text extraction algorithm are given below, and diagrammed in Figure 10. The details are discussed in the following sections. 1. Convert the input image to YUV color space. The luminance(Y) value is used for further processing. The output is a gray image. 2. Convert the gray image to an edge image. 3. Compute the horizontal and vertical projection profiles of candidate text regions using a histogram with an appropriate threshold value. 4. Use geometric properties of text such as width to height ratio of characters to eliminate possible non-text regions. 5. Binarize the edge image enhancing only the text regions against a plain black background. 6. Create the Gap Image (as explained in the next section) using the gap-filling process and use this as a reference to further eliminate non-text regions the output.