Gockenbach-M.S

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.

带有级比调整的灰色预测代码 在灰色预测之前做级比检验，降低相对误差(GREY MODEL)

空时信号处理的基础程序，在matlab上运行。(space-time adaptive processor)

根据已给数据，画出风场示意图。有图例，方向。(draw wind field)

用钱买回来的资料.利用CMOS锁相环芯片实现ASK信号调制与解调(CMOS PLL chip using ASK modulation and demodulation)

说明：  RKF78积分的Matlab源码程序，可以实现高精度的积分(RKF78 integral Matlab source program, you can achieve high-precision integral)

通信系统基带传输系统中的窗函数法设计滤波器(Communication system baseband transmission system window function design filters)

Recent work by Petricoin and Liotta and co-workers (Petricoin et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet. 2002 Feb 16 359(9306):572-7. PMID: 11867112) has generated a lot of excitement and controversy. This example shows some ways that MATLAB can be used to read, visualize, pre-process (base-line correction, resample) and classify the data. The data can be downloaded from http://home.ccr.cancer.gov/ncifdaproteomics/ppatterns.asp (Recent work by Petricoin and Liotta and co-workers (Petricoin et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet. 2002 Feb 16 359 (9306) :572-7. PMID: 11867112) has generated a lot of excitement and controversy. This example shows some ways that MATLAB can be used to read, visualize, pre-process (base-line correction, resample) and classify the data. The data can be downloaded from http://home.ccr.cancer. gov/ncifdaproteomics/ppatterns.asp)

This a code for adaptive Histogram equalzation

水纹干涉图样. 可以自由设置两个波源的位置,振幅以及频率.形成水纹干涉图样并动画展示.(Waterlines interference pattern. the two wave source location, amplitude and frequency can be set freely . )