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提供了图像增强技术在医学方面的应用及算法，并实现了普通中值及自适应中值图像增强的不同效果，有Matlab代码(Provides image enhancement in medical applications and algorithms, and to achieve the common value and the adaptive value of different image enhancement effect has Matlab code)

Displays an image with the right size and colors and with a title

power_transfohyst,matlab仿真文件,电力电子、功率电子控制方面很有价值，调试通过(aspects of power_transfohyst, matlab simulation files, power electronics, power electronics control valuable debugging through)

16PSK调制解调程序，经过仿真，没有问题(16PSK modulation and demodulation process, through simulation, there is no problem)

完成802.11a的建模，可供通信专业研究人员参考(complete the model of 802.11a)

matlab实现数字信号处理中FIR的设计，各子函数完整。(matlab digital signal processing in the FIR design, the Functions integrity.)

Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which is promising in exposing the more complicated correlation between original high-dimensional features. In this paper, we first talk about the basic ideas of PCA and kernel PCA, and then focus on the reconstruction of pre-images for kernel PCA. We also give an introduction on how PCA is used in active shape models (ASMs), and discuss how kernel PCA can be applied to improve traditional ASMs. Then we show some experiment results to compare the performance of kernel PCA and traditional PCA for pattern classification. We also implement the kernel PCA-based ASMs, and use it to construct human face models.

画一个分形图Julia集的程序，分形图MATLAB环境下编程的(Draw a fractal Julia sets procedures, fractal images programming in MATLAB environment)

说明：  集合规划方法用于实时嵌入式系统中周期分配，可以有效提高实时系统的实时性。(Collection of real-time embedded systems programming method for distribution in the cycle, can improve the real-time systems in real time.)

Program _6_11 of prof Rappaport textbook