voa

不错的chirp方向识别例程，可对chirp进行分解，供参考(Good chirp direction identification routine, the decomposition of the chirp for reference)

说明：  该程序通过模仿生物的遗传特点，解决全局最优解的问题(The program solves the problem of global optimal solution by imitating the genetic characteristics of organisms)

simulink 采样系统的一个简单的例证，采样周期为0.1，使用了保持器(simulink sampling system, a simple example, the sampling period is 0.1, the use of retainer)

Computing an Exact Gaussian Scale-space 介绍了一种图像去模糊算法 保护论文和源代码 用c 编写(Computing an Exact Gaussian Scale-space introduce a debulrring algorithm, including a source C code)

perform cross correlation between two time series

这是我自己编写的压缩感知图像重构的算法，用于学习，先稀疏，再观测系数，最后重建(This is your perception image compression algorithm used to study and review, thin, and observation of the reconstruction and )

Its is Assump.m used in antennae theory and applications. Can be run matlab 2007 or higher.

基本的调制解调程序集(包括BPSK,QPSK,QAM,GMSK等)(Basic modulation and demodulation assembly (including BPSK, QPSK, QAM, GMSK, etc.))

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.

自适应信号处理工具箱，国外经典通信教材的配套源代码(Adaptive Signal Processing Toolbox, foreign classic communications materials supporting source code)