Ch4figs

In this paper, we show how support vector machine (SVM) can be employed as a powerful tool for $k$-nearest neighbor (kNN) classifier. A novel multi-class dimensionality reduction approach, Discriminant Analysis via Support Vectors (SVDA), is introduced by using the SVM. The kernel mapping idea is used to derive the non-linear version, Kernel Discriminant via Support Vectors (SVKD). In SVDA, only support vectors are involved to obtain the transformation matrix. Thus, the computational complexity can be greatly reduced for kernel based feature extraction. Experiments carried out on several standard databases show a clear improvement on LDA-based recognition

这个程序实现AMLE方法的图像插值。首先，通过入口从输入图像得到一定数量的水平集。起点只是自动选择的。然后，每个水平集的边界被提取出来，图像边界上的数据被记录。最后，通过使用ＡＭＬＥ扩展这些信息重建一个非常接近原图像的新的图像。(This program implement image interpolation by AMLE method. Firstly, get a number of level sets from an input image by thresholdding. The threshold values are chosen automatically. Then the boundaries for each level set are extracted, the image data on the boundaries are recorded. Finally, by using AMLE, extend those imformation to reconstract a new image, which will approximate the original one quitr well.)

Z-transform, like the Laplace transform, is an indispensable mathematical tool for the design, analysis and monitoring of systems. The z-transform is the discrete-time counter-part of the Laplace transform and a generalization of the Fourier transform of a sampled signal. Like Laplace transform the z- transform allows insight into the transient behavior, the steady state behavior, and the stability of discrete-time systems. A working knowledge of the z-transform is essential to the study of digital filters and systems.

Line codes of polar codes for n=8

Efficient Face Detection

Dijkstra最短路算法Matlab程序用于求从起始点s到其它各点的最短路(Dijkstra shortest path algorithm from the Matlab program used to find the starting point s to other points of the shortest)

语音孤立词识别的系统程序，包括预处理，断点检测，及其使用DTW的算法(Isolated word speech recognition system procedures, including pretreatment, break detection, and using DTW algorithm)

刚好这里有一个现成的 ，自己编程剔除数据异常值。(Here are just a ready-made, its own programming excluding data outliers.)

使用MATLAB编程，采用贝叶斯分类方法实现的一个具体程序实例，已调试成功(Using the MATLAB programming, the use of Bayesian classification to achieve a specific application instance, has been successful commissioning)

matlab启动画面，只需调用就可以了，里面有几个调用例子，看看便知(matlab splash screen, simply call on it, there are a few examples of calls to see if a glance)