KNN1

使用matlab对二维图像进行压缩编码，用哈弗曼函数进行(Use matlab for the two-dimensional image compression, Ha Fuman function)

说明：  这里面是一个灰色预测模型的程序，在预测方面有着很重要的作用(There is a gray prediction model program, over the forecast has a very important role)

可以定位彩色车牌.而且定位的准确率是比其它的定位方法要高一些. (location )

这个是机械领域的二级展开圆柱斜齿减速器 设计的一些计算程序 自动化不高 要根据情况 改一些数据 但程序里有详细的说明 高手可以把它用GUI实现了(This is the area of secondary mechanical start helical gear reducer design automation of some of the computer program does not change according to the situation Gaoyao some data but the program in detail as master, it can be achieved with a GUI)

给出完整的通信系统和多径通信信道，并使用带RLS算法的判决反馈均衡器进行均衡。 内有详细注释。 在DFE(lms算法）的基础上，采用RLS算法 产生 0 1 序列--> QPSK映射 --> 上变频 --> 信道（多径、加噪） --> 下变频 --> LMS算法均衡 --> 解映射、判决 --> 求误码率、星座图(This progam include a complete communication system with a multipath channel, based which decision feedback equalization with RLS algrithem is implemented.)

Box jekkins metodology on time series forecast video

this program to compute the shoot function

一般教材上讲诉的是如何用MATLAB实现一元或二元的霍夫曼编码，而这个是实现r（r>2）元的霍夫曼编码。(Generally speaking textbook complaint is how to use MATLAB to achieve mono- or dicarboxylic Huffman encoding, and this is the realization of r (r> 2) yuan Huffman coding.)

该演示中包含的代码演示如何氡相似的功能，可以用来提高（以及部分）在Connectome电磁图像单元格边界。 请举出下列文件如果您发现此代码有用： Ritwik库马尔，阿梅里奥五雷纳和Hanspeter Pfister说“氡样的特点及其应用Connectomics”，接受，IEEE计算机学会研讨会在生物医学图像分析（MMBIA）2010年数学方法 http://seas.harvard.edu/〜 rkkumar radonLikeFeaturesDemo.m：演示边缘增强用氡相似的功能， getEdgeFeatures.m：助手为高斯函数的二阶导数滤波器 makeBarFilters.m：助手为高斯函数的二阶导数滤波器 sample.png：示例图像在此演示使用(The demo included in the code demonstrates how Radon-Like Features can be used to enhance (and segment) cell boundaries in Connectome EM images. Please cite the following paper if you find this code useful: Ritwik Kumar, Amelio V. Reina & Hanspeter Pfister, “Radon-Like Features and their Application to Connectomics”, accepted, IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA) 2010 http://seas.harvard.edu/~rkkumar radonLikeFeaturesDemo.m : Demonstrates edge enhancement using Radon-Like Features getEdgeFeatures.m : Helper function for Gaussian Second Derivative Filters makeBarFilters.m : Helper function for Gaussian Second Derivative Filters sample.png : Sample image for use in this demo )

基于功率谱相减的语音消噪增强法程序，采用硬阈值法(Power spectrum subtraction based speech denoising Enhancement Act program, using hard-threshold)