exa060206

kmeans algorithm used for image processing

本章将介绍 Hitech-PICC 编译器的一些基本概念，由于篇幅所限将不涉及C 语言的标准 语法和基础知识介绍，因为在这些方面都有大量的书籍可以参考。重点突出针对PIC 单片 机的特点而所需要特别注意的地方。(This chapter will introduce the Hitech-PICC compiler of some basic concepts, lack of space will not be involved in the standard C language to introduce basic knowledge of grammar and because in these areas can have a large number of reference books. Focused features for the PIC MCU and the need of special attention.)

Gini系数典线拟合算法,包含传统数值方法与曲线拟合法比较!(Gini coefficient calculation!)

利用随机Hough变换提取二值图像中的直线(Random Hough transform to extract straight lines in binary image)

说明：  求解在弹流润滑条件下中心油膜厚度，使用温诗铸在其著作中的经验公式(Solving Central Oil Film Thickness under Elastohydrodynamic Lubrication)

OFDM的详细仿真代码，有信道编码，调制，信道估计等(OFDM detailed simulation codes, channel coding and modulation, channel estimation, etc.)

这是一个可以对随机信号进行加噪，并通过QPSK和8PSK解调后，并分析误码率的程序，为m文件，比较简单，纯粹是调用自带函数制作的(This is a random signal can add noise, QPSK and 8PSK demodulation through, and after the procedure error rate analysis for the m file, relatively simple, purely native function calls made)

Not mine code, but very usefull!

人脸数据库数据降维的Matlab实现，可将高维的人脸数据降维到3维或2维(The face database data dimensionality reduction Matlab, the face of the high-dimensional data down to 3-dimensional or two-dimensional)

说明：  一种最小二乘法的RBF网络 ---------------------------------- radical basis function neural network ------------------------------------------ clear all close all global sp k w2 b2 unitcenters alldatanum=400 traindatanum=300 testdatanum=100 sp=8 errorlimit=0.1 u=rand(1,alldatanum+10) y=zeros(1,alldatanum+10) for i=4:alldatanum+3 y(1,i)=1.5*y(1,i-1)*y(1,i-2)*y(1,i-3)/(3+y(1,i-1)+y(1,i-2)*y(1,i-2)+... y(1,i-3)*y(1,i-3)*y(1,i-3))+u(1,i)+u(1,i-1)+u(1,i-2) 。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。(radical basis function neural network ------------------------------------------ clear all close all global sp k w2 b2 unitcenters alldatanum=400 traindatanum=300 testdatanum=100 sp=8 errorlimit=0.1 u=rand(1,alldatanum+10) y=zeros(1,alldatanum+10) for i=4:alldatanum+3 y(1,i)=1.5*y(1,i-1)*y(1,i-2)*y(1,i-3)/(3+y(1,i-1)+y(1,i-2)*y(1,i-2)+... y(1,i-3)*y(1,i-3)*y(1,i-3))+u(1,i)+u(1,i-1)+u(1,i-2) 。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。)