Kalman

vc和matlab混合编程，在vc中调用matlab的函数进行计算和处理，本程序中调用了matlab图像处理函数打开图像并进行灰度处理(vc and matlab mixed programming, matlab function calls are calculated and processed in the vc, the program calls the matlab image processing function to open and grayscale image processing)

This guide reviews the rules and syntax of the principle commands that comprise C and its object-oriented cousin, C++. The reference consists of 19 chapters that define operators and the standard input/output, string, character, and more.

排氣閥門的UDF，裏頭有寫著在如何的壓力底下排氣閥門會開啟，當壓力未達到時排氣閥門將會關閉(Exhaust valve UDF, inside there that says how the pressure beneath the exhaust valve opens when the pressure does not reach the exhaust valve will be closed)

数字滤波，包含：中位值滤波，算术平均滤波，去极值平均滤波，加权平均滤波，低通滤波()

LDPC码是目前通信中性能最好的纠错编码之上，这是我在Matlab下编写的LDPC基本解码算法，已经通过调试，大家共同学习(LDPC code is the best communication performance on error-correcting code, this is my prepared in Matlab basic LDPC decoding algorithm has been through debugging, U.S. co-learning)

说明：  matlab+com接口编程 这里 以 Matlab擅长的矩阵运算为例来说明基于COM的VC与Matlab接口实现方法。(matlab+ com interface to Matlab programming here at the matrix calculation as an example to illustrate the VC based on the COM interface methods and Matlab.)

一个用vc做的挖金子的游戏，有几关，可供参考(gold)

电力系统潮流计算，基于BX快速解耦算法，对IEEE14节点标准拓扑网络进行检测，能够正确快速地计算出结果。(Power flow calculation based BX fast decoupled algorithm, IEEE14 standard topology network node detection, able to correctly calculate the results quickly.)

GMM 混合高斯自适应背景维护 可以用来做行人检测 等(GMM Gaussian Mixture adaptive background maintenance can be used to make the pedestrian detection)

说明：  按FPE定阶的 源程序：fpe.cpp M序列：M序列.txt 白噪声：Gauss.txt 程序中先用依模型阶次递推算法估计模型的参数，再用fpe方法判断模型的阶次。 程序运行结果如下： n: 1 判断阶次FPE的值: 0.0096406 -0.481665 1.07868 n: 2 判断阶次FPE的值: 0.00875755 -0.446739 0.00498181 1.07791 0.0527289 n: 3 判断阶次FPE的值: 0.0087098 -0.459433 0.120972 -0.0569228 1.07814 0.0390757 0.116982 n: 4 判断阶次FPE的值: 0.000396884 -0.509677 0.4501 -0.200906 0.0656188 1.07991 -0.0156362 0.442989 0.0497236 n: 5 判断阶次FPE的值: 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771 n: 6 判断阶次FPE的值: 3.23349e-007 -1.14659 0.76933 -0.487651 0.329676 -0.10377 -0.00440907 1.07999 -0.703574 0.447253 -0.235282 0.113587 0.00479688 从以上结果可以看出，当n=5时，fpe值最小，所以这时的模型阶次和参数估计值为最优结果： 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771(err)