全面的ID3决策树分类算法完整程序

这是一个关于matlab的电子书，适合初学者，讲解matlab基础知识，simulink，notebook等，是一本比较全面的书籍，有部分程序(This is a matlab about the e-books, suitable for beginners, basic knowledge of matlab on, simulink, notebook and so on, are a more comprehensive books, has some of the procedures)

The following code implements a kernel Wiener Filter algorithm in MATLAB. The algorithm dependes on the eigenvalue decomposition, thus only a few thousand of data samples for training dataset is applicable so far.

clossed loop boost converter mpdel

利用matlab实现的最小二乘法的计算，可以利用在处理信号和进行数值计算的时候(Using matlab realize the least squares method of calculation can be utilized in signal processing and numerical calculation time)

无线通信中继协作功率控制相关代码，基于通信资源的有效分配,比如中继选择和功率控制等， 多中继感知协作通信和功率控制技术是无线通信领域中尤为重要。(Wireless communication relay coordination related generation, power control depends on the communication efficient allocation of resources, such as relay selection and power control, relay more cognitive collaborative communication and power control technology is very important in the area of wireless communication. )

解决vrp问题的ALNS的matlab算法(Matlab algorithm of ALNS for VRP Problem)

极大似然参数辨识，以及递推的极大似然参数估计应用示例（加上有色噪声）。(Maximum likelihood parameter identification, and recursive maximum likelihood parameter estimation application examples (plus colored noise).)

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)

基于BorlandC_Builder和MATLAB混合编程的仿真应用.pdf(based on MATLAB and mixed BorlandC_Builder Simulation Application Programming. P df)

多目标非线性约束的粒子群算法，采用灰度理论，混沌理论，动态惩罚函数，可针对任何复杂函数进行优化，效果很好(Nonlinear constrained multi-objective particle swarm algorithm, using gray theory, chaos theory, dynamic penalty function can be optimized for any complex function, the effect is very good)