MATLAB-7

his algorithm was proposed by Quinlan (1993). The C4.5 algorithm generates a classification-decision tree for the given data-set by recursive partitioning of data. The decision is grown using Depth-first strategy. The algorithm considers all the possible tests that can split the data set and selects a test that gives the best information gain. For each discrete attribute, one test with outcomes as many as the number of distinct values of the attribute is considered. For each continuous attribute, binary tests involving every distinct values of the attribute are considered. In order to gather the entropy gain of all these binary tests efficiently, the training data set belonging to the node in consideration is sorted for the values of the continuous attribute and the entropy gains of the binary cut based on each distinct values are calculated in one scan of the sorted data. This process is repeated for each continuous attributes.

实现云模型与分形的树模拟，用MATLAB和VB混合编程实现(achieve cloud model and fractal tree simulation with MATLAB and VB Programming)

matlab的s函数编程教程。来自企业的电子书(matlab s function programming tutorial. From the corporate e-book)

Sesia, S. - LTE, The UMTS Long Term Evolution

拉普拉斯方程的MATLAB有限元求解三维

基于一个二阶线性系统实例，介绍了全程滑模变结构控制，实现了系统的鲁棒性特点。(Global sliding mode variable structure control, based on a second order linear system instance, the robustness of the system characteristics.)

三种方法被提出，以指导遗传算法的收敛向所需的解决方案：偏压以便有利于搜索空间的特定区域的探索初始群体的产生，根据归因不同的权重的目标和比较解的目标的加权和（WPMOGA），并且包括最小和最大的交易客中的解决方案（G-MOGA）的比较。三种方法进行，以发现是否意味着增加一些新的传输线的解决方案上测试的网络的扩展的问题。加权和的方法似乎是低效率的，而其他两个成功引导随机群体朝少添加的行的解决方案。偏压初始种群是最简单的实施而所提供的最佳结果，但容易使用该方法的依赖于所考虑的问题，并且它可能不是可实现的，在大多数的多目标的问题。反之，在G-MOGA是通用的，可以在任何类型的多目标的问题予以实施。结果被通过的可靠性核心措施，这表明在网络中的节点的相对重要性装置根据连接节点的，程度进行了分析，其接近到网络的其他节点，其中最可靠的存在网络的路径，并除去该节点到网络的可靠性的效果。

A program for solving system of differential equations using runge kutta method.

星历计算 可以自己调试运行下 很好的一个matlab程序 根据一本书编写的(Ephemeris calculation a good matlab programme)

三相电压型spwm逆变器仿真 IGBT模型已修改 电流跟踪型逆变器仿真(three v spwm inventor)