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rbf RBF网络用于函数逼近 ，过程很适合初学者懂的。很详细，很容易的！(RBF RBF network for function approximation, the process is very suitable for beginners understand. Very detailed, )

calculate the 3d voxels (in 2d pixel)

高质量的基于感兴趣编码的仿真程序，可以直接运行，观看仿真结果(Interest coding based on high-quality simulation procedures can be directly run to watch the simulation results)

利用Matlab建立主电网发生故障时的交流微电网模型。交流微网运行在480V，从120 kV电网交流输入降压11kV然后走到480V。故障发生在t 10秒。(Using Matlab to establish the AC micro grid model of the fault of the main power grid. AC microgrid runs in 480V, 120 kV AC input to buck 11 kV and then go to 480V. Failure occurred at t 10 seconds.)

说明：  梯度法是最优化方法中由于球多变量最优值的一种方法(Gradient method is the most optimal method of multi-variable optimal value due to the ball a way of)

simulink model for ac-dc buck converter with voltage mode control

Simple but effective example of "Region Growing" from a single seed point. The region is iteratively grown by comparing all unallocated neighbouring pixels to the region. The difference between a pixel s intensity value and the region s mean, is used as a measure of similarity. The pixel with the smallest difference measured this way is allocated to the region. This process stops when the intensity difference between region mean and new pixel becomes larger than a certain treshold

Learning_random.m : 随机选择样例，从（90）pool里随机选择样本，删除版本空间树的数量 activeLearning.m:根据最大熵原则,从pool里选择样本，删除版本空间树的数量 getlabel.m:根据树和测试样例，得到根据该树得到的类标 getTrees.m:从提供的大量树结构(随机生成的)中，随机挑选一定数量的树(如果该树的叶子节点无类标随机添加) RandomCreateTree_d_unbalance:根据样本点割点中的非平衡割点建造树， RandomCreateTree_d_all.m:根据所有样本点的割点建造树 randomdata.m：给定属性取值，造数据 randomselect.m:从数据中随机选择一部分作为 showTree.m:显示树的结构 test.m:给出树，测试样例，得到正确率(Learning_random.m: randomly selected sample, randomly selected sample from (90) pool the The deleted version space tree quantity activeLearning.m: selecting a sample from the pool based on the principle of maximum entropy, delete the number of version space tree getlabel.m: According to the tree and the test sample obtained according to the class standard getTrees.m the tree: from the tree structure (randomly generated), randomly selected a certain number of trees (the leaves of the tree node class marked randomly adding ) RandomCreateTree_d_unbalance: According to the sample point cut point unbalanced cut point construction tree, RandomCreateTree_d_all.m: construction of the tree randomdata.m all sample points cut point: given the value of the property, manufacturing data randomselect.m: random data Select as part showTree.m: tree structure test.m: tree, the test sample is given to get the correct rate)

getting started with storm

音频信号的小波分解与重构实例，在MATLAB里调用sym1小波函数进行三层分解。(audio signal decomposition and reconstruction by means of wavelet )