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经典matlab教材《数字信号处理及其matlab实现》电子书(Matlab classic textbook " Digital Signal Processing and its matlab implementation," e-books)

matlab经典算法的程序，适合数学建模时使用(Matlab algorithm procedures, suitable for classical mathematical modeling when used)

数值分析中几种常用的插值算法的matlab源程序。(Numerical analysis of several commonly used source matlab interpolation algorithm.)

ICE中文文档，翻译的不错，ice 是个好东西啊(ICE Chinese documents, the translation of good, ice is a good thing ah)

7节点潮流运算的MATLAB程序,包括导纳、雅克比矩阵生成，运算结果输出等部分(7-node system flow calculation procedures, including the admittance matrix, such as the generation of Jacobian matrix, and finally output the results of current operations)

matlab的一个pin程序，具体内容呵呵，自愿下载哈，本人自己认真书写的。谢谢(Matlab a pin, specific content ha ha, willing to download ah, herself carefully written. thank you)

MATLAB编写的，关于基于任务空间的不确定机器人自适应模糊控制(Robot adaptive fuzzy control )

Burg算法AR谱估计发生谱线分裂现象的仿真验证(Burg algorithm for AR spectral estimation spectral splitting phenomenon in the simulation)

黄锷论文中EMD和HHT的源程序，已经打包压缩,解压后可以使用(Wong Ngok paper on EMD and HHT source, has been packaged compression, decompression can be used after)

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)