UCA

Matlab NLMS program, ready for using

Blind channel estimation equalization adpative CMA method (Blind channel estimation equalization ad CMA method pative)

估算信号时延估算信号延时估算信号时延估算信号延时(delay estimation and estimation delay delay estimation and estimation delay)

说明：  龙格库塔法，包含边值问题的matlab求解程序(Runge Kutta method, a matlab program for solving boundary value problems)

比较生存曲线可以用统计假设测试日志秩检验。它是用来测试的零假设，没有任何区别的人口的生存曲线（即概率事件发生在任何时间点是相同的每个人口）.这个函数使用卡普兰曲线的程序来估计生存函数.(Comparison of two survival curves can be done using a statistical hypothesis test called the log rank test. It is used to test the null hypothesis that there is no difference between the population survival curves (i.e. the probability of an event occurring at any time point is the same for each population). This function use the Kaplan-Meier procedure to estimate the survival function, so it is mandatory to download )

Markov Chain 3,4 states (Simple Markove Chain with 2,3,4 states )

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)

静态电压稳定临界点的使用求解方法，基于主导节点法的分岔类型检验法(Static voltage stability critical point of use solving method, based on the dominant node bifurcation type-test method)

Implemented Gamma correction using matlab

here i have provided a matlab code in which we have the gold price of laast 4 yrs.we have predicted and showed it using a matlab code.