sexy_and_drnd

LTE for UMTS - OFDMA and SC-FDMA Based Radio Access 关于随机接入很好的一本书籍是针对LTE系统的。(LTE for UMTS- OFDMA and SC-FDMA Based Radio Access on the random access good books for a LTE system.)

Frequency-tuned Salient Region Detection这篇论文的matlab代码，已运行通过。(This is the code of the paper“Frequency-tuned Salient Region Detection”，and it has been run successfully.)

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)

Algorithm as described in "CoSaMP: Iterative signal recovery from incomplete and inaccurate samples"

卡尔曼滤波的原理及应用书的破地方，以及书中例子的源代码(The principle of Kalman filtering and the broken place of the application book, as well as the source code of the examples in the book)

迭代法产生蕨类叶子的图像，分形的艺术入门(use the methord to draw a fern.it contains a lot points and very beautiful)

数据统计学习中的knn算法，实现对多组数据的交叉验证(Statistics Learning knn algorithm to achieve the multi-group cross-validation data)

LCL filter Model m file

power_voltmeasure,matlab仿真文件,电力电子、功率电子控制方面很有价值，调试通过(aspects of power_voltmeasure, matlab simulation files, power electronics, power electronics control valuable debugging through)

In computer science, a binary tree is a tree data structure in which each node has at most two children, which are referred to as the left child and the right child. A recursive definition using just set theory notions is that a (non-empty) binary tree is a triple (L, S, R), where L and R are binary trees or the empty set and S is a singleton set.[1] Some authors allow the binary tree to be the empty set as well.