viterbichengxu

用matlab语言写的RDA(Regularized descriminant analysis)算法,用于模式分类(Matlab language used to write the RDA (Regularized descriminant analysis) algorithm for pattern classification)

reflect spectral by layer peeling

画函数用的matlab界面源代码 多多指教(Painting function used in the source code matlab interface exhibitions)

利用matlab来实现多线性主成分的算法，具有很强的实用性(Using matlab to implement multi-linear principal component algorithm, has a strong practical)

用matlab实现一个简单的积分求和运算，已成功运行(Using matlab to achieve a simple summation of the integral operator, has successfully run)

以pn码为信源，通过定时同步和载波恢复。在收端得到正确的信息。(Pn in the source code for the letter, through the timing synchronization and carrier recovery. Client in the admission to be correct information.)

this matlab is used widely there

HYCON HY4145 Battery Fuel Gauge Demo For Arduino

here to import the pictures and how to segment the picture. how to add the noise. some screen shots will be added this file.

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)