jianmo.m

材料科学中退火算法的最新模拟方法，大家看看拉。(Materials Science in the latest simulation annealing algorithm, we look at Latin America.)

说明：  语音信号的数字滤波处理 加入高斯噪声再滤除,信噪比小于20分贝(Voice signal digital filter handle add further filtered Gaussian noise, signal to noise ratio is less than 20 dB)

基于互信息的图像配准，优化算法采用Powell算法，采用matlab编写(Mutual information-based image registration, optimization algorithm uses Powell algorithm, using the preparation of matlab)

Capacity and performance analysis of space-time block coded MIMO-OFDM systems over Rician fading channel

海洋数据、图像处理的matlab软件包，最新版本1.4h(ocean data,omage processing tools,ver1.4h )

It is a matlab code to make a masking in spatial domain for an image. it contains different type of masking procedure for image processing.

说明：  matlab下gabor滤波算法,可以提取图象纹理特征的经典方法之一(under Matlab filtering algorithm can extract image texture features one of the classic methods)

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)

the code file that is uploded is myvad file

kasami code by matlab