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高频地波雷达的仿真程序 可能会有人需要 实用MATLAB(Simulation of High Frequency Ground Wave Radar)

这是一个最基本的OFDM系统仿真，说明一个信号通过OFDM系统所产生信号对比(This is a basic OFDM system simulation, that a signal generated by the signal OFDM system comparison)

PSO基本实现过程的详细演示，适合初学者进一步加深对理论的理解，推荐使用(A detailed presentation of the basic PSO implementation process, suitable for beginners to further deepen the understanding of the theory, recommended the use of)

matlab读取YUV视频数据参考程序，matlab实现(matlab read YUV video data reference program, matlab achieve)

对遗传算法进行分析，介绍，并用多种matlab方法，C语言，c++算法进行仿真(The genetic algorithm is introduced, and a variety of analysis, matlab method, C language, c++ simulation)

蒙特卡洛模拟的例子以及程序 关于结构可靠度分析的 有需要的可以下载看看(Examples and programs of Monte Carlo simulation)

说明：  additive white gaussian noise in matlab

新PROSPECT可模拟多色素信息叶片光谱特征(new PROSPECT can model multiple leaf pigment information spectra)

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)

awgn model channel programme matlab