对ofdm频偏估计算法进行优

说明：  工频信号的离散matlab图形画法,其中包括程序及实验报告.(Discrete-frequency signals in matlab graphics drawing method, including the procedures and experimental report.)

在衰落环镜下的qpskfading仿真程序(In fading loop mirror under the qpskfading simulation program)

Device on off with eyes

两个简单序列的褶积，是地球物理信号处理的简单基本程序(convolution of two alignments)

Chen混沌系统控制仿真 基于自适应控制法的MATLAB仿真实现(The simulation of Chen chaos by the method of adaptive control method)

光伏电池阵列输出功率受光照强度和温度变化的影响，因此最大功率点跟踪（MPPT）技术广泛应用于光伏系统中。在所有最大功率点(MPP)控制策略中，扰动观察（P&O）MPPT算法因易实现被广泛应用，然而它的缺点是在稳定工作状态下工作点通过MPP 时会导致能量振荡损耗，并且在光照强度或温度发生突变时表现较差的动态响应。在本文中，提出一种改进型变步长扰动观察MPPT 算法，此方法依据工作点动态调整步长变化，与传统固定步长方法比较，本文提出的方法能有效地提高MPPT 速度和转换效率，通过仿真和实验结果分析，验证了此改进算法的可行性。(PV array output power by light intensity and temperature changes, so the maximum power point tracking (MPPT) technology is widely used in photovoltaic systems. In all the maximum power point (MPP) control strategy, the perturbation and observation (P & O) MPPT algorithm because easy to implement is widely used, but its disadvantage is the steady-state operating point by the MPP causes energy oscillations loss, and in the light intensity or temperature mutated poor performance dynamic response. In this paper, we propose a modified variable step size perturbation and observation MPPT algorithm, this method is based on dynamically adjusting the operating point changes in steps, with the traditional fixed-step methods, the proposed method can effectively improve the speed and efficiency MPPT, The simulation and experimental results verify the feasibility of this algorithm.)

重要的模拟程序，模拟精度很高，值得大家好好参考，好好学习一下(Important simulation, the simulation accuracy is high, is worth a good reference to learn about)

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)

电力市场中计算直流潮流程序，结合杜松怀版电力市场例题的程序，简单实用(DC load flow calculation in electricity market program, combined with Du Songhuai example electricity market version of the program, simple and practical)

An Introduction to Pattern Recognition: matlab approach