sober-edge-detection

基于最小二乘辨识的模型参考自适应，含有详细word说明文件(Based on the model reference adaptive least squares identification, documentation contains detailed word)

中科大 Matlab学习入门文档,很详细的资料(USTC Matlab study entry documents, very detailed information)

基于matlab/simulink的电流源型SMES仿真(Based on matlab/simulink simulation of current source type SMES)

详尽介绍了VB和MATLAB混合编程的实现与应用方法(Detailed introduction of the mixed VB and MATLAB programming and application of methods to achieve)

matlab实现基本的通信仿真技术fade(To achieve basic communications simulation technology bpsk using matlab)

三分matlab基础文档，三本比较经典的书籍。中文。侧重点不同。(Matlab third base document, three more classic books. Chinese. Different focus.)

一种基于神经网络模型的matlab实现程序(Based on neural network model matlab implementation procedures)

该源码是用MATLAB语言编写，目的是实现序列特征选却和RBF网络功能(The source code is written in MATLAB, in order to achieve sequence is selected and RBF network function)

说明：  多种实现三组数据集（iris测试数据）分类的算法实现（LMS、MSE、HK等。(several methods(LMS,MSE,HK) to achieve classification of three data set（iris data set).)

针对粒子群优化算法应用于约束优化问题时易陷入局部极小值的问题, 提出了一种改进的粒子群优化算 法. 该算法综合了约束优化问题的目标函数值和约束函数的违反度值作为粒子群优化算法的双适应度值, 采用了 双适应值动态判断粒子群优化算法中粒子的优劣. 违反度值的计算引入了自适应加权系数, 相应地提出了调整各 权系数的自适应策略, 并改进了粒子群优化算法的粒子竞争选择策略, 拓展了粒子群优化算法的单适应值的应用 范围.应用约束自适应粒子群优化算法实现了城市水厂的节能优化调度. 结果表明, 该算法收敛速度快且结果可 靠. 粒子群优化算法为解决工程约束优化问题提供了一条可行途径(Considering that theparticleswarmoptimization( PSO) algorithmcanbeeasily trappedinto the local minimal valueinconstrainedoptimizationproblems, amodifiedconstrainedparticleswarmoptimiza
tionalgorithmwasproposed. Theobjective functionvalue andthe violationvalue of constraint functions wereeffectively combinedto formtwofitnesses, andthefitnesseswereadoptedto estimate if theparticle wassuperior or not ina dynamicway. Theadaptiveweight functionwasadoptedinthe calculationof the violationvalue. The strategy of keeping anadaptive relationof weight coefficientswasproposed, andthe strategyof swarmtournament selectionwasimproved. Theapplicationlocalizationsof thesinglefitnessof PSOwerewidenedaswell. ThemodifiedconstrainedPSOalgorithmwasappliedtosolveenergyoptimiza
tionproblemsof theurbanwater supplyprocess, whichshowedthat theconvergent speedof thealgorithm isfast andthe result isvalid. Afeasibleapproachto solvetheindustrial constraint optimizationproblems withPSOwasprovided.)