matlab-tool

利用MATLAB实现简单字符识别的一个例子(The use of MATLAB in the example of a simple character recognition)

基于SVR的非线性系统故障诊断，假设非线性系统在1.4s~1.6s期间发生系统参数变化故障(SVR-based fault diagnosis of nonlinear systems, assuming nonlinear systems in 1.4s ~ 1.6s failure occurred during the parameter variations)

说明：  MATLAB实现股票价格预测 源程序代码(MATLAB source code to achieve stock price prediction)

这是一个matlab编写的程序。实现k均值。实现成功。(it is a matlab programming.)

For quantum well Schrodinger poisson

it is about sammon map in tha clustering.

用matlab中simulink工具箱搭建的非线性模型，功能便于实现！(Using matlab simulink toolbox to build the nonlinear model, features easy to implement!)

PCA(Principal Component Analysis)预处理和最近邻分类程序(the code of Principal Component Analysis)

64个子载波的OFDM系统在多径衰落信道中LS和MMSE信道估计误码率比较，MATLAB程序(64 sub-carrier OFDM system in multipath fading channel LS and MMSE channel estimation error rate more, the MATLAB program)

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.)