Single-Sonoluminesce

刘金坤《先进 PID 控制及其 MATLAB 仿真》书上第三章源程序。供大家参考。(Liu Jinkun " Advanced PID Control and MATLAB Simulation" Chapter III of the book source. For your reference.)

Matlab ART algorithm for finding length of beam through each pixel

Van der Pol Oscillator (chaotic map)

说明：  异步电机启动模型，仿真结果表明该模型鲁棒性强，调节时间短。(asymotor_stator.mdl)

　提高电源的动态响应　　非线性和复杂的系统是一个转换器　　电力电子的有趣的挑战。摘要介绍了　　设计和实现数字PID控制器使用　　混沌粒子群优化(复)提振　　转换器,提出了自动调优转换器的方法　　最优启动响应。当系统启动时,处理器　　单元分析了开环启动响应转炉和　　在一些迭代使用复准备最佳反应　　算法。使用逻辑映射混沌映射序列　　增加它的收敛速度和精度。模拟　　和实现结果显示提出的效率　　方法(Improving dynamic response of DC-DC converters which are nonlinear and complicate systems is an interesting challenge in power electronics. This paper presents the design and implementation of digital PID controller using the chaotic particle swarm optimization (CPSO) for a Boost converter and proposes an approach for auto tuning converter optimum startup response. When the system starts, processor unit analyses the open loop startup response of converter and prepares optimum response during some iteration using CPSO algorithm. Chaotic mapping using logistic map sequences increases its convergence rate and resulting precision. Simulation and Implementation results show efficiency of proposed approach)

偏最小二乘法是集主成分分析、典型相关分析和多元线性回归分析3种分析方法的优点于一身(PLS is a principal component analysis, canonical correlation analysis and multiple linear regression analysis three kinds of analysis method has the advantage in a)

FCBF算法是基于显著的思想，采用后向顺序搜索策略快速有效地寻找最优特征子集的特征选择方法，它采用对称不确定性作为相关程度度量标准，每次选择一个显著特征并删除它的所有冗余特征。(The FCBF algorithm is based on the significant idea, using the backward sequential search strategy to find the feature selection method quickly and effectively. It uses the symmetric uncertainty as the correlation measure, and selects a significant feature each time and deletes all the redundant features.)

this code is for frame difference.

实现数字编码的matlab小实验。在matlab上调试通过(Matlab digital encoding small experiments. Debugging through the matlab)

稀疏约束的非负矩阵分解Non-negative Matrix Factorization with Sparseness Constraints(Non-negative Matrix Factorization with Sparseness Constraints)