slmatlabjc

MATLAB gui经典设计方案MATLAB gui classic design(MATLAB gui classic design MATLAB gui classic design)

如何使用遗传算法，里面有ppt教程与案例分析，遗传算法与优化问题(How to Use Genetic Algorithms)

偏振去雾 Yoav Y.Schechner,一直研究偏振去雾算法，典型的代表作，blind haze separation, advanced visiblity improvement based on polarization filtered images，(Polarization defogging Yoav Y.Schechner, has been studying the polarization defogging algorithm, a typical representative, blind haze separation, advanced visiblity improvement based on polarization filtered images,)

说明：  matlab经验模态分解 emd 工具包 包含emd常用函数，可用于机械设备故障诊断(Matlab empirical mode decomposition toolkit can be directly used in mechanical equipment fault diagnosis)

有多普勒频移的海底混响点散射模型（matlab编程）( the seafloor reverberation point scattering model with Doppler frequency shift)

让ARToolKit支持MQO模型的必须头文件，GLMetaseq.h(Let ARToolKit support MQO model must header files, GLMetaseq.h)

遗传算法GA—模拟自然界遗传机制和生物进化论而成的一种并行随机搜索最优化方法。（具有“生存+检测”的迭代过程的搜索算法）基于自然界“优胜劣汰，适者生存”的生物进化原理引入优化参数形成的编码串联群体中，按照所选择的适应度函数并通过遗传中的选择、交叉和变异对个体进行筛选，使适应度值好的个体被保留，适应度差的个体被淘汰，新的群体既继承了上一代的信息，又优于上一代。反复循环，直至满足条件。(GA-A parallel random search optimization method that simulates natural genetic mechanisms and biological evolution. (Search algorithm with "survival + detection" iterative process) Based on the biological evolution principle of "survival of the fittest, survival of the fittest" in the natural world, the coding series formed by optimized parameters is introduced. Individuals are screened according to the selected fitness function and through genetic selection, crossover, and variation, so that individuals with good fitness values are retained, individuals with poor adaptability are eliminated, and new groups inherit the information of the previous generation., Better than the last generation. Repeat until conditions are met.)

使用支持向量机进行特征选择的集成算法模型(Feature selection of support vector machines)

模糊逻辑的几个应用举例。 《matlab辅助模糊系统设计》(Several application examples of fuzzy logic. " Matlab auxiliary fuzzy system design" )

最优化算法，包括各种线性优化和非线性优化问题(Optimization algorithms, including linear optimization and nonlinear optimization problems)