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EKM
更新一代的二型模糊降型算法-EKM算法。由KMA算法改进而成，具有更高的计算效率与优化时间(EKM algorithm (enhance Karnik-Mendel Algorithm). With higher computational sufficiency and cost less time in calculating.)
- 2021-01-02 13:48:57下载
- 积分：1
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daobaixitong
倒摆系统演示,倒摆闭环系统在整体上可以达到较为理想的动态性能。(inverted pendulum demonstration, inverted pendulum in the overall closed-loop system can be quite satisfactory dynamic performance.)
- 2007-04-21 15:14:46下载
- 积分：1
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ImprovedSegment
改进的基于区域的图像分割算法，对含有噪声的图像非常适用！在matlab6.5下顺利编译通过
(Improvement on the region's image segmentation algorithm for noisy images very well! In matlab6.5 smoothly through the compiler)
- 2007-04-29 21:46:31下载
- 积分：1
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GRA
本代码实现了灰色关联度分析，仿真了整个分析过程，是一个高效实用的代码值得下载实用。(The source implementation of the Grey Relational Analysis and simulation of the entire analysis process is a practical and efficient code is worth the download utility.)
- 2012-05-31 00:44:25下载
- 积分：1
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mri
it is for music information retrival
- 2015-01-12 15:46:16下载
- 积分：1
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noma
说明： energy efficiency of noma
- 2020-03-07 13:56:24下载
- 积分：1
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matlab_programming_tutorial_explaining_the_functio
matlab程序设计函数讲解教程matlab programming tutorial explaining the function(explain the function matlab programming tutorial matlab programming tutorial explaining the function)
- 2010-08-02 11:26:57下载
- 积分：1
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HilbertTransformer
Hilbert transform in matlab
- 2014-08-20 19:23:26下载
- 积分：1
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NSGA
说明： 多目标遗传算法是NSGA-II[1]（改进的非支配排序算法）,该遗传算法相比于其它的多目标遗传算法有如下优点：传统的非支配排序算法的复杂度为 ，而NSGA-II的复杂度为 ，其中M为目标函数的个数，N为种群中的个体数。引进精英策略，保证某些优良的种群个体在进化过程中不会被丢弃，从而提高了优化结果的精度。采用拥挤度和拥挤度比较算子，不但克服了NSGA中需要人为指定共享参数的缺陷，而且将其作为种群中个体间的比较标准，使得准Pareto域中的个体能均匀地扩展到整个Pareto域，保证了种群的多样性。（消除了共享参数）。(Multi-objective genetic algorithm is nsga-ii [1] (improved non-dominant sorting algorithm), which has the following advantages compared with other multi-objective genetic algorithms: the complexity of the traditional non-dominant sorting algorithm is, while the complexity of nsga-ii is, where M is the number of objective functions and N is the number of individuals in the population.The introduction of elite strategy to ensure that some good individuals in the evolutionary process will not be discarded, thus improving the accuracy of the optimization results.The comparison operator of crowding degree and crowding degree not only overcomes the defect that NSGA needs to specify the Shared parameter artificially, but also takes it as the comparison standard between individuals in the population, so that individuals in the quasi-pareto domain can uniformly expand to the whole Pareto domain, ensuring the diversity of the population.(eliminating Shared parameters).)
- 2020-02-13 19:30:43下载
- 积分：1
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superresolution
说明： 超分辨率程序，用matlab开发,可以直接执行(matlab, super resolution)
- 2010-04-12 18:30:32下载
- 积分：1
