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PSO-GA-TSP-PID

于 2015-01-22 发布 文件大小:169KB
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  压缩包包括5个群智能算法的程序，即PSOGA-PID优化，PSO的多目标perota优化问题，基于TSP-PSO算法，遗传算法求解TSP问题，遗传算法求解TSP问题(Compression package includes five swarm intelligence algorithm procedures, namely PSOGA-PID optimization, PSO perota multi-objective optimization problem, TSP-PSO algorithm based on genetic algorithm for TSP, genetic algorithm for TSP)

文件列表：

PSOGA-PID参数
.............\案例14
.............\......\cell模式下运行结果
.............\......\..................\GA_run.html,3271,2010-08-23


.............\......\..................\PSO.html,11078,2010-08-22



.............\......\源程序
.............\......\......\GA_run.m,477,2010-08-23
.............\......\......\PID_Model.mdl,29558,2010-08-22
.............\......\......\PSO.m,2589,2010-08-23
.............\......\......\PSO_PID.m,174,2010-08-22
.............\......\问题解决思路.pdf,116504,2010-08-23
PSO多目标perota优化问题
.......................\chapter10
.......................\.........\data.mat,422,2010-12-28
.......................\.........\main.m,6048,2010-12-28
基于TSP-PSO算法
...............\chapter15
...............\.........\bayg29.txt,695,2009-06-12
...............\.........\burma14.txt,236,2009-06-12
...............\.........\ch130.txt,4394,2009-06-12
...............\.........\ch150.txt,5098,2009-06-12
...............\.........\dist.m,126,2009-06-12
...............\.........\eil51.txt,444,2009-06-12
...............\.........\fitness.m,419,2010-10-16
...............\.........\gr96.txt,1628,2009-06-12
...............\.........\main.asv,5551,2011-03-19
...............\.........\main.m,5566,2011-03-19
...............\.........\Oliver30.txt,434,2009-06-12
...............\.........\pr226.txt,3459,2009-06-12
...............\.........\pr76.txt,1117,2009-06-12
...............\.........\st70.txt,678,2009-06-12
蚁群-二维路径规划
.................\chapter23
.................\.........\barrier.txt,190,2009-09-04
.................\.........\DijkstraPlan.m,1158,2010-11-17
.................\.........\DijstraPlan.m,0,2010-11-17
.................\.........\lines.txt,122,2009-07-19
.................\.........\main.m,5601,2010-12-29
.................\.........\matrix.txt,989,2009-08-05
遗传算法求解TSP问题
...................\CityPosition1.mat,324,2010-08-02
...................\CityPosition2.mat,447,2010-08-02
...................\CityPosition3.mat,570,2010-08-03
...................\Distanse.m,271,2010-08-05
...................\DrawPath.m,614,2010-08-05
...................\dsxy2figxy.m,960,2010-08-02
...................\Fitness.m,125,2010-08-04
...................\GA_TSP.m,2003,2011-04-03
...................\InitPop.m,238,2010-08-04
...................\Mutate.m,263,2010-08-04
...................\OutputPath.m,158,2010-08-05
...................\PathLength.m,304,2010-08-05
...................\Recombin.m,1403,2010-08-04
...................\Reins.m,296,2011-04-04
...................\Reverse.m,530,2011-04-04
...................\Select.m,233,2011-04-04
...................\Sus.m,455,2011-04-04
...................\test.m,187,2010-08-21

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    毫米波图像存在分辨率低的缺点，该程序在WRLA算法的基础上，进一步采用投影算法，能有效改善毫米波图像的分辨率(Images acquired from Passive Millimeter-Wave (PMMW) radiometer have poor resolution due to limited aperture dimension. Therefore, Super-Resolution Algorithm (SRA) is a key component for PMMW imager. SRA realizes spectrum extrapolation, however, spectrum in-band is deteriorated too. Wiener-Richardson-Lucy Algorithm (WRLA) recovers spectrum in-band by Wiener filter, and extrapolates spectrum out-of-band by Richardson-Lucy Algorithm (RLA). WRLA can avoid spectrum deterioration in passband, but its ability for spectrum extrapolation is limited also. We propose an improved algorithm to solve this problem. This algorithm, which has built constraints according to characteristics of PMMW imaging, uses Projection-Onto-Convex-Sets (POCS) technique to enhance the WRLA s performance, so it is termed as POCS-WRLA.)
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    积分：1
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