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NSGA2

于 2014-01-24 发布文件大小:98KB

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下载积分: 1 下载次数: 25

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代码说明：

用Matlab实现的NSGA2多目标优化算法的源程序，用户可以根据需要定义相应的参数(Using Matlab multi-objective evolutionary algorithm to achieve the source, the user can define the parameters of the corresponding)

文件列表：

NSGA2
.....\NSGA2
.....\.....\binary_decode.m,614,2011-06-05
.....\.....\binary_mutation.m,520,2011-06-05
.....\.....\blend_crossover.m,1429,2011-06-05
.....\.....\compare_crow_dist.m,927,2011-06-05
.....\.....\compare_rank_crow.m,1189,2011-06-05
.....\.....\compute_obj_error.m,554,2011-06-05
.....\.....\compute_sp.asv,701,2011-10-08
.....\.....\compute_sp.m,681,2011-10-08
.....\.....\constr_computation.m,853,2011-06-05
.....\.....\crossover.m,719,2011-06-05
.....\.....\crowding_distance_assignment.asv,1257,2011-09-24
.....\.....\crowding_distance_assignment.m,1257,2011-06-05
.....\.....\crowding_distance_truncated_assignment.m,784,2011-06-05
.....\.....\crtbase.M,1238,2011-06-05
.....\.....\crtbp.M,2270,2011-06-05
.....\.....\crtrp.M,2171,2011-06-05
.....\.....\decode.m,411,2011-06-05
.....\.....\detail.txt,768940,2011-12-24
.....\.....\display_func.m,4093,2011-06-05
.....\.....\elitism.m,3830,2011-06-05
.....\.....\generate_cites.m,470,2011-06-05
.....\.....\generate_P_pop.m,860,2011-06-05
.....\.....\gray2bin.m,551,2011-06-05
.....\.....\GUI.fig,3473,2011-06-05
.....\.....\GUI.m,22639,2011-06-05
.....\.....\ind_cmp.m,843,2011-10-08
.....\.....\ind_cmp_constr.m,662,2011-06-05
.....\.....\init_P_ranking.m,1473,2011-06-05
.....\.....\linear_crossover.m,761,2011-06-05
.....\.....\main_loop.m,3913,2011-10-08
.....\.....\multipoint_crossover.m,1003,2011-06-05
.....\.....\mutation.m,559,2011-06-05
.....\.....\NSGA_sorting.asv,3403,2011-10-08
.....\.....\NSGA_sorting.m,3485,2011-10-08
.....\.....\obj_computation.m,698,2011-06-05
.....\.....\polynomial_mutation.m,1204,2011-06-05
.....\.....\print_generation.m,1004,2011-06-05
.....\.....\random_mutation.m,950,2011-06-05
.....\.....\result.txt,7733,2011-12-24
.....\.....\simulated_binary_crossover.m,1874,2011-06-05
.....\.....\tournament_selection.m,757,2011-06-05
.....\.....\uniform_crossover.m,463,2011-06-05

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pso
The particle swarm optimization algorithm is very popular this years and widely used in many specilities. Our procedure is hoped to bu useful to you. (The particle swarm optimization algorith m is very popular this years and widely used in ma ny specilities. Our procedure is hoped to use negation ful to you.)

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说明：摘要盲图像恢复的主要困难是信息不足，而为了恢复图像和确定点扩散函数需要适当的先验知识。解决这个问题的法、法以及正则化方法等。但是这些方法的计算量都太大，针对上述方法的不足，文章提出了一种恢复图方法有图像的新算法，它通过恢复残差的最小化和后验概率的最大化来估计参数和恢复图像。其中，巧妙地利用了最陡梯度法和共轭梯度法的迭代求解。对由于运动造成的模糊图像，可以明显地改善图像的质量，实验结果证明，在对模糊操作没有严格限制的情况下，仍可得到较好的恢复图像。(： : 2$*/<$ I?E L691/6@ F9MM9G:0=@ R9=? S092F 91/DE 6EC=76/=972 9C 92C:MM9G9E2= 92M761/=972$I?9C G/00C M76 L67LE6 92G76L7 （） =972 7M/L69769 U27R0EFDE /S7:= =?E 91/DE /2F =?E L792=8CL6E/F M:2G=972 &[ $RE008U27R CL/GE8/F/L=9OE 6ED:0/69</= 1E=?7F /2F 3+ 1E=?7F M76 91/DE 6EC=76/=972 /6E E =E2FEF =7 /FF6ECC =?9C L67S0E1$] 2ER 1E=?7F 9C L67L7CEF =7 6EC= S0:6 91/DE :C92D+5 /2F 5E/C=V:/6EC 1E=?7F$W= :CE 192919<E/G7C= M:2G=972 /2F 1/ 919<E &[ M:2G=972 =7 6EC= =?E 91/DE /2F 9FE2=9M@ =?E L/6/1E=E6C$I?9C 1E=?7F :CE C=EELEC= FECGE2= /2F G72Q:D/=E D6/F9E2= 1E=?7FC =7 192919<E ， G7C= M:2G=972 /2F 1/ 919<E L7C=E69769 L67S/S909=@ =7 91L67OE =?E S0:6 91/DE X?9G? 9C /0C7 =7 91L67OE =?E 91/DE V: =@ 92 C71E FED6EE R9=? 27 C=69G= 0919=/=972$)

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