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PSO

于 2020-12-04 发布 文件大小:5KB
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代码说明:

  根据PSO算法原理,在MATLAB中编程实现基于PSO算法的函数极值寻优算法,程序前面给出了PSO算法参数设置,种群初始化,寻找初始极值,迭代寻优,最后通过算法反复迭代300次,画出每代最优个体适应度值变化曲线,最后通过对比发现说明PSO算法具有较强的函数极值寻有能力,谢谢,希望对大家有帮助。 (According to the principle of PSO algorithm in MATLAB programming function PSO algorithm based on extreme value optimization algorithm, the preceding program gives the PSO algorithm parameter settings, population initialization, looking for initial extreme value, iterative optimization, and finally through the iterative algorithm 300 times draw the best individual fitness value of each generation curve, and finally by comparing the findings indicate that PSO algorithm has strong function extreme ability to find, thank you, we want to help.)

文件列表:

fun.m,241,2010-08-03
main.m,1579,2010-08-05
MexicoHatnew.m,174,2010-08-03
PSO0.m,1802,2010-08-05
PSO1.m,1859,2010-08-05
PSO2.m,1859,2010-08-05
PSO3.m,1878,2010-08-05
PSO4.m,1863,2010-08-05
wchange.m,353,2010-08-05

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    The channel estimation algorithm is based on a subspace approach. The method works only for identifiable STBCs (excluding >=1-rate STBCs). See publication [1] for more detail about the algorithm and the identifiability conditions. The zip file contains three m files. - space_time_coding.m (perform space time coding) - subspace_channel_estimation_STBC.m (channel estimation) - one_shot.m (show an example) To use these files, extract the three files in the same folder. Then, call the script one_shot in the matlab command window. Reference: [1] Ammar, N. Ding, Z. "Blind Channel Identifiability for Generic Linear Space-Time Block Codes" IEEE Transactions on Signal Processing Volume 55, Issue 1, Jan. 2007 Page(s):202 - 217(The channel estimation algorithm is based on a subspace approach. The method works only for identifiable STBCs (excluding >=1-rate STBCs). See publication [1] for more detail about the algorithm and the identifiability conditions. The zip file contains three m files. - space_time_coding.m (perform space time coding) - subspace_channel_estimation_STBC.m (channel estimation) - one_shot.m (show an example) To use these files, extract the three files in the same folder. Then, call the script one_shot in the matlab command window. Reference: [1] Ammar, N. Ding, Z. "Blind Channel Identifiability for Generic Linear Space-Time Block Codes" IEEE Transactions on Signal Processing Volume 55, Issue 1, Jan. 2007 Page(s):202- 217)
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