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FISTA-master

于 2020-05-08 发布
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代码说明：

说明：  基于FISTA算法的代码和模拟实例，其中包括迭代算法和仿真过程。(Code and simulation example based on fista algorithm)

文件列表：

FISTA-master, 0 , 2017-11-08
FISTA-master\.DS_Store, 8196 , 2017-11-08
FISTA-master\README.md, 13712 , 2017-11-08
FISTA-master\demo, 0 , 2017-11-08
FISTA-master\demo\fista_general.m, 802 , 2017-11-08
FISTA-master\demo_enet.m, 1311 , 2017-11-08
FISTA-master\demo_full.m, 5142 , 2017-11-08
FISTA-master\demo_lasso.m, 1231 , 2017-11-08
FISTA-master\demo_lasso_weighted.m, 1291 , 2017-11-08
FISTA-master\demo_row_sparsity.m, 615 , 2017-11-08
FISTA-master\figs, 0 , 2017-11-08
FISTA-master\figs\FISTA_L.png, 54185 , 2017-11-08
FISTA-master\figs\FISTA_noL.png, 74078 , 2017-11-08
FISTA-master\figs\ply.png, 8081 , 2017-11-08
FISTA-master\figs\qlxy.png, 6381 , 2017-11-08
FISTA-master\fista_backtracking.m, 4944 , 2017-11-08
FISTA-master\fista_enet.m, 1076 , 2017-11-08
FISTA-master\fista_enet_backtracking.m, 1207 , 2017-11-08
FISTA-master\fista_general.m, 3730 , 2017-11-08
FISTA-master\fista_lasso.m, 1097 , 2017-11-08
FISTA-master\fista_lasso_backtracking.m, 1419 , 2017-11-08
FISTA-master\fista_row_sparsity.m, 1128 , 2017-11-08
FISTA-master\latex, 0 , 2017-11-08
FISTA-master\latex\definitions.tex, 11636 , 2017-11-08
FISTA-master\latex\done, 2938 , 2017-11-08
FISTA-master\latex\fista1.aux, 8 , 2017-11-08
FISTA-master\latex\fista1.fdb_latexmk, 26012 , 2017-11-08
FISTA-master\latex\fista1.fls, 24729 , 2017-11-08
FISTA-master\latex\fista1.log, 29830 , 2017-11-08
FISTA-master\latex\fista1.pdf, 34425 , 2017-11-08
FISTA-master\latex\fista1.png, 5534 , 2017-11-08
FISTA-master\latex\fista1.synctex.gz, 2613 , 2017-11-08
FISTA-master\latex\fista1.tex, 267 , 2017-11-08
FISTA-master\latex\fista_elastic.aux, 8 , 2017-11-08
FISTA-master\latex\fista_elastic.fdb_latexmk, 27181 , 2017-11-08
FISTA-master\latex\fista_elastic.fls, 25823 , 2017-11-08
FISTA-master\latex\fista_elastic.log, 31644 , 2017-11-08
FISTA-master\latex\fista_elastic.pdf, 56633 , 2017-11-08
FISTA-master\latex\fista_elastic.png, 8766 , 2017-11-08
FISTA-master\latex\fista_elastic.synctex.gz, 3053 , 2017-11-08
FISTA-master\latex\fista_elastic.tex, 358 , 2017-11-08
FISTA-master\latex\fista_elastic2.aux, 8 , 2017-11-08
FISTA-master\latex\fista_elastic2.fdb_latexmk, 27192 , 2017-11-08
FISTA-master\latex\fista_elastic2.fls, 25830 , 2017-11-08
FISTA-master\latex\fista_elastic2.log, 31650 , 2017-11-08
FISTA-master\latex\fista_elastic2.pdf, 57219 , 2017-11-08
FISTA-master\latex\fista_elastic2.png, 9548 , 2017-11-08
FISTA-master\latex\fista_elastic2.synctex.gz, 3078 , 2017-11-08
FISTA-master\latex\fista_elastic2.tex, 363 , 2017-11-08
FISTA-master\latex\fista_lasso1.aux, 8 , 2017-11-08
FISTA-master\latex\fista_lasso1.fdb_latexmk, 27170 , 2017-11-08
FISTA-master\latex\fista_lasso1.fls, 25816 , 2017-11-08
FISTA-master\latex\fista_lasso1.log, 31638 , 2017-11-08
FISTA-master\latex\fista_lasso1.pdf, 56581 , 2017-11-08
FISTA-master\latex\fista_lasso1.png, 7261 , 2017-11-08
FISTA-master\latex\fista_lasso1.synctex.gz, 2874 , 2017-11-08
FISTA-master\latex\fista_lasso1.tex, 325 , 2017-11-08
FISTA-master\latex\fista_lasso2.aux, 8 , 2017-11-08
FISTA-master\latex\fista_lasso2.fdb_latexmk, 27041 , 2017-11-08
FISTA-master\latex\fista_lasso2.fls, 25738 , 2017-11-08
FISTA-master\latex\fista_lasso2.log, 31564 , 2017-11-08
FISTA-master\latex\fista_lasso2.pdf, 52514 , 2017-11-08
FISTA-master\latex\fista_lasso2.png, 11595 , 2017-11-08
FISTA-master\latex\fista_lasso2.synctex.gz, 3038 , 2017-11-08
FISTA-master\latex\fista_lasso2.tex, 377 , 2017-11-08
FISTA-master\latex\fista_row_sparsity0.aux, 8 , 2017-11-08
FISTA-master\latex\fista_row_sparsity0.fdb_latexmk, 27376 , 2017-11-08
FISTA-master\latex\fista_row_sparsity0.fls, 25943 , 2017-11-08
FISTA-master\latex\fista_row_sparsity0.log, 31754 , 2017-11-08
FISTA-master\latex\fista_row_sparsity0.pdf, 65074 , 2017-11-08
FISTA-master\latex\fista_row_sparsity0.png, 9526 , 2017-11-08
FISTA-master\latex\fista_row_sparsity0.synctex.gz, 3063 , 2017-11-08
FISTA-master\latex\fista_row_sparsity0.tex, 338 , 2017-11-08
FISTA-master\latex\fista_row_sparsity1.aux, 8 , 2017-11-08
FISTA-master\latex\fista_row_sparsity1.fdb_latexmk, 26606 , 2017-11-08
FISTA-master\latex\fista_row_sparsity1.fls, 25479 , 2017-11-08
FISTA-master\latex\fista_row_sparsity1.log, 31314 , 2017-11-08
FISTA-master\latex\fista_row_sparsity1.pdf, 15781 , 2017-11-08
FISTA-master\latex\fista_row_sparsity1.png, 3103 , 2017-11-08
FISTA-master\latex\fista_row_sparsity1.synctex.gz, 2481 , 2017-11-08
FISTA-master\latex\fista_row_sparsity1.tex, 256 , 2017-11-08
FISTA-master\latex\fista_row_sparsity2.aux, 8 , 2017-11-08
FISTA-master\latex\fista_row_sparsity2.fdb_latexmk, 26478 , 2017-11-08
FISTA-master\latex\fista_row_sparsity2.fls, 25402 , 2017-11-08
FISTA-master\latex\fista_row_sparsity2.log, 31240 , 2017-11-08
FISTA-master\latex\fista_row_sparsity2.pdf, 8460 , 2017-11-08
FISTA-master\latex\fista_row_sparsity2.png, 2938 , 2017-11-08
FISTA-master\latex\fista_row_sparsity2.synctex.gz, 2449 , 2017-11-08
FISTA-master\latex\fista_row_sparsity2.tex, 254 , 2017-11-08
FISTA-master\proj, 0 , 2017-11-08
FISTA-master\proj\proj_l1.m, 1643 , 2017-11-08
FISTA-master\proj\proj_l12.m, 610 , 2017-11-08
FISTA-master\proj\proj_l2.m, 920 , 2017-11-08
FISTA-master\spams, 0 , 2017-11-08
FISTA-master\spams\.DS_Store, 6148 , 2017-11-08
FISTA-master\spams\HOW_TO_INSTALL.txt, 2353 , 2017-11-08
FISTA-master\spams\HOW_TO_USE.txt, 1095 , 2017-11-08
FISTA-master\spams\README, 2468 , 2017-11-08
FISTA-master\spams\build, 0 , 2017-11-08
FISTA-master\spams\build\README, 39 , 2017-11-08

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发表评论

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  • BEMDfenjie
    这个是EMD分解算法,相对比较简单,十分适合初学者,我开始也是从个程序入手的,觉得十分不错,与大家共享.(This is the EMD decomposition algorithm is relatively simple and very suitable for beginners, I started a program from the start, and feel very good to share with you.)
    2009-05-26 15:13:09下载
    积分：1
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    2014-12-05 21:25:44下载
    积分：1
  • y
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    2010-01-21 14:19:41下载
    积分：1
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    2020-10-30 10:39:55下载
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    2011-05-24 05:43:30下载
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    说明：  svdd分类 用matlab实现的svdd算法 挺好用的(Svdd classification svdd algorithm implemented with matlab is very easy to use)
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    针对粒子群优化算法应用于约束优化问题时易陷入局部极小值的问题, 提出了一种改进的粒子群优化算 法. 该算法综合了约束优化问题的目标函数值和约束函数的违反度值作为粒子群优化算法的双适应度值, 采用了 双适应值动态判断粒子群优化算法中粒子的优劣. 违反度值的计算引入了自适应加权系数, 相应地提出了调整各 权系数的自适应策略, 并改进了粒子群优化算法的粒子竞争选择策略, 拓展了粒子群优化算法的单适应值的应用 范围.应用约束自适应粒子群优化算法实现了城市水厂的节能优化调度. 结果表明, 该算法收敛速度快且结果可 靠. 粒子群优化算法为解决工程约束优化问题提供了一条可行途径(Considering that theparticleswarmoptimization( PSO) algorithmcanbeeasily trappedinto the local minimal valueinconstrainedoptimizationproblems, amodifiedconstrainedparticleswarmoptimiza tionalgorithmwasproposed. Theobjective functionvalue andthe violationvalue of constraint functions wereeffectively combinedto formtwofitnesses, andthefitnesseswereadoptedto estimate if theparticle wassuperior or not ina dynamicway. Theadaptiveweight functionwasadoptedinthe calculationof the violationvalue. The strategy of keeping anadaptive relationof weight coefficientswasproposed, andthe strategyof swarmtournament selectionwasimproved. Theapplicationlocalizationsof thesinglefitnessof PSOwerewidenedaswell. ThemodifiedconstrainedPSOalgorithmwasappliedtosolveenergyoptimiza tionproblemsof theurbanwater supplyprocess, whichshowedthat theconvergent speedof thealgorithm isfast andthe result isvalid. Afeasibleapproachto solvetheindustrial constraint optimizationproblems withPSOwasprovided.)
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