bcs-master

代码说明：

  贝叶斯压缩感知 用于稀疏信号重建，基于贝叶斯理论(Adaptive compressive sensing, Bayesian model selection, compressive sensing (CS), experimental design, relevance vector machine (RVM), sparse Bayesian learning.)

文件列表：

bcs-master, 0 , 2019-03-12
bcs-master\BCS_demo, 0 , 2019-03-12
bcs-master\BCS_demo\approx_results.mat, 60263 , 2019-03-06
bcs-master\BCS_demo\BCS_fast_rvm.m, 5463 , 2016-02-28
bcs-master\BCS_demo\Fig2.m, 2096 , 2016-02-28
bcs-master\BCS_demo\Fig4_ab.m, 1259 , 2016-02-28
bcs-master\BCS_demo\l1qc_logbarrier.m, 3524 , 2018-12-07
bcs-master\BCS_demo\l1qc_newton.m, 4401 , 2018-12-07
bcs-master\BCS_demo\multi_approx_measures.m, 1696 , 2016-02-28
bcs-master\BCS_demo\multi_optimized_measures.m, 1763 , 2016-02-28
bcs-master\BCS_demo\multi_random_measures.m, 1514 , 2016-02-28
bcs-master\BCS_demo\optimized_results.mat, 60238 , 2019-03-06
bcs-master\BCS_demo\random_results.mat, 60084 , 2016-02-28
bcs-master\MT_CS_demo, 0 , 2019-03-12
bcs-master\MT_CS_demo\Fig2.m, 2662 , 2016-02-28
bcs-master\MT_CS_demo\Fig3.m, 1899 , 2016-02-28
bcs-master\MT_CS_demo\mt_CS.m, 6377 , 2016-02-28
bcs-master\MT_CS_demo\multi_results_25.mat, 299828 , 2016-02-28
bcs-master\MT_CS_demo\multi_results_50.mat, 299942 , 2016-02-28
bcs-master\MT_CS_demo\multi_results_75.mat, 300077 , 2016-02-28
bcs-master\MT_CS_demo\multi_runs_25.m, 2569 , 2016-02-28
bcs-master\MT_CS_demo\multi_runs_50.m, 2602 , 2016-02-28
bcs-master\MT_CS_demo\multi_runs_75.m, 2602 , 2016-02-28
bcs-master\README.md, 2413 , 2016-02-28