CVX工具下载及测试

（1）下载cvx工具

下载地址：Download CVX | CVX Research, Inc.

我选了这个选项，下载后进行解压。

（2）测试

根据 <压缩感知学习总结及Matlab代码实现_压缩感知代码_WinrenJoe的博客-CSDN博客>的步骤进行测试下载的文件是否有效。

在MATLAB命令行中输入了：

cd C:\personal\cvx
cvx_setup

可是出现报错：错误使用cd 输入参数太多

原因：路径里有文件名中带空格

解决方法：路径用括号括上。
cd('路径'）

以cvx首页的一个例子为例进行测试：

cd('E:\CompressSensing\example\cvx-w64\cvx')
cvx_setup
m = 20; n = 10; p = 4;
A = randn(m,n); b = randn(m,1);
C = randn(p,n); d = randn(p,1); e = rand;
cvx_beginvariable x(n)minimize( norm( A * x - b, 2 ) )subject toC * x == dnorm( x, Inf ) <= e
cvx_end

结果为：

---------------------------------------------------------------------------
CVX: Software for Disciplined Convex Programming (c)2014 CVX Research
Version 2.2, Build 1148 (62bfcca) Tue Jan 28 00:51:35 2020
---------------------------------------------------------------------------
Installation info:
Path: E:\parameter estimation\WHY230309CompressSensing\example\cvx-w64\cvx
MATLAB version: 9.10 (R2021a)
OS: Windows 10 amd64 version 10.0
Java version: 1.8.0_202
Verfying CVX directory contents:
WARNING: The following files/directories are missing:
E:\parameter estimation\WHY230309CompressSensing\example\cvx-w64\cvx\sedumi\.travis.yml
These omissions may prevent CVX from operating properly.
Preferences: none found; defaults loaded.
License host:
Username: WHY
Host ID: 7085c275472f (eth4)
Installed license:
No license installed.
No valid licenses found.
Click here to fill out an academic license request
for the username and first hostid listed above.
---------------------------------------------------------------------------
Setting CVX paths...done.
Saving updated path...done.
Searching for solvers...5 shims found.
2 solvers initialized (* = default):
* SDPT3 4.0 {cvx}\sdpt3
SeDuMi 1.3.4 {cvx}\sedumi
3 solvers skipped:
GLPK
Could not find a GLPK installation.
Gurobi unknown {cvx}\gurobi\w64
No valid Gurobi license was found.
Mosek 9.1.9 {cvx}\mosek\w64
Using MOSEK with CVX requires an academic MOSEK license
or a MOSEK-enabled CVX Professional license.
Saving updated preferences...done.
Testing with a simple model...done!
---------------------------------------------------------------------------
To change the default solver, type "cvx_solver <solver_name>".
To save this change for future sessions, type "cvx_save_prefs".
Please consult the users' guide for more information.
---------------------------------------------------------------------------

Calling SDPT3 4.0: 56 variables, 22 equality constraints
For improved efficiency, SDPT3 is solving the dual problem.
------------------------------------------------------------

num. of constraints = 22
dim. of socp var = 41, num. of socp blk = 11
dim. of linear var = 11
dim. of free var = 4 *** convert ublk to lblk
*******************************************************************
SDPT3: Infeasible path-following algorithms
*******************************************************************
version predcorr gam expon scale_data
NT 1 0.000 1 0
it pstep dstep pinfeas dinfeas gap prim-obj dual-obj cputime
-------------------------------------------------------------------
0|0.000|0.000|1.4e+01|8.9e+00|2.8e+03| 9.935275e+00 0.000000e+00| 0:0:00| chol 1 1
1|0.926|0.488|1.0e+00|4.6e+00|6.6e+02| 1.722089e+01 -4.400342e+00| 0:0:00| chol 1 1
2|1.000|0.966|1.9e-05|1.6e-01|3.8e+01| 1.786365e+01 -3.919783e+00| 0:0:00| chol 1 1
3|0.939|0.902|2.8e-06|1.7e-02|5.8e+00| 1.511488e+00 -3.744599e+00| 0:0:00| chol 1 1
4|0.900|0.340|6.3e-07|1.1e-02|1.4e+00|-2.479326e+00 -3.687956e+00| 0:0:00| chol 1 1
5|1.000|0.617|7.8e-09|4.3e-03|3.5e-01|-3.287179e+00 -3.603414e+00| 0:0:00| chol 1 1
6|0.962|0.953|3.0e-10|2.0e-04|1.4e-02|-3.581614e+00 -3.595187e+00| 0:0:00| chol 1 1
7|0.973|0.981|9.3e-11|4.0e-06|3.8e-04|-3.594213e+00 -3.594581e+00| 0:0:00| chol 1 1
8|0.923|0.840|4.6e-10|1.6e-06|3.7e-05|-3.594520e+00 -3.594552e+00| 0:0:00| chol 1 1
9|1.000|0.977|6.1e-10|1.5e-07|2.0e-06|-3.594545e+00 -3.594546e+00| 0:0:00| chol 1 1
10|0.996|0.980|9.0e-10|7.9e-09|3.9e-08|-3.594546e+00 -3.594546e+00| 0:0:00|
stop: max(relative gap, infeasibilities) < 1.49e-08
-------------------------------------------------------------------
number of iterations = 10
primal objective value = -3.59454603e+00
dual objective value = -3.59454605e+00
gap := trace(XZ) = 3.95e-08
relative gap = 4.82e-09
actual relative gap = 2.79e-09
rel. primal infeas (scaled problem) = 8.96e-10
rel. dual " " " = 7.93e-09
rel. primal infeas (unscaled problem) = 0.00e+00
rel. dual " " " = 0.00e+00
norm(X), norm(y), norm(Z) = 1.5e+00, 3.8e+00, 5.4e+00
norm(A), norm(b), norm(C) = 1.8e+01, 2.0e+00, 5.8e+00
Total CPU time (secs) = 0.20
CPU time per iteration = 0.02
termination code = 0
DIMACS: 9.0e-10 0.0e+00 1.7e-08 0.0e+00 2.8e-09 4.8e-09
-------------------------------------------------------------------

------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): +3.59455

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