文件名称:cvx-w32
介绍说明－－下载内容均来自于网络，请自行研究使用
CVX-一款在matlab中，用于解决计算包括凸优化等问题，支持线性优化和二次方优化以及半正定算法。-CVX is a modeling system for constructing and solving disciplined convex programs (DCPs). CVX supports
a number of standard problem types, including linear and quadratic programs (LPs/QPs), second-order
cone programs (SOCPs), and semidefinite programs (SDPs).
a number of standard problem types, including linear and quadratic programs (LPs/QPs), second-order
cone programs (SOCPs), and semidefinite programs (SDPs).
(系统自动生成,下载前可以参看下载内容)
下载文件列表
cvx
...\structures
...\..........\cvx_s_symmetric.m
...\..........\cvx_s_sparse.m
...\..........\cvx_s_complex.m
...\..........\cvx_s_upper_hankel.m
...\..........\cvx_create_structure.m
...\..........\cvx_s_skew_symmetric.m
...\..........\cvx_s_lower_hessenberg.m
...\..........\cvx_replicate_structure.m
...\..........\cvx_s_banded.m
...\..........\cvx_s_upper_hessenberg.m
...\..........\cvx_s_symmetric_ut.m
...\..........\cvx_s_lower_triangular.m
...\..........\cvx_s_lower_bidiagonal.m
...\..........\Contents.m
...\..........\@cvx
...\..........\....\structures.m
...\..........\cvx_s_hankel.m
...\..........\cvx_s_diagonal.m
...\..........\cvx_s_tridiagonal.m
...\..........\cvx_s_upper_bidiagonal.m
...\..........\cvx_s_hermitian.m
...\..........\cvx_orthog_structure.m
...\..........\cvx_invert_structure.m
...\..........\cvx_s_scaled_identity.m
...\..........\cvx_s_upper_triangular.m
...\..........\cvx_s_toeplitz.m
...\cvx_version.m
...\keywords
...\........\hypograph.m
...\........\integer.m
...\........\minimize.m
...\........\subject.m
...\........\In.m
...\........\variables.m
...\........\expressions.m
...\........\minimise.m
...\........\Contents.m
...\........\dual.m
...\........\maximise.m
...\........\variable.m
...\........\maximize.m
...\........\binary.m
...\........\expression.m
...\........\epigraph.m
...\cvx_startup.m
...\cvx_license.p
...\sets
...\....\complex_lorentz.m
...\....\semidefinite.m
...\....\nonneg_poly_coeffs.m
...\....\geo_mean_cone.m
...\....\simplex.m
...\....\hermitian_semidefinite.m
...\....\nonnegative.m
...\....\Contents.m
...\....\rotated_lorentz.m
...\....\exponential.m
...\....\rotated_complex_lorentz.m
...\....\convex_poly_coeffs.m
...\....\lorentz.m
...\....\norm_ball.m
...\gurobi
...\......\w32
...\......\...\gurobi.mexw32
...\......\...\gurobi56.dll
...\......\...\grbgetkey.exe
...\......\EULA.pdf
...\shims
...\.....\cvx_sdpt3.m
...\.....\cvx_sedumi.m
...\.....\cvx_mosek.p
...\.....\cvx_gurobi.p
...\examples
...\........\min_phase_spectral_fact.m
...\........\examples.css
...\........\bullet.gif
...\........\simple_LS.m
...\........\sparse_heuristics
...\........\.................\sparse_solution.m
...\........\.................\sparse_infeas_dual.m
...\........\.................\html
...\........\.................\....\sparse_infeas.html
...\........\.................\....\sparse_solution.html
...\........\.................\....\sparse_infeas_dual.html
...\........\.................\....\sparse_solution__01.png
...\........\.................\Contents.m
...\........\.................\sparse_infeas.m
...\........\regularized_norm_tradeoff.m
...\........\quickstart.m
...\........\simple_LP.m
...\........\html
...\........\....\min_phase_spectral_fact.html
...\........\....\quickstart.html
...\........\....\closest_toeplitz_psd.html
...\........\....\regularized_norm_tradeoff__02.png
...\........\....\simple_LP.html
...\........\....\equality_constr_norm_min.html
...\........\....\regularized_norm_tradeoff__01.png