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来自「斯坦福大学Grant和Boyd教授等开发的凸优化matlab工具箱」· M 代码 · 共 19 行

% Chapter 6: Approximation and fitting
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%  deadzone.m             - Section 6.1.2: Residual minimization with deadzone penalty
%  fig6_15.m              - Figure 6.15: A comparison of stochastic and worst-case robust approximation
%  fig6_19.m              - Figure 6.19: Polynomial fitting
%  convex_interpolation.m - Figure 6.24: Fitting a convex function to given data
%  penalty_comp_cvx.m     - Figure 6.2: Penalty function approximation
%  fig6_9.m               - Figure 6.9: An optimal tradeoff curve
%  tv_cvx.m               - Figures 6.11-6.14: Total variation reconstruction
%  basispursuit.m         - Figures 6.21-6.23: Basis pursuit using Gabor functions
%  smoothrec_cvx.m        - Figures 6.8-6.10: Quadratic smoothing
%  fig6_5.m               - Example 6.2: Robust regression using the Huber penalty
%  fig6_6.m               - Example 6.3: Optimal input design
%  regressor_cvx.m        - Example 6.4: Regressor selection problem
%  wcrobls.m              - Example 6.6: Comparison of worst-case robust, Tikhonov, and nominal least squares
%  fig6_20.m              - Example 6.8: Spline fitting
%  preference_regions.m   - Example 6.9: Bounding consumer preference
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