gcv.rar_GCV正则化参数_正则化 matlab_正则化函数_正则化工具箱_正则参数

function [reg_min,G,reg_param] = gcv(U,s,b,method) %GCV Plot the GCV function and find its minimum. % % [reg_min,G,reg_param] = gcv(U,s,b,method) % [reg_min,G,reg_param] = gcv(U,sm,b,method) , sm = [sigma,mu] % % Plots the GCV-function % || A*x - b ||^2 % G = ------------------- % (trace(I - A*A_I)^2 % as a function of the regularization parameter reg_param. % Here, A_I is a matrix which produces the regularized solution. % % The following methods are allowed: % method = 'Tikh' : Tikhonov regularization (solid line ) % method = 'tsvd' : truncated SVD or GSVD (o markers ) % method = 'dsvd' : damped SVD or GSVD (dotted line) % If method is not specified, 'Tikh' is default. % % If any output arguments are specified, then the minimum of G is % identified and the corresponding reg. parameter reg_min is returned. % Per Christian Hansen, IMM, Dec. 16, 2003. % Reference: G. Wahba, "Spline Models for Observational Data", % SIAM, 1990. % Set defaults. if (nargin==3), method='Tikh'; end % Default method. npoints = 200; % Number of points on the curve. smin_ratio = 16*eps; % Smallest regularization parameter. % Initialization. [m,n] = size(U); [p,ps] = size(s); beta = U'*b; beta2 = norm(b)^2 - norm(beta)^2; if (ps==2) s = s(p:-1:1,1)./s(p:-1:1,2); beta = beta(p:-1:1); end if (nargout > 0), find_min = 1; else find_min = 0; end if (strncmp(method,'Tikh',4) | strncmp(method,'tikh',4)) % Vector of regularization parameters. reg_param = zeros(npoints,1); G = reg_param; s2 = s.^2; reg_param(npoints) = max([s(p),s(1)*smin_ratio]); ratio = (s(1)/reg_param(npoints))^(1/(npoints-1)); for i=npoints-1:-1:1, reg_param(i) = ratio*reg_param(i+1); end % Intrinsic residual. delta0 = 0; if (m > n & beta2 > 0), delta0 = beta2; end % Vector of GCV-function values. for i=1:npoints G(i) = gcvfun(reg_param(i),s2,beta(1:p),delta0,m-n); end % Plot GCV function. % loglog(reg_param,G,'-'), xlabel('\lambda'), ylabel('G(\lambda)') % title('GCV function') % Find minimum, if requested. if (find_min) [minG,minGi] = min(G); % Initial guess. reg_min = fminbnd('gcvfun',... reg_param(min(minGi+1,npoints)),reg_param(max(minGi-1,1)),... optimset('Display','off'),s2,beta(1:p),delta0,m-n); % Minimizer. minG = gcvfun(reg_min,s2,beta(1:p),delta0,m-n); % Minimum of GCV function. % ax = axis; % HoldState = ishold; hold on; % loglog(reg_min,minG,'*r',[reg_min,reg_min],[minG/1000,minG],':r') % title(['GCV function, minimum at \lambda = ',num2str(reg_min)]) % axis(ax) % if (~HoldState), hold off; end end elseif (strncmp(method,'tsvd',4) | strncmp(method,'tgsv',4)) % Vector of GCV-function values. rho2(p-1) = abs(beta(p))^2; if (m > n & beta2 > 0), rho2(p-1) = rho2(p-1) + beta2; end for k=p-2:-1:1, rho2(k) = rho2(k+1) + abs(beta(k+1))^2; end G = zeros(p-1,1); for k=1:p-1 G(k) = rho2(k)/(m - k + (n - p))^2; end reg_param = (1:p-1)'; % Plot GCV function. % semilogy(reg_param,G,'o'), xlabel('k'), ylabel('G(k)') % title('GCV function') % % Find minimum, if requested. if (find_min) [minG,reg_min] = min(G); % ax = axis; % HoldState = ishold; hold on; % semilogy(reg_min,minG,'*r',[reg_min,reg_min],[minG/1000,minG],':r') % title(['GCV function, minimum at k = ',num2str(reg_min)]) % axis(ax); % if (~HoldState), hold off; end end elseif (strncmp(method,'dsvd',4) | strncmp(method,'dgsv',4)) % Vector of regularization parameters. reg_param = zeros(npoints,1); G = reg_param; reg_param(npoints) = max([s(p),s(1)*smin_ratio]); ratio = (s(1)/reg_param(npoints))^(1/(npoints-1)); for i=npoints-1:-1:1, reg_param(i) = ratio*reg_param(i+1); end % Intrinsic residual. delta0 = 0; if (m > n & beta2 > 0), delta0 = beta2; end % Vector of GCV-function values. for i=1:npoints G(i) = gcvfun(reg_param(i),s,beta(1:p),delta0,m-n,1); end % % Plot GCV function. % loglog(reg_param,G,':'), xlabel('\lambda'), ylabel('G(\lambda)') % title('GCV function') % Find minimum, if requested. if (find_min) [minG,minGi] = min(G); % Initial guess. reg_min = fminbnd('gcvfun',... reg_param(min(minGi+1,npoints)),reg_param(max(minGi-1,1)),... optimset('Display','off'),s,beta(1:p),delta0,m-n,1); % Minimizer. minG = gcvfun(reg_min,s,beta(1:p),delta0,m-n,1); % Minimum of GCV function. % ax = axis; % HoldState = ishold; hold on; % loglog(reg_min,minG,'*r',[reg_min,reg_min],[minG/1000,minG],':r') % title(['GCV function, minimum at \lambda = ',num2str(reg_min)]) % axis(ax) % if (~HoldState), hold off; end end elseif (strncmp(method,'mtsv',4) | strncmp(method,'ttls',4)) error('The MTSVD and TTLS methods are not supported') else error('Illegal method') end