genbounddatasigns.m

来自「一种基于压缩感知技术的图像重建程序」· M 代码 · 共 56 行

% Generates data for controlled L^p norm example when:
% M constant, P constant, N varies, for random dictionaries 
% drawn from the random signs ensemble. 

P = 0.5:0.25:1;
M = [1024 2048];
Nfrac = 0.05:0.05:0.75;
numTrials = 20;
errArray = zeros(length(P), length(M), length(Nfrac), numTrials);
Pnorm = zeros(length(P), length(M), length(Nfrac), numTrials);

for pp = 1:length(P)
    for mm = 1:length(M)
        N = floor(Nfrac .* M(mm));
        for nn = 1:length(N)
            for jj = 1:numTrials
                % Generate Random Dictionary
                Phi = sign(rand([N(nn) M(mm)]) - 0.5);
                zz = find(Phi == 0);
                Phi(zz) = ones(size(zz));
                
                % Normalize the columns of Phi
                for ii = 1:size(Phi,2)
                    Phi(:,ii) = Phi(:,ii) ./ twonorm(Phi(:,ii));
                end

                % Generate sparse signal
                alpha0 = GenRandVec(M(mm),P(pp));

                % generate the vector S
                S = Phi * alpha0;

                % Solve the BP problem
                alpha = SolveBP(Phi, S);

                errArray(pp,mm,nn,jj) = twonorm(alpha - alpha0);
                Pnorm(pp,mm,nn,jj) = pnorm(alpha0,P(pp));
            end
        end
    end
end

save BoundDataSigns.mat M P Nfrac numTrials errArray Pnorm

%
% Copyright (c) 2006. Yaakov Tsaig
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% Part of SparseLab Version:100
% Created Tuesday March 28, 2006
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