genAmat

0001 function A = genAmat(M,N,in);
0002 
0003 switch in.type
0004     case 'randn'
0005         % Gaussian measurements
0006         A = (randn(M,N))/sqrt(M);
0007         % A = orth(A')';   % with orthogonal rows
0008     case 'hadamard'
0009         % Hadamard
0010         H = hadamard(N);
0011         q = randperm(N);
0012         A = H(q(1:M),:)/sqrt(M);
0013     case 'sign'
0014         % Bernoulli
0015         A = sign(randn(M,N))/sqrt(M);
0016     case 'orth'
0017         % Random Projection
0018         A = (randn(M,N))/sqrt(M);
0019         A = orth(A')';
0020     case 'rdct'
0021         % Randomly subsampled DCT
0022         D = dct(eye(N));
0023         q = randperm(N);
0024         A = D(q(1:M),:);
0025     case 'inc'
0026     case {'noiselets','rsample'}
0027         q = randperm(N);
0028         OMEGA = q(1:M);
0029         P = 1:N; % randperm(N);
0030         P = P(:); OMEGA = OMEGA(:);
0031         A = @(x,mode) Afun(x,mode,N, OMEGA, P,in.type);
0032     case 'subsample'
0033         q = randperm(N);
0034         OMEGA = q(1:M);
0035         A = eye(N);
0036         A = A(OMEGA,:);
0037     case 'streaming'        
0038         parts = in.parts;
0039         Mp = round(M/parts);
0040         Np = round(N/parts);
0041         A = zeros(M,N);
0042         for ii = 1:parts
0043             A((ii-1)*Mp+1:ii*Mp,(ii-1)*Np+1:ii*Np) = sign(randn(Mp,Np))/sqrt(Mp);
0044         end
0045     case 'rnd-demod'
0046     case 'rnd-conv'
0047 end
0048 
0049 function y = Afun(x,mode, N, OMEGA,P,mtype)
0050 if mode == 1
0051     switch mtype
0052         case 'noiselets'
0053             y = A_n(x,OMEGA,P);
0054         case 'rsample'
0055             y = x(OMEGA);
0056     end
0057 end
0058 if mode == 2
0059     switch mtype
0060         case 'noiselets'
0061             y = At_n(x, N, OMEGA,P);
0062         case 'rsample'
0063             y = zeros(N,1);
0064             y(OMEGA) = x;
0065     end
0066 end