bidiag

(PublicToolbox/regutools/bidiag.m in BrainStorm 2.0 (Alpha))

Function Synopsis

[U,B_n,V] = bidiag(A)

Help Text

BIDIAG Bidiagonalization of an m-times-n matrix with m >= n.

 B_n = bidiag(A)
 [U,B_n,V] = bidiag(A)
 
 Computes the bidiagonalization of the m-times-n matrix A
 with m >= n:
     A = U*B*V' ,
 where B is an upper bidiagonal n-times-n matrix, and U and
 V have orthogonal columns.

 The matrix B is stored in compact form in B_n as follows:
         [b_11 b_12            ]         [b_11    b_12]
     B = [     b_22 b_23       ]   B_n = [b_22    b_23] .
         [            .    .   ]         [ .       .  ] 
         [                b_nn ]         [b_nn    NaN ]
 The NaN in B_n(n,2) is used to distinguish a "compact" upper
 bidiagonal matrix from a "compact" lower bidiagonal one.

Cross-Reference Information

app_hh                             C:\BrainStorm_2001\PublicToolbox\regutools\app_hh.m
gen_hh                             C:\BrainStorm_2001\PublicToolbox\regutools\gen_hh.m

Listing of function C:\BrainStorm_2001\PublicToolbox\regutools\bidiag.m

function [U,B_n,V] = bidiag(A)
%BIDIAG Bidiagonalization of an m-times-n matrix with m >= n.
%
% B_n = bidiag(A)
% [U,B_n,V] = bidiag(A)
% 
% Computes the bidiagonalization of the m-times-n matrix A
% with m >= n:
%     A = U*B*V' ,
% where B is an upper bidiagonal n-times-n matrix, and U and
% V have orthogonal columns.
%
% The matrix B is stored in compact form in B_n as follows:
%         [b_11 b_12            ]         [b_11    b_12]
%     B = [     b_22 b_23       ]   B_n = [b_22    b_23] .
%         [            .    .   ]         [ .       .  ] 
%         [                b_nn ]         [b_nn    NaN ]
% The NaN in B_n(n,2) is used to distinguish a "compact" upper
% bidiagonal matrix from a "compact" lower bidiagonal one.

% Reference: L. Elden, "Algorithms for regularization of ill-
% conditioned least-squares problems", BIT 17 (1977), 134-145.

% Per Christian Hansen, UNI-C, 03/11/92.

% Initialization.
[m,n] = size(A);
if (m<n), error('Illegal dimensions of A'), end
B_n = zeros(n,2);
if (nargout> 1), U = [eye(n);zeros(m-n,n)]; betaU = zeros(n,1); end
if (nargout==3), V = eye(n); betaV = zeros(n,1); end

% Bidiagonalization; save Householder quantities.
if (m > n), k_last = n; else k_last = n-1; end
for k=1:k_last

  [B_n(k,1),beta,A(k:m,k)] = gen_hh(A(k:m,k));
  if (k < n), A(k:m,k+1:n) = app_hh(A(k:m,k+1:n),beta,A(k:m,k)); end
  if (nargout>1), betaU(k) = beta; end

  if (k < n-1)
    [B_n(k,2),beta,v] = gen_hh(A(k,k+1:n)'); A(k,k+1:n) = v';
    A(k+1:m,k+1:n) = app_hh(A(k+1:m,k+1:n)',beta,A(k,k+1:n)')';
    if (nargout==3), betaV(k) = beta;, end
  elseif (k == n-1)
    B_n(n-1,2) = A(n-1,n);
  end

end

% Save bottom element if A is square.
if (k_last < n), B_n(n,1) = A(n,n); end

% Put a NaN in bottom element of B_n.
B_n(n,2) = NaN;

% Compute U if wanted.
if (nargout>1)
  for k=k_last:-1:1
    U(k:m,k:n) = app_hh(U(k:m,k:n),betaU(k),A(k:m,k));
  end
end

% Compute V if wanted.
if (nargout==3)
  for k=n-2:-1:1
    V(k+1:n,k:n) = app_hh(V(k+1:n,k:n),betaV(k),A(k,k+1:n)');
  end
end

if (nargout==1), U = B_n; end