--- /dev/null
+function [IR, CC, D] = adim(U, UC, IR, CC, arg5);
+% ADIM adaptive information matrix. Estimates the inverse
+% correlation matrix in an adaptive way.
+%
+% [IR, CC] = adim(U, UC [, IR0 [, CC0]]);
+% U input data
+% UC update coefficient 0 < UC << 1
+% IR0 initial information matrix
+% CC0 initial correlation matrix
+% IR information matrix (inverse correlation matrix)
+% CC correlation matrix
+%
+% The algorithm uses the Matrix Inversion Lemma, also known as
+% "Woodbury's identity", to obtain a recursive algorithm.
+% IR*CC - UC*I should be approx. zero.
+%
+% Reference(s):
+% [1] S. Haykin. Adaptive Filter Theory, Prentice Hall, Upper Saddle River, NJ, USA
+% pp. 565-567, Equ. (13.16), 1996.
+
+
+% $Id: adim.m 5090 2008-06-05 08:12:04Z schloegl $
+% Copyright (C) 1998-2003 by Alois Schloegl <a.schloegl@ieee.org>
+%
+% This program is free software: you can redistribute it and/or modify
+% it under the terms of the GNU General Public License as published by
+% the Free Software Foundation, either version 3 of the License, or
+% (at your option) any later version.
+%
+% This program is distributed in the hope that it will be useful,
+% but WITHOUT ANY WARRANTY; without even the implied warranty of
+% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+% GNU General Public License for more details.
+%
+% You should have received a copy of the GNU General Public License
+% along with this program. If not, see <http://www.gnu.org/licenses/>.
+
+
+
+[ur,p] = size(U);
+
+Mode_E = 1;
+%if nargin < 4,
+% m = zeros(size(U)+[0,Mode_E]);
+%end;
+
+if nargin<2,
+ fprintf(2,'Error ADIM: missing update coefficient\n');
+ return;
+else
+ if ~((UC > 0) & (UC <1)),
+ fprintf(2,'Error ADIM: update coefficient not within range [0,1]\n');
+ return;
+ end;
+ if UC > 1/p,
+ fprintf(2,'Warning ADIM: update coefficient should be smaller than 1/number_of_dimensions\n');
+ end;
+end;
+
+if nargin<3,
+ IR = [];
+end;
+if nargin<4,
+ CC = [];
+end;
+if nargin<5,
+ arg5 = 6;
+end;
+if isempty(IR),
+ IR = eye(p+Mode_E);
+end;
+if isempty(CC),
+ CC = eye(p+Mode_E);
+end;
+
+D = zeros(ur,(p+Mode_E)^2);
+%D = zeros(ur,1);
+W = eye(p+Mode_E)*UC/(p+Mode_E);
+W2 = eye(p+Mode_E)*UC*UC/(p+Mode_E);
+
+for k = 1:ur,
+ if ~Mode_E,
+ % w/o mean term
+ d = U(k,:);
+ else
+ % w/ mean term
+ d = [1,U(k,:)];
+ end;
+
+ if ~any(isnan(d)),
+ CC = (1-UC)*CC + UC*(d'*d);
+
+ %K = (1+UC)*IR*d'/(1+(1+UC)*d*IR*d');
+ v = IR*d';
+ %K = v/(1-UC+d*v);
+
+ if arg5==0; % original version according to [1], can become unstable
+ IR = (1+UC)*IR - (1+UC)/(1-UC+d*v)*v*v';
+
+ elseif arg5==1; % this provides IR*CC == I, this seems to be stable
+ IR = IR - (1+UC)/(1-UC+d*v)*v*v' + sum(diag(IR))*W;
+
+ elseif arg5==6; % DEFAULT:
+ IR = ((1+UC)/2)*(IR+IR') - ((1+UC)/(1-UC+d*v))*v*v';
+
+ % more variants just for testing, do not use them.
+ elseif arg5==2;
+ IR = IR - (1+UC)/(1-UC+d*v)*v*v' + sum(diag(IR))*W2;
+
+ elseif arg5==3;
+ IR = IR - (1+UC)/(1-UC+d*v)*v*v' + eps*eye(p+Mode_E);
+
+ elseif arg5==4;
+ IR = (1+UC)*IR - (1+UC)/(1-UC+d*v)*v*v' + eps*eye(p+Mode_E);
+
+ elseif arg5==5;
+ IR = IR - (1+UC)/(1-UC+d*v)*v*v' + eps*eye(p+Mode_E);
+
+ end;
+ end;
+
+ %D(k) = det(IR);
+ D(k,:) = IR(:)';
+end;
+
+IR = IR / UC;
+if Mode_E,
+ IR(1,1) = IR(1,1) - 1;
+end;
+
+