function outsig = sig_bincorrnoise(siglen,coher,varargin)
%SIG_BINCORRNOISE Binaurally correlated noise
% Usage: outsig = sig_bincorrnoise(siglen,coher)
%
% Input parameters:
% siglen : Number of samples of outsig
% coher : Interaural coherence of the produced signal.
%
% Output parameters:
% outsig : nsig x 2 correlated noise signal
%
% SIG_BINCORRNOISE(siglen,coher) will generate a interaurally correlated noise signal
% with coherence coher. The output is a 2 column matrix of length siglen.
%
% SIG_BINCORRNOISE(siglen,coher,...) will pass all additional parameters
% onto the noise function to select between different types of stochastic
% noise.
%
% Url: http://amtoolbox.org/amt-1.4.0/doc/signals/sig_bincorrnoise.php
% #Author: Hagen Wierstorf (2013)
% This file is licensed unter the GNU General Public License (GPL) either
% version 3 of the license, or any later version as published by the Free Software
% Foundation. Details of the GPLv3 can be found in the AMT directory "licences" and
% at <https://www.gnu.org/licenses/gpl-3.0.html>.
% You can redistribute this file and/or modify it under the terms of the GPLv3.
% This file is distributed without any warranty; without even the implied warranty
% of merchantability or fitness for a particular purpose.
% ------ Checking of input parameters ------------------------------------
if nargin<2
error('%s: Too few input parameters.',upper(mfilename));
end;
if ( ~isnumeric(siglen) || ~isscalar(siglen) || siglen<0 )
error('%s: siglen has to be a positive scalar.',upper(mfilename));
end
if ( ~isnumeric(coher) || ~isscalar(coher) || coher<0)
error('%s: coher has to be a positive scalar.',upper(mfilename));
end
% ------ Computation -----------------------------------------------------
% Generate correlation matrix
R = [1 coher; coher 1];
% Eigen decomposition
[V,D] = eig(R);
% Form correlating filter
W = V*sqrt(D);
% Generate uncorrelated noise
n = noise(siglen,2,varargin{:});
% Correlate the noise
outsig = n * W';