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quad_transform.m
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quad_transform.m
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%UT_TRANSFORM Perform quadratic approximation based transform of a Gaussian rv
%
%
% Syntax:
% [mu,S,C,X,Y,w] = QUAD_TRANSFORM(M,P,g,g_param,tr_param)
%
% In:
% M - Random variable mean (Nx1 column vector)
% P - Random variable covariance (NxN pos.def. matrix)
% g - Transformation function of the form g(x,param) as
% matrix, inline function, function name or function reference
% g_param - Parameters of g (optional, default empty)
% tr_param - Parameters of linearization as a cell array with elements:
% tr_param{1} = derivative function gx of g
% tr_param{2} = 2nd derivative function gxx of g
%
% Out:
% mu - Estimated mean of y
% S - Estimated covariance of y
% C - Estimated cross-covariance of x and y
%
% Description:
% ...
% For default values of parameters, see UT_WEIGHTS.
%
% See also
% UT_WEIGHTS UT_MWEIGHTS UT_SIGMAS
% Copyright (C) 2006 Simo S�rkk�
%
% $Id: ut_transform.m 111 2007-09-04 12:09:23Z ssarkka $
%
% This software is distributed under the GNU General Public
% Licence (version 2 or later); please refer to the file
% Licence.txt, included with the software, for details.
function [mu,S,C] = quad_transform(M,P,g,g_param,tr_param)
if nargin < 4
g_param = [];
end
if nargin < 5
tr_param = [];
end
%
% Apply defaults
%
if isempty(tr_param)
gx = [];
gxx = [];
else
gx = tr_param{1};
if length(tr_param) >= 2
gxx = tr_param{2};
else
gxx = [];
end
end
if isempty(gx)
gx = eye(size(M,1));
end
if isempty(gxx)
gxx = eye(size(M,1));
end
if isnumeric(gx)
% nop
elseif isstr(gx) | strcmp(class(gx),'function_handle')
gx = feval(gx,M,g_param);
else
gx = gx(M,g_param);
end
if isnumeric(gxx)
% nop
elseif isstr(gxx) | strcmp(class(gxx),'function_handle')
gxx = feval(gxx,M,g_param);
else
gxx = gxx(M,g_param);
end
if isempty(g)
mu = g*M;
elseif isnumeric(g)
mu = g;
elseif ischar(g) | strcmp(class(g),'function_handle')
mu = feval(g,M,g_param);
else
mu = g(M,g_param);
end
for i = 1:size(gxx,1)
mu(i) = mu(i) + 0.5*trace(squeeze(gxx(i,:,:))*P);
end
S = gx*P*gx';
for i = 1:size(gxx,1)
gxx_i = squeeze(gxx(i,:,:));
for j = 1:size(gxx,1)
gxx_j = squeeze(gxx(j,:,:));
S(i,j) = S(i,j) + 0.5*trace(gxx_i*P*gxx_j*P);
end
end
C = P*gx';