1 function v=fgradw_general(obj,x,t,u,varargin)
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2 % Calculates: grad_w[f(x,t) + gu(x,t)*u(t) + gw(x,t)*w(t)]
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4 % Syntax: (* = optional)
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6 % grad_w = fgradw_general(model, x, t, u, w*);
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13 % Column vector or scalar containing x
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15 % Scalar containing the time of the operation.
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17 % Column vector or scalar containing deterministic data for this particular step.
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19 % Column vector or scalar containing w(t) for this particular step.
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20 % Redundant argument for this model, because w(t) is elimiated by the differentiation.
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25 % The result of the operation: the gradient with respect to w.
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27 % Toolbox for nonlinear filtering.
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28 % Copyright (C) 2005 Jakob Rosén <jakob.rosen@gmail.com>
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30 % This program is free software; you can redistribute it and/or
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31 % modify it under the terms of the GNU General Public License
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32 % as published by the Free Software Foundation; either version 2
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33 % of the License, or (at your option) any later version.
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35 % This program is distributed in the hope that it will be useful,
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36 % but WITHOUT ANY WARRANTY; without even the implied warranty of
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37 % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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38 % GNU General Public License for more details.
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40 % You should have received a copy of the GNU General Public License
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41 % along with this program; if not, write to the Free Software
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42 % Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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44 % Everything except for gw(x,t) is eliminated by the differentiation.
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45 % Hence, we just need to evaluate gw(x,t)
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46 v=eval(obj.gw,x,t,[],[]);
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