I would like to minimize: $$J = \int_{\Omega} \|\nabla u - \nabla g\|^2 + \lambda \|\frac{\partial u}{\partial t} + \nabla u.v||^2 ~\text{dx dy dt}$$ where $u(x,y,t)$ is the unknown function, the integral is over a fixed spatio-temporal domain $\Omega$, $\nabla$ is the spatial gradient, $v(x,y,t)$ is a velocity (vector) field. $g(x,y,t)$ and $v(x,y,t)$ are known. $\lambda$ is a constant.
Computing and cancelling the variation of $J$ using a neighborhood $u+\epsilon h$ of $u$, I obtain:
$$ ``\frac{\partial J}{\partial u}" = \int_{xyt} -\Delta (u-g).h + \lambda (\frac{\partial u}{\partial t} + \nabla u.v)(\frac{\partial h}{\partial t} + \nabla h.v) = 0$$
If only the term $\Delta (u-g).h$ was present, I could directly say that if the integral is zero for all $h$, then $\Delta (u-g)$ is zero locally. I'd obtain the standard Poisson equation.
However, the addition of the other term makes me wonder how I can turn this expression into a local PDE to solve via finite differences. Any idea ?
Thanks!