  In this paper, we establish a neural network to approximate functionals,
which are maps from infinite dimensional spaces to finite dimensional spaces.
The approximation error of the neural network is $O(1/\sqrt{m})$ where $m$ is
the size of networks, which overcomes the curse of dimensionality. The key idea
of the approximation is to define a Barron spectral space of functionals.
