  The Singular Value Decomposition (SVD) of linear functions facilitates the
calculation of their 2-induced norm and row and null spaces, hallmarks of
linear control theory. In this work, we present a function representation that,
similar to SVD, provides an upper bound on the 2-induced norm of bounded-input
bounded-output functions, as well as facilitates the computation of
generalizations of the notions of row and null spaces. Borrowing from the
notion of "lifting" in Koopman operator theory, we construct a
finite-dimensional lifting of inputs that relaxes the unitary property of the
right-most matrix in traditional SVD, $V^*$, to be an injective,
norm-preserving mapping to a slightly higher-dimensional space.
