  We introduce and study the Split Common Null Point Problem (SCNPP) for
set-valued maximal monotone mappings in Hilbert spaces. This problem
generalizes our Split Variational Inequality Problem (SVIP) [Y. Censor, A.
Gibali and S. Reich, Algorithms for the split variational inequality problem,
Numerical Algorithms 59 (2012), 301--323]. The SCNPP with only two set-valued
mappings entails finding a zero of a maximal monotone mapping in one space, the
image of which under a given bounded linear transformation is a zero of another
maximal monotone mapping. We present four iterative algorithms that solve such
problems in Hilbert spaces, and establish weak convergence for one and strong
convergence for the other three.
