  Exact solutions for the learning problem of autoassociative networks with
binary couplings are determined by a new method. The use of a branch-and-bound
algorithm leads to a substantial saving of computational time compared with
complete enumeration. As a result, fully connected networks with up to 40
neurons could be investigated. The network capacity is found to be close to
0.83.
