Asymmetric neural networks with multispin interactions.

A dilute nonsymmetric ferromagnetic neural network with multispin interactions and a version of the Hopfield model with multispin interactions are solved in the limit where the average number of inputs per spin is finite. It is found that in such asymmetric systems the critical exponents of local quantities can take a few different values, instead of just one.