A neural network classifier for conflicting information environments

We investigate nonconvergence phenomena in the training of neural network classifiers when overlapping patterns exist in the training set. A linear weights piecewise hyperquadratic neural network (LWPQNN) which guarantees convergence is presented. It is shown that this neural-network can easily generate satisfactory decision surfaces in problems which are difficult for nearly all other neural network classifiers