1. A computer-implemented process for determining high and low bounds on states of output processing elements (PEs) and any hidden PEs in a continuous-state feedforward neural network additionally having input PEs and that is stored in a computer, wherein said bounds serve as limits on the possible range of each such state, said computer comprising a CPU and an input device coupled to said CPU, said CPU comprising an inference module, said neural network being fed into said CPU via said input device, said process comprising commanding the inference module to execute the steps of: determining upper and lower bounds on states of the input PEs using input variable distribution information that has been fed into said CPU via said input device; in succession, computing the bounds on the states of any hidden PEs from the bounds on the input PEs and the computed bounds on the states of any hidden PEs from hidden layers of PEs closer to the input PEs; and computing the bounds on the states of the output PEs from the bounds on the states of the input PEs and the bounds on the states of any hidden PEs.