A finite-element program using simplices has been developed to model nonlinear dynamic systems. The program has the fast convergence properties of single-stage neural nets but is also able to adapt its memory usage to match the complexity of the plant being modelled. Efficient algorithms are presented to quantize the input space with respect to the simplex structure. The efficacy of the method is illustrated on two nonlinear dynamic systems.