Abstract: The design of nonlinear smoothing filter based on feedforward neural networks is discussed. The existence of the nonlinear smoothing filter and the composition of filter error variance are analyzed theoretically. The target function for training networks is given, then a new suboptimal algorithm for training networks is proposed, which has good noise suppression capability. Its reliability and advantage are illustrated through an example.