Approximate Limit Sampling Data Using Fuzzy-Tree Model

A linear binary fuzzy tree structure approach, i.e. Fuzzy-Tree model, is proposed for complex nonlinear system modeling. In comparison with some other modeling approaches, such as ANFIS and Neural Network model, the proposed model is of less computation, higher accuracy, especially insensitivity to high dimension. It is proved that for any square integrated continuous function, there always exists a Fuzzy-Tree model to approximate it arbitrarily. Fuzzy-Tree model simulates the layered decision-making and piece-wise linearized processing procedure for solving complex problems. A numerical solution was given to show the approach.