Universal approximation propriety of Flexible Beta Basis Function Neural Tree

In this paper, the universal approximation propriety is proved for the Flexible Beta Basis Function Neural Tree (FBBFNT) model. This model is a tree-encoding method for designing Beta basis function neural network. The performance of FBBFNT is evaluated for benchmark problems drawn from time series approximation area and is compared with other methods in the literature.