Abstract
In this paper, we introduce a new method for fractal interpolation, herein called Neural Network Algorithm (NNA), which is based on Iterated Functions Systems (IFS); proposed to self-affine signals interpolation with error of expected interpolation. Experiments on theoretical data show
that the proposed interpolation schemes can obtain the expected point value and work with great precision in rebuilding the specified data profile, which leads to a significant advantage over other interpolation methods.