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Neural Network Operator Approach to Fractal Approximation Preserves Smoothness
A new arXiv paper studies fractal interpolation functions built from iterated function systems and combines them with neural network operators. The authors construct alpha-fractal functions and analyze how smoothness is retained alongside convergence guarantees. The work sits at the intersection of approximation theory and neural operator methods.