Function approximation, a central theme in numerical analysis and applied mathematics, seeks to represent complex functions through simpler or more computationally tractable forms. In this context, ...

At least implicitly, functions are the daily concern of most engineers and scientists. When they are not very smooth, i.e. when they do not have a significant number of derivatives, they can be ...

Abstract: Function approximation has experienced significant success in the field of reinforcement learning (RL). Despite a handful of progress on developing theory for nonstationary RL with function ...

In this paper, a hybrid Fuzzy Neural Network (FNN) system for function approximation is presented. The proposed FNN can handle numeric and fuzzy inputs simultaneously. The numeric inputs are fuzzified ...

One of the issues raised in mathematical and engineering sciences is the ap proximation of a function. Function approximation means that, by having the ability to calculate the value of an unknown ...

Abstract: Nonlinear function approximation plays a critical role in the area efficiency and accuracy of transformer-based hardware accelerators. Functions such as softmax, GELU, SiLU, and layer ...

In this paper, we propose a method for finding the best piecewise linearization of nonlinear functions. For this aim, we try to obtain the best approximation of a nonlinear function as a piecewise ...