Nature

Function Approximation and Sobolev Spaces

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, ...
IEEE

Toward General Function Approximation in Nonstationary Reinforcement Learning

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 ...
IEEE

High-Dimensional Function Approximation With Neural Networks for Large Volumes of Data

Abstract: Approximation of high-dimensional functions is a challenge for neural networks due to the curse of dimensionality. Often the data for which the approximated function is defined resides on a ...
GitHub

function-approximation

Function Approximation and Classification implementations using Neural Network Toolbox in MATLAB. Function Approximation was done on California Housing data-set and Classification was done on SPAM ...
Scientific Research Publishing

Design of Hybrid Fuzzy Neural Network for Function Approximation ()

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 ...
GitHub

function-approximation

This project involves approximating a function to solve an optimization problem. Functions can often be costly to write in code. Approximating a function can sometimes save time and money. Especially ...
Scientific Research Publishing

A Rational Approximation of the Fourier Transform by Integration with Exponential Decay ...

1 Thoth Technology Inc., Algonquin Radio Observatory, Pembroke, ON, Canada. 2 Department of Earth and Space Science and Engineering, York University, Toronto, Canada. 3 Epic College of Technology, ...