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 ...

We develop an approach for the optimization of continuous costly functions that uses a space-filling experimental design and local function approximation to reduce the number of function evaluations ...

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 ...

Function approximation is one of the core tasks that are solved using neural networks in the context of many engineering problems. However, good approximation results need good sampling of the data ...

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 ...

Of the many function approximation schemes proposed, emphtile coding strikes an empirically successful balance among representational power, computational cost, and ease of use and has been widely ...