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, ...

Matrix functions, such as the exponential, square root and cosine, play an indispensable role in various fields including quantum mechanics, control theory and numerical solution of differential ...

You do not have access to this resource. 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 ...

Mathematics of Computation, Vol. 34, No. 150 (Apr., 1980), pp. 441-463 (23 pages) Constructive proofs and several generalizations of approximation results of J. H. Bramble and S. R. Hilbert are ...

Abstract: The output of an electromagnetic solver is usually the tabulated data of simulated network parameters as a function of frequency. There is a need to convert this data to an equivalent ...

XOR Classification: A feedforward neural network is trained to classify the XOR logic function using a hidden layer with 2 neurons, tanh and sigmoid activation functions, and backpropagation for ...

Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world problems, learning this value ...