Linear and nonlinear models are two types of mathematical functions that can be used to describe the relationships between variables. In this article, you will learn what they are, how they differ ...

For this aim, we try to obtain the best approximation of a nonlinear function as a piecewise linear function. Our method is based on an optimization problem. The optimal solution of this optimization ...

This is a PyTorch implementation of graph-adaptive activation functions for Graph Neural Networks (GNNs). For any questions or suggestions, please e-mail Bianca Iancu at [email protected] or ...

Discover new examples of non-elementary expo-elliptic functions and their applications in second-order nonlinear ODEs and systems of nonlinear ODEs. ... We will study some of the second-order ...

Graph techniques together with the nonharmonic series representation of stationary Gaussian signals can be used in the analysis of a wide class of nonlinear systems. This point is illustrated by the ...

Graph wavelet transforms allow for the effective representation of signals that are defined over irregular domains. The transform coefficients should be sparse, and encode salient features of a signal ...

Learn what linear and nonlinear models are, how they differ, and how they are applied in neural networks with real-world examples. Skip to main content LinkedIn Articles ...

They can then plot this data on a graph and assess whether the function is linear or nonlinear. 3. Modelling: Modelling is an activity that encourages students to create mathematical models that ...