This project allows users to dynamically create and plot polynomial functions of varying degrees with user-defined coefficients and intercepts. The graph shows the polynomial curve along with the ...

Graph polynomials serve as robust algebraic encodings of the intricate combinatorial properties inherent to graphs. At the heart of this discipline lies the Tutte polynomial, an invariant that not ...

Abstract: While frequency-domain algorithms have been demonstrated to be powerful for conventional nonlinear signal processing, there is still not much progress in literature dedicated to nonlinear ...

Department of Mathematics and Statistics, Qinghai Minzu University, Xining, China. Since then, much attention has been paid to this topic, but they mainly focus on undirected graphs and integral trees ...

General graph neural networks (GNNs) implement convolution operations on graphs based on polynomial spectral filters. Existing filters with high-order polynomial approximations can detect more ...

Abstract: Although graph structures have proved useful in high level vision for object recognition and matching, they can prove computationally cumbersome because of the need to establish reliable ...

This project is a Python application that uses a Polynomial Network to analyze and fit a polynomial to a set of data points. The application provides a GUI for users to interact with the data and the ...

ABSTRACT: The matching energy of graph G is defined as , where be the roots of matching polynomial of graph G. In order to compare the energies of a pair of graphs, Gutman and Wager further put ...