Abstract: In this paper, we explore an efficient numerical integration scheme for solving 2D Neural Field Equations(NFEs) in the presence of external stimuli input in both deterministic and stochastic ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

Introduction: Approximate numerical comparison is often influenced by various non-numerical sensory cues, yet whether they act via uniform inhibition (inhibitory control theory) or cue-weighted ...

ABSTRACT: A system of ordinary differential equations (ODEs) is produced by the semi-discretize method of discretizing the advection diffusion equation (ADE). Runge-Kutta methods of the second and ...

Biophysical modeling serves as a valuable tool for understanding brain function by linking neural dynamics at the cellular level with large-scale brain activity. These models are governed by ...

This study presents an (ε, μ)−uniform numerical method for a two-parameter singularly perturbed time-delayed parabolic problems. The proposed approach is based on a fitted operator finite difference ...

Currently supports integration over discrete datasets as well as integration given a reference to a function. The library intends to have similar numerical integration functions to MATLAB. It can be ...

this course is one of the undergraduate courses in Sharif university of technology that is about method of numerical solving methods of differential equation linear and non linear form , numerical ...