A neuron inspired model for the time constant of dynamical systems

TL;DR

This paper introduces a neuron-inspired mathematical model for the time constant of dynamical systems, allowing for response morphology adjustments through parameter tuning.

Contribution

It presents a novel analytical continuous function model inspired by ionic channel gating mechanisms for dynamical system time constants.

Findings

Model can be tuned to modify response morphology

Analytical continuous function provides a new approach

Evidence supports adjustable response characteristics

Abstract

Emulate the gating mechanism of ionic channels in neurons, we present a mathematical model for the time constant of dynamical systems. Our model is an analytical continues function. The analyses give evidence that one can adjust the desirable morphology of the response of the dynamical system by adjusting the parameters of the proposed model.