Period-halving Bifurcation of a Neuronal Recurrence Equation

TL;DR

This paper investigates neuronal recurrence equations, demonstrating exponential convergence times and the occurrence of period-halving bifurcations through a novel construction of equations with specific cycle lengths.

Contribution

It introduces a method to construct neuronal recurrence equations exhibiting exponential convergence and period-halving bifurcations, advancing understanding of their dynamic behavior.

Findings

Exponential convergence times to fixed points.

Existence of period-halving bifurcations.

Construction of equations with prescribed cycle lengths.

Abstract

We study the sequences generated by neuronal recurrence equations of the form $x(n) = {\bf 1}[\sum_{j=1}^{h} a_{j} x(n-j)- \theta]$. From a neuronal recurrence equation of memory size $h$ which describes a cycle of length $\rho(m) \times lcm(p_0, p_1,..., p_{-1+\rho(m)})$, we construct a set of $\rho(m)$ neuronal recurrence equations whose dynamics describe respectively the transient of length $O(\rho(m) \times lcm(p_0, ..., p_{d}))$ and the cycle of length $O(\rho(m) \times lcm(p_{d+1}, ..., p_{-1+\rho(m)}))$ if $0 \leq d \leq -2+\rho(m)$ and 1 if $d=\rho(m)-1$. This result shows the exponential time of the convergence of neuronal recurrence equation to fixed points and the existence of the period-halving bifurcation.