Bifurcation study of neuron firing activity of the modified Hindmarsh–Rose model. Issue 3 (April 2016)

• Record Type: Journal Article
• Authors: Wu, Kaijun; Luo, Tianqi; Lu, Huaiwei; Wang, Yang
• Is Part Of: Neural computing & applications. Volume 27:Issue 3(2016)
• Page Start: 739
• Page End: 747
• Publication Date: 2016-04
• Subjects: Neural model -- Modified Hindmarsh–Rose Model -- Bifurcation -- Two-parameter dynamic characteristics; Neural networks (Computer science) -- Periodicals; Neural circuitry -- Periodicals; Artificial intelligence -- Periodicals; Neural Networks (Computer) -- Periodicals; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux nerveux -- Périodiques; Intelligence artificielle -- Périodiques; 006.32
• DOI: 10.1007/s00521-015-1892-1
• Languages: English
• ISSNs: 0941-0643

Abstract

Abstract In this paper, the effects of different parameters on the dynamic behavior of the nonlinear dynamical system are investigated based on modified Hindmarsh–Rose neural nonlinear dynamical system model. We have calculated and analyzed dynamic characteristics of the model under different parameters by using single parameter bifurcation diagram, time response diagram and two parameter bifurcation diagram. The results show that the period-adding bifurcation (with or without chaos), period-doubling bifurcation and intermittent chaos phenomenon (periodic and intermittent chaotic) can be observed more clearly and directly from the two parameter bifurcation diagram, and the optimal parameters matching interval can also be found easily.