Convolution Representation of Traveling Pulses in Reaction-Diffusion Systems

Convolution representation manifests itself as an important tool in the reduction of partial differential equations. In this study, we consider the convolution representation of traveling pulses in reaction-diffusion systems. Under the adiabatic approximation of inhibitor, a two-component reaction-diffusion system is reduced to a one-component reaction-diffusion equation with a convolution term. To find the traveling speed in a reaction-diffusion system with a global coupling term, the stability of the standing pulse and the relation between traveling speed and bifurcation parameter are examined. Additionally, we consider the traveling pulses in the kernel-based Turing model. The stability of the spatially homogeneous state and most unstable wave number are examined. The practical utilities of the convolution representation of reaction-diffusion systems are discussed.

[1]  Masakatsu Watanabe,et al.  Studies of Turing pattern formation in zebrafish skin , 2021, Philosophical Transactions of the Royal Society A.

[2]  Akiko Nakamasu,et al.  Correspondences Between Parameters in a Reaction-Diffusion Model and Connexin Functions During Zebrafish Stripe Formation , 2021, Frontiers in Physics.

[3]  E. S. Selima,et al.  Bubbles interactions in fluidized granular medium for the van der Waals hydrodynamic regime , 2021, The European Physical Journal Plus.

[4]  Qihong Shi,et al.  Periodic traveling waves and asymptotic spreading of a monostable reaction-diffusion equations with nonlocal effects , 2021, Electronic Journal of Differential Equations.

[5]  H. Ishii,et al.  The motion of weakly interacting localized patterns for reaction-diffusion systems with nonlocal effect , 2021, Discrete & Continuous Dynamical Systems - B.

[6]  T. A. Wahid,et al.  Exact solutions of plasma flow on a rigid oscillating plate under the effect of an external non-uniform electric field , 2020 .

[7]  T. A. Wahid,et al.  On Analytical Solution of a Plasma Flow over a Moving Plate under the Effect of an Applied Magnetic Field , 2020, Advances in Mathematical Physics.

[8]  H. Ishii,et al.  Effective nonlocal kernels on Reaction-diffusion networks. , 2020, Journal of theoretical biology.

[9]  Li Chen,et al.  Mathematical models for cell migration: a non-local perspective , 2019, Philosophical Transactions of the Royal Society B.

[10]  Pulin Gong,et al.  Complex Dynamics of Propagating Waves in a Two-Dimensional Neural Field , 2019, Front. Comput. Neurosci..

[11]  Helmut Schmidt,et al.  Action potential propagation and synchronisation in myelinated axons , 2019, bioRxiv.

[12]  Yadan Mao,et al.  Applicable symbolic computations on dynamics of small-amplitude long waves and Davey–Stewartson equations in finite water depth , 2018 .

[13]  Kokichi Sugihara,et al.  A differential equation model of retinal processing for understanding lightness optical illusions , 2018 .

[14]  Hirokazu Ninomiya,et al.  Reaction, diffusion and non-local interaction , 2017, Journal of Mathematical Biology.

[15]  Shigeru Kondo An updated kernel-based Turing model for studying the mechanisms of biological pattern formation. , 2017, Journal of theoretical biology.

[16]  A. M. Abourabia,et al.  Exact traveling wave solutions of the van der Waals normal form for fluidized granular matter , 2015 .

[17]  Eckehard Schöll,et al.  Nonlocal control of pulse propagation in excitable media , 2014, 1404.4289.

[18]  François Charru,et al.  Sand Ripples and Dunes , 2013 .

[19]  Guangying Lv,et al.  Traveling waves of some integral-differential equations arising from neuronal networks with oscillatory kernels☆ , 2010 .

[20]  Shigeru Kondo,et al.  Interactions between zebrafish pigment cells responsible for the generation of Turing patterns , 2009, Proceedings of the National Academy of Sciences.

[21]  H. Byrne,et al.  Mathematical Biology , 2002 .

[22]  L. Solnica-Krezel Pattern Formation in Zebrafish , 2002, Results and Problems in Cell Differentiation.

[23]  Ian Stewart,et al.  Target Patterns and Spirals in Planar Reaction-Diffusion Systems , 2000, J. Nonlinear Sci..

[24]  Masayasu Mimura,et al.  Collision of Travelling Waves in a Reaction-Diffusion System with Global Coupling Effect , 1998, SIAM J. Appl. Math..

[25]  Dan Luss,et al.  Pattern selection in controlled reaction–diffusion systems , 1993 .

[26]  A. Hodgkin,et al.  A quantitative description of membrane current and its application to conduction and excitation in nerve , 1990, Bulletin of mathematical biology.

[27]  Ryo Kobayashi,et al.  Higher-dimensional localized patterns in excitable media , 1989 .

[28]  E. Yanagida Stability of fast travelling pulse solutions of the FitzHugh—Nagumo equations , 1985 .

[29]  David Terman,et al.  Propagation Phenomena in a Bistable Reaction-Diffusion System , 1982 .

[30]  A. M. Turing,et al.  The chemical basis of morphogenesis , 1952, Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences.