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首页> 外文期刊>International journal of bifurcation and chaos in applied sciences and engineering >Edge of chaos and local activity domain of fitzhugh-nagumo equation
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Edge of chaos and local activity domain of fitzhugh-nagumo equation

机译:fitzhugh-nagumo方程的混沌边缘和局部活动域

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The local activity theory [Chua, 97] offers a constructive analytical tool for predicting whether a nonlinear system composed of coupled cells, such as reaction-diffusion and lattice dynamical systems, can exhibit complexity. The fundamental result of the local activity theory asserts that a system cannot exhibit emergence and complexity unless its cell are locally active. This paper gives the first in-depth application of this new theory to a specific Cellular Nonlinear Network (CNN) with cells described by the FitzHugh-Nagumo Equation. Explicit inequalities which define uniquely the local activity parameter domain for the FitzHugh-Nagumo Equation are presented. It is shown that when the cell parameters are chosen within a subset of the local activity parameter domain, where at least one of the equilibrium state of the decoupled cells is stable, the probability of the emergence of complex nonhomogenous static as well as dynamic patterns is greatly enhanced regardless of the coupling parameters. This precisely-defined parameter domain is called the "edge of chaos", a terminology previously used loosely in the literature to define a related but much more ambiguous concept. Numerical simulations of the CNN dynamics corresponding to a large variety of cell parameters chosen on, or nearby, the "edge of chaos" confirmed the existence of a wide spectrum of complex behaviors, many of them with computational potentials in image processing and other applications. Several examples are presented to demonstrate the potential of the local activity theory as a novel tool in nonlinear dynamics not only from the perspective of understanding the genesis and emergence of complexity, but also as an efficient tool for choosing cell parameters in such a way that the resulting CNN is endowed with a brain-like information processing capability.
机译:局部活动理论[Chua,97]提供了一个建设性的分析工具,用于预测由耦合单元组成的非线性系统(例如反应扩散和晶格动力学系统)是否可以表现出复杂性。局部活动理论的基本结果认为,除非系统的单元处于局部活动状态,否则它不会表现出出现和复杂性。本文首次将这种新理论深入应用于具有FitzHugh-Nagumo方程描述的单元的特定细胞非线性网络(CNN)。给出了显式不等式,其明确定义了FitzHugh-Nagumo方程的局部活动参数域。结果表明,当在局部活动参数域的子集中选择一个单元参数时,解耦单元的至少一个平衡状态是稳定的,则复杂非均匀静态和动态模式出现的概率为无论耦合参数如何,都大大增强。这个精确定义的参数域称为“混乱边缘”,该术语先前在文献中被宽松地用来定义相关但更为模糊的概念。与在“混沌边缘”上或附近选择的大量细胞参数相对应的CNN动力学数值模拟,证实了存在多种复杂行为,其中许多行为在图像处理和其他应用中具有计算潜力。给出了几个例子,以证明局部活性理论作为非线性动力学的一种新颖工具的潜力,不仅从理解起源和复杂性出现的角度来看,而且还可以作为一种以如下方式选择细胞参数的有效工具:最终的CNN具有类似大脑的信息处理能力。

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