时空模式识别的仿生网络模型设计

F. Corinto, V. Lanza, M. Gilli
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引用次数: 0

摘要

人们提出了许多数学模型来描述呈现时空模式的系统。其中大多数主要是相位模型,其中每个振荡单元都是用一个单独的相位变量来表征的。众所周知,在适当的假设下,可以通过相位模型研究由弱连接振子组成的网络的全局动力学。特别地,马尔金定理和描述函数技术的联合应用使人们能够获得允许Lur’e表示的弱连接网络的相位偏差方程的解析近似。本文的目的是提供一种方法来识别弱连接振荡系统表现出给定时空模式的条件,并利用结果来设计相应的网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of bio-inspired network models for spatio-temporal pattern identification
Many mathematical models have been proposed to describe systems that present spatio-temporal patterns. Most of them are mainly phase models, where each oscillating cell is characterized in terms of a sole phase variable. It is well known that under suitable assumptions the global dynamics of networks composed by oscillators with weak connections can be investigated through phase models. In particular, the joint application of Malkin's Theorem and the describing function technique allows one to obtain an analytical approximation of the phase deviation equation for weakly connected networks that admit of a Lur'e representation. The aim of this manuscript is to provide a method for identifying the conditions under which weakly connected oscillatory systems exhibit given spatio-temporal patterns and to exploit the results for designing the corresponding networks.
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