Modeling and Data Analysis for Complex Systems and Dynamics
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Organizer(s): |
Name:
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Affiliation:
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Country:
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Pengcheng Xiao
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Kennesaw State University
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USA
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Jianzhong Su
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The University of Texas at Arlington
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USA
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Lixia Duan
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North China University of Technology
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Peoples Rep of China
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Introduction:
| | Many dynamical systems, as examples from small scale neuronal systems and genomic systems in human, to large scale ecosystems of earth that impact climate change, are featured by nonlinear and complex patterns in spatial and temporal dimensions. These phenomena that are represented by massive amount of data, carry significant information and regulate down-stream dynamics. Understanding the mechanisms underlying such events by quantitative modeling represents a mathematical challenge of current interest. Yet all these systems share the similar dynamical system issues in ordinary/partial different equation such as bifurcation, stability, oscillations, stochastic noise as well as issues in determining hidden model parameters from experimental data sets and computational errors of the models. This special session offers a forum to exchange the state of the art theoretical advances related to this promising area as well as computational tools. It will foster and encourage communication and interaction between researchers in these directions. The common themes include mathematical models and data analysis, theoretical analysis, computational and statistical methods of dynamical systems and differential equations for the bio-system focused models, as well as applications in brain research.
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