Abstract
Biomedical Signal Processing and Modeling Complexity of Living Systems
Highlights
Living systems are often maintained by information flows and, as such, they present interesting mathematical problems for example, in the modeling and analysis of spatial structures, self-organization, environmental interaction, behavior, and development
Many researchers have been studying these problems because of their interesting mathematical features and because of their scientific importance. The focus of this special issue is the mathematical analysis and modeling of time series in living systems and biomedical signals. It is mostly interested in the related new development of both theoretical study and practical implementation, either with modeling, complexity, statistics, or signal transformation in living systems
The topics of the research papers and review papers are connected with the living systems and biomedical signals, including modeling dynamical complexity in living systems, for example, network dynamics, mass action, dynamical systems theory, methods for analysis and characterization of dynamical complexity, biomedical signal analysis such as mathematical pattern analysis of biological signals, generative mechanisms of biological signal patterning, implementation of signal analysis algorithms, linking biological structure to biological signal generation, and intracellular signal processing, as well as related models and applications, such as systems theory, biological organization, and biomedical information processing
Summary
Biomedical Signal Processing and Modeling Complexity of Living Systems Carlo Cattani,1 Radu Badea,2 Shengyong Chen,3 and Maria Crisan4 Living systems are often maintained by information flows and, as such, they present interesting mathematical problems for example, in the modeling and analysis of spatial structures, self-organization, environmental interaction, behavior, and development. Many researchers have been studying these problems because of their interesting mathematical features and because of their scientific importance.
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