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Advances in Adaptive Data Analysis provides a common forum for scientists and engineers working in the areas of data analysis, especially the adaptive data analysis methodology and applications, to communicate their original findings and interact with one another and thereby enhance the opportunities for such cross-fertilization of ideas and reporting on new research frontiers. The Journal publishes original papers pertaining to state-of-the-art research and development in adaptive data analysis methodology and applications with emphasis on data from nonlinear and nonstationary processes.
We welcome papers in the following categories:
Adaptive Data Analysis Methodology
Adaptive approach in data analysis in general
Adaptive decomposition and basis generation for one and multi-dimensional data
Spline, regression, prediction and compression for nonlinear and nonstationary time series
Theoretical foundation for Empirical Mode Decomposition
Analysis methods for data from nonlinear and nonstationary processes
Statistical description of nonlinear and nonstationary data
Time frequency and time scale Analysis
Instantaneous frequency computation
Filtering for nonlinear and nonstationary data
Nonlinear system identification
Applications
Nondestructive health monitoring
Sound and nonlinear vibrations
Earthquake
Nonlinear waves and oceanic data analysis
Weather and climate data analysis
Biomedical and physiological data analysis
Financial data analysis
Image analysis and compression
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