This project is dedicated for the development of new methods and algorithms for time series analysis and application of these algorithms for the identification, forecasting and segmentation of chaotic processes. The essential distinction of this project is the applicability of the concept of the algebraic skeleton based on intelligent interpolation on regular grids for time series analysis. Such an approach will enable to develop new time series forecasting algorithms. The generalization of the algebraic skeleton in 2D will enable to design novel segmentation algorithms for complex intertwined sequences and digital images. On the other hand, 2D algebraic skeletons will enable the development of novel algorithms for the construction of solutions to processes governed by partial differential equations. All these research efforts will build novel algebraic approach for the consideration of chaotic dynamical systems.
Project funding:
Projects funded by the Research Council of Lithuania (RCL), Projects carried out by researchers’ teams
Project results:
More than 15 papers are published in International Journals.
Period of project implementation: 2015-04-01 - 2018-03-31
Project coordinator: Kaunas University of Technology
