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Multiscale Dynamical Systems: Identifying and Predicting Physiologic Fatigue

This presentation explores a theoretical and algorithmic framework for identifying and predicting physiologic fatigue within multiscale dynamical systems. Dr. David Chelidze discusses phase space warping and smooth orthogonal decomposition techniques to analyze nonlinear dynamics. The workshop at Duke University emphasizes the need for reduced-order models that adhere to concepts of subspace and dynamical consistency. By employing multivariate analysis, the work aims to enhance our understanding of complex systems in mechanical engineering and dynamic behaviors in various applications.

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Multiscale Dynamical Systems: Identifying and Predicting Physiologic Fatigue

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  1. Theoretical Framework Algorithmic Framework Conformational Dynamics Physiologic Fatigue Identification and Prediction A/D PSR PSWM PSWF SODC Multivariate Analysis for Characterizing Multiscale Dynamical SystemsDavid ChelidzeProfessor of Mechanical Engineeringchelidze@egr.uri.edu ● mcise.uri.edu/chelidze/nld Phase Space Warping Multi-Parameter Sensing Applications Smooth Orthogonal Decomposition 2ND NONLINEAR DYNAMICS WORKSHOP, MAY 27-28, 2010, DUKE UNIVERSITY, DURHAM, NORTH CAROLINA, UNITED STATES TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A

  2. Dynamical Characterization of Fatigue Nonlinear Reduced-Order Models based on new Concepts of Subspace Consistency and Dynamical Consistency 2ND NONLINEAR DYNAMICS WORKSHOP, MAY 27-28, 2010, DUKE UNIVERSITY, DURHAM, NORTH CAROLINA, UNITED STATES

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