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    Maximizing Sensitivity Vector Fields: A Parametric Study 

    Source: Journal of Computational and Nonlinear Dynamics:;2014:;volume( 009 ):;issue: 002:;page 21018
    Author(s): Sloboda, Andrew R.; Epureanu, Bogdan I.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Sensitivity vector fields (SVFs) have proven to be an effective method for identifying parametric variations in dynamical systems. These fields are constructed using information about how a dynamical system's attractor ...
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    Boundary Transformation Vectors: A Geometric Method of Quantifying Attractor Deformation for Structural Health Monitoring 

    Source: Journal of Computational and Nonlinear Dynamics:;2022:;volume( 017 ):;issue: 012:;page 121004
    Author(s): Sloboda, Andrew R.;Kong, Chin Ting
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Chaotic signals have long held promise as a means of excitation in structural health monitoring applications, but methods to process the structural response and infer damage are limited in number and effectiveness. Here, ...
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