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    The Girsanov Linearization Method for Stochastically Driven Nonlinear Oscillators 

    Source: Journal of Applied Mechanics:;2007:;volume( 074 ):;issue: 005:;page 885
    Author(s): Nilanjan Saha; D. Roy
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: For most practical purposes, the focus is often on obtaining statistical moments of the response of stochastically driven oscillators than on the determination of pathwise response histories. In ...
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    Monte–Carlo Based Method for Predicting Extreme Value Statistics of Uncertain Structures 

    Source: Journal of Engineering Mechanics:;2010:;Volume ( 136 ):;issue: 012
    Author(s): Nilanjan Saha; A. Naess
    Publisher: American Society of Civil Engineers
    Abstract: In the present paper, a simple method is proposed for predicting the extreme response of uncertain structures subjected to stochastic excitation. Many of the currently used approaches to extreme response predictions are ...
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    Two-Stage Extended Kalman Filters with Derivative-Free Local Linearizations 

    Source: Journal of Engineering Mechanics:;2011:;Volume ( 137 ):;issue: 008
    Author(s): Nilanjan Saha; D. Roy
    Publisher: American Society of Civil Engineers
    Abstract: This paper proposes a derivative-free two-stage extended Kalman filter (2-EKF) especially suited for state and parameter identification of mechanical oscillators under Gaussian white noise. Two sources of modeling uncertainties ...
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