Monte Carlo filters for identification of nonlinear structural dynamical systems

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo

Probabilistic modeling provides the capability to represent and manipulate uncertainty in data, models, decisions and predictions. We are concerned with the problem of learning probabilistic models of dynamical systems from measured data. Specifically, we consider learning of probabilistic nonlinear state space models. There is no closedform solution available for this problem, implying that we...

متن کامل

Multistage Modified Sinc Method for Solving Nonlinear Dynamical Systems

The sinc method is known as an ecient numerical method for solving ordinary or par-tial dierential equations but the system of dierential equations has not been solved by this method which is the focus of this paper. We have shown that the proposed version of sinc is able to solve sti system while Runge-kutta method can not able to solve. Moreover, Due to the great attention to mathematical mod...

متن کامل

Convergence of Nonlinear Filters for Randomly Perturbed Dynamical Systems∗

We establish convergence of the nonlinear filter of the state of a randomly perturbed dynamical system in which the perturbation is a rapidly fluctuating ergodic Markov process, and the observation process conditions the state of the system. The limiting nonlinear filter is completely characterized.

متن کامل

Improvement Strategies for Monte Carlo Particle Filters

The particle filtering field has seen an upsurge in interest over recent years and accompanying this a number of enhancements to the basic techniques have been suggested in the literature. In this paper we collect together a group of these developments which seem to be particularly important for time series applications and give a broad discussion of the methods, showing the interrelationships ...

متن کامل

Sequential Monte Carlo sampling in hidden Markov models of nonlinear dynamical systems

We investigate the issue of which state functionals can have their uncertainty estimated efficiently in dynamical systems with uncertainty. Because of the high dimensionality and complexity of the problem, sequential Monte Carlo (SMC) methods are used. We prove that the variance of the SMC method is bounded linearly in the number of time steps when the proposal distribution is truncated normal ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Sadhana

سال: 2006

ISSN: 0256-2499,0973-7677

DOI: 10.1007/bf02716784