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Author: H. Salzwedel
Publisher:
ISBN:
Category :
Languages : en
Pages : 63
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Book Description
Analysis of test results indicates that the measurement and process noise is significantly non-white and non-Gaussian. Some analyses indicate that 10% to 15% of the data points may deviate significantly from non-Gaussian distribution. In addition, numerous sources lead to non-white noise. These errors effect both the accuracy of state and parameter estimates as well as the estimation of accuracy levels. In this report, techniques have been developed to treat systems with non-white and non-Gaussian noise. These techniques provide good estimates under given whiteness and Gaussianess conditions. The procedures are simple and can be easily incorporated in the standard maximum likelihood and model structure determination methods.
Author: H. Salzwedel
Publisher:
ISBN:
Category :
Languages : en
Pages : 63
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Book Description
Analysis of test results indicates that the measurement and process noise is significantly non-white and non-Gaussian. Some analyses indicate that 10% to 15% of the data points may deviate significantly from non-Gaussian distribution. In addition, numerous sources lead to non-white noise. These errors effect both the accuracy of state and parameter estimates as well as the estimation of accuracy levels. In this report, techniques have been developed to treat systems with non-white and non-Gaussian noise. These techniques provide good estimates under given whiteness and Gaussianess conditions. The procedures are simple and can be easily incorporated in the standard maximum likelihood and model structure determination methods.
Author: Frank Moss
Publisher: Cambridge University Press
ISBN: 0521352290
Category : Mathematics
Languages : en
Pages : 410
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Book Description
A specially written review of all areas of noise and nonlinear in natural environments.
Author: Rolf Isermann
Publisher: Springer
ISBN: 9783540871552
Category : Technology & Engineering
Languages : en
Pages : 705
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Book Description
Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.
Author: Tomás Caraballo
Publisher: Springer
ISBN: 3319492470
Category : Mathematics
Languages : en
Pages : 115
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Book Description
This book offers an introduction to the theory of non-autonomous and stochastic dynamical systems, with a focus on the importance of the theory in the Applied Sciences. It starts by discussing the basic concepts from the theory of autonomous dynamical systems, which are easier to understand and can be used as the motivation for the non-autonomous and stochastic situations. The book subsequently establishes a framework for non-autonomous dynamical systems, and in particular describes the various approaches currently available for analysing the long-term behaviour of non-autonomous problems. Here, the major focus is on the novel theory of pullback attractors, which is still under development. In turn, the third part represents the main body of the book, introducing the theory of random dynamical systems and random attractors and revealing how it may be a suitable candidate for handling realistic models with stochasticity. A discussion of future research directions serves to round out the coverage.
Author: David Brillinger
Publisher: Springer
ISBN:
Category : Gardening
Languages : en
Pages : 416
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Book Description
Part of a two volume set based on a recent IMA program of the same name. The goal of the program and these books is to develop a community of statistical and other scientists kept up-to-date on developments in this quickly evolving and interdisciplinary field. Consequently, these books present recent material by distinguished researchers. Topics discussed in Part I include nonlinear and non- Gaussian models and processes (higher order moments and spectra, nonlinear systems, applications in astronomy, geophysics, engineering, and simulation) and the interaction of time series analysis and statistics (information model identification, categorical valued time series, nonparametric and semiparametric methods). Self-similar processes and long-range dependence (time series with long memory, fractals, 1/f noise, stable noise) and time series research common to engineers and economists (modeling of multivariate and possibly non-stationary time series, state space and adaptive methods) are discussed in Part II.
Author: Arunabha Bagchi
Publisher:
ISBN:
Category : Electronic noise
Languages : en
Pages : 82
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Book Description
The present dissertation is a study of identifying parameters of a continuous-time dynamical system with noisy observation and with or without noise in the state of the system. In identifying parameters of a continuous-time dynamical system, the difficulty arises when the observation noise covariance is unknown. The present paper solves this problem in the case of a linear time invariant system with white noise affecting additively both the state and the observation. Likelihood functional cannot be obtained when the observation noise covariance is unknown. A similar procedure, however, works and the estimates are obtained by finding roots of an appropriate functional. It is shown that the estimates obtained are weakly consistent. In the special case of no noise in the state, it is further shown that similar procedure yields estimates that are strongly consistent. Consistency is proved under certain sufficient condition called the 'Identifiability Condition'. This condition is studied in detail and computational algorithm for determining the estimates is discussed.
Author: Sez Atamturktur
Publisher: Springer
ISBN: 3319297546
Category : Technology & Engineering
Languages : en
Pages : 366
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Book Description
Model Validation and Uncertainty Quantifi cation, Volume 3. Proceedings of the 34th IMAC, A Conference and Exposition on Dynamics of Multiphysical Systems: From Active Materials to Vibroacoustics, 2016, the third volume of ten from the Conference brings together contributions to this important area of research and engineering. Th e collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: • Uncertainty Quantifi cation & Model Validation • Uncertainty Propagation in Structural Dynamics • Bayesian & Markov Chain Monte Carlo Methods • Practical Applications of MVUQ • Advances in MVUQ & Model Updating • Robustness in Design & Validation • Verifi cation & Validation Methods
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 2
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Book Description
Pinsky's research is concerned with the exponential growth rate (= Lyapunov exponent) of solutions of stochastic differential equations. In a paper to appear in the Annals of Applied Probability, a formula is obtained for the quadratic Lyapunov exponent of the simple harmonic oscillator in the presence of a finite-state Markov noise process. In case the noise process is reversible, the quadratic Lyapunov exponent is strictly less than for the corresponding white noise process obtained from the central limit theorem. An example is presented of a non-reversible Markov noise process for which this inequality is reversed. In another article, to appear in the volume 'Stochastic Partial Differential Equations and their Applications' in the Springer Verlag Lecture Notes in Control and Information Sciences (Proceedings of the 1991 Charlotte NC Conference on SPDE, ed. B. Rozovskii), the Lyapunov exponent is computed for the, solution of a hyperbolic partial differential equation with damping. In this case, one studies the exponential growth rate of the energy of the solution with Dirichlet boundary conditions. The detailed results depend on the size of the damping constant (overdamped vs. underdamped case). To our knowledge, this is the first study ever of the Lyapunov exponent for a partial differential equation. Lyapunov exponent, Stochastic oscillator, Fourier transform, Heat kernel.
Author:
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 592
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Book Description
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 1014
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Book Description
