Applied Non-Gaussian Processes

Applied Non-Gaussian Processes
Author: Mircea Grigoriu
Publisher: Prentice Hall
Total Pages: 472
Release: 1995
Genre: Matlab
ISBN:

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This text defines a variety of non-Gaussian processes, develops methods for generating realizations of non-Gaussian models, and provides methods for finding probabilistic characteristics of the output of linear filters with non-Gaussian inputs.

Random Processes: Measurement, Analysis and Simulation

Random Processes: Measurement, Analysis and Simulation
Author: J. Cacko
Publisher: Elsevier
Total Pages: 245
Release: 2012-12-02
Genre: Technology & Engineering
ISBN: 0444598030

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This book covers the basic topics associated with the measurement, analysis and simulation of random environmental processes which are encountered in practice when dealing with the dynamics, fatigue and reliability of structures in real environmental conditions. The treatment is self-contained and the authors have brought together and integrated the most important information relevant to this topic in order that the newcomer can see and study it as a whole. This approach should also be of interest to experienced engineers from fatigue laboratories who want to learn more about the possible methods of simulation, especially for use in real time on electrohydraulic computer-controlled loading machines.Problems of constructing a measuring system are dealt with in the first chapter. Here the authors discuss the choice of measuring conditions and locations, as well as the organization of a chain of devices for measuring and recording random environmental processes. Some experience gained from practical measurements is also presented. The recorded processes are further analysed by various methods. The choice is governed by the aims of the measurements and applications of the results. Chapter 2 is thus devoted to methods of random process evaluations for digital computers, both from the fatigue and dynamic point of view. The most important chapter is Chapter 3 as this presents a review of up-to-date methods of random process simulation with given statistical characteristics. These methods naturally follow those of random process analysis, and their results form initial data for the corresponding simulations algorithms, including occurrences of characteristic parameters of counting methods, reproduction of correlation theory characteristics and of autoregressive models. The simulation of non-stationary processes is treated in depth, taking into account their importance for practical applications and also the lack of information of this subject.The book is intended to help resolve many practical problems concerning the methods and quality of environmental process evaluation and simulation which can arise when up-to-date loading systems with computer control are being used in material, component and structural fatigue and dynamic research.

Non-Gaussian Random Vibration Fatigue Analysis and Accelerated Test

Non-Gaussian Random Vibration Fatigue Analysis and Accelerated Test
Author: Yu Jiang
Publisher: Springer Nature
Total Pages: 171
Release: 2021-09-15
Genre: Technology & Engineering
ISBN: 981163694X

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This book discusses the theory, method and application of non-Gaussian random vibration fatigue analysis and test. The main contents include statistical analysis method of non-Gaussian random vibration, modeling and simulation of non-Gaussian/non-stationary random vibration, response analysis under non-Gaussian base excitation, non-Gaussian random vibration fatigue life analysis, fatigue reliability evaluation of structural components under Gaussian/non-Gaussian random loadings, non-Gaussian random vibration accelerated test method and application cases. From this book, the readers can not only learn how to reproduce the non-Gaussian vibration environment actually experienced by the product, but also know how to evaluate the fatigue life and reliability of the structure under non-Gaussian random excitation.

Nonlinear Transformations of Random Processes

Nonlinear Transformations of Random Processes
Author: Ralph Deutsch
Publisher: Courier Dover Publications
Total Pages: 177
Release: 2017-11-08
Genre: Technology & Engineering
ISBN: 0486826031

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This concise treatment of nonlinear noise techniques encountered in system applications is suitable for advanced undergraduates and graduate students. It is also a valuable reference for systems analysts and communication engineers. 1962 edition.

Numerical Modelling of Random Processes and Fields

Numerical Modelling of Random Processes and Fields
Author: V. A. Ogorodnikov
Publisher: Walter de Gruyter GmbH & Co KG
Total Pages: 252
Release: 2018-11-05
Genre: Mathematics
ISBN: 3110941996

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No detailed description available for "Numerical Modelling of Random Processes and Fields".

Gaussian Processes for Machine Learning

Gaussian Processes for Machine Learning
Author: Carl Edward Rasmussen
Publisher: MIT Press
Total Pages: 266
Release: 2005-11-23
Genre: Computers
ISBN: 026218253X

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A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.

Random Processes for Engineers

Random Processes for Engineers
Author: Bruce Hajek
Publisher: Cambridge University Press
Total Pages: 429
Release: 2015-03-12
Genre: Technology & Engineering
ISBN: 1316241246

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This engaging introduction to random processes provides students with the critical tools needed to design and evaluate engineering systems that must operate reliably in uncertain environments. A brief review of probability theory and real analysis of deterministic functions sets the stage for understanding random processes, whilst the underlying measure theoretic notions are explained in an intuitive, straightforward style. Students will learn to manage the complexity of randomness through the use of simple classes of random processes, statistical means and correlations, asymptotic analysis, sampling, and effective algorithms. Key topics covered include: • Calculus of random processes in linear systems • Kalman and Wiener filtering • Hidden Markov models for statistical inference • The estimation maximization (EM) algorithm • An introduction to martingales and concentration inequalities. Understanding of the key concepts is reinforced through over 100 worked examples and 300 thoroughly tested homework problems (half of which are solved in detail at the end of the book).