Описание: The first two chapters are devoted to the basic theory of nonlinear functions of stationary Gaussian processes, Hermite polynomials, cumulants and higher order spectra, multiple Wiener-Ito integrals and finally chaotic Wiener-Ito spectral representation of subordinated processes.
Автор: Wei-Bin Zhang Название: Synergetic Economics ISBN: 3642759114 ISBN-13(EAN): 9783642759116 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Of particular interest are sudden (structural) changes, the existence of regular and irregular oscillations, the role of random factors in economic evolution, and the effects of time scales and rates of adjustment of economic variables in economic analysis.
Автор: Gao, Jiti Название: Nonlinear Time Series ISBN: 1584886137 ISBN-13(EAN): 9781584886136 Издательство: Taylor&Francis Рейтинг: Цена: 24499.00 р. Наличие на складе: Поставка под заказ.
Описание: This brief is a clear, concise description of the main techniques of time series analysis —stationary, autocorrelation, mutual information, fractal and multifractal analysis, chaos analysis, etc.— as they are applied to the influence of wind speed and solar radiation on the production of electrical energy from these renewable sources. The problem of implementing prediction models is addressed by using the embedding-phase-space approach: a powerful technique for the modeling of complex systems. Readers are also guided in applying the main machine learning techniques for classification of the patterns hidden in their time series and so will be able to perform statistical analyses that are not possible by using conventional techniques.The conceptual exposition avoids unnecessary mathematical details and focuses on concrete examples in order to ensure a better understanding of the proposed techniques.Results are well-illustrated by figures and tables.
Автор: De Gooijer, Jan G. Название: Elements of nonlinear time series analysis and forecasting ISBN: 3319827707 ISBN-13(EAN): 9783319827704 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications.
Автор: Holger Kantz Название: Nonlinear Time Series Analysis ISBN: 0521529026 ISBN-13(EAN): 9780521529020 Издательство: Cambridge Academ Рейтинг: Цена: 12355.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The time variability of many natural and social phenomena is not well described by standard methods of data analysis. Nonlinear time series analysis uses chaos theory and nonlinear dynamics to understand such seemingly unpredictable behaviour. Results are applied to real data from physics, biology, medicine and engineering.
Автор: Fan Jianqing, Yao Qiwei Название: Nonlinear Time Series / Nonparametric and Parametric Methods ISBN: 0387261427 ISBN-13(EAN): 9780387261423 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents the contemporary statistical methods and theory of nonlinear time series analysis. The principal focus is on nonparametric and semiparametric techniques developed in the last decade. It covers the techniques for modelling in state-space, in frequency-domain as well as in time-domain. To reflect the integration of parametric and nonparametric methods in analyzing time series data, the book also presents an up-to-date exposure of some parametric nonlinear models, including ARCH/GARCH models and threshold models. A compact view on linear ARMA models is also provided. Data arising in real applications are used throughout to show how nonparametric approaches may help to reveal local structure in high-dimensional data. Important technical tools are also introduced. The book will be useful for graduate students, application-oriented time series analysts, and new and experienced researchers. It will have the value both within the statistical community and across a broad spectrum of other fields such as econometrics, empirical finance, population biology and ecology. The prerequisites are basic courses in probability and statistics. Jianqing Fan, coauthor of the highly regarded book Local Polynomial Modeling, is Professor of Statistics at the University of North Carolina at Chapel Hill and the Chinese University of Hong Kong. His published work on nonparametric modeling, nonlinear time series, financial econometrics, analysis of longitudinal data, model selection, wavelets and other aspects of methodological and theoretical statistics has been recognized with the Presidents' Award from the Committee of Presidents of Statistical Societies, the Hettleman Prize for Artistic and Scholarly Achievement from the University of North Carolina, and by his election as a fellow of the American Statistical Association and the Institute of Mathematical Statistics. Qiwei Yao is Professor of Statistics at the London School of Economics and Political Science. He is an elected member of the International Statistical Institute, and has served on the editorial boards for the Journal of the Royal Statistical Society (Series B) and the Australian and New Zealand Journal of Statistics.
Описание: Safety evaluation by definition involves many complex factors and thus covers a wide range of topics. Figure 1 indicates the range of topics covered in the workshop. This table relates the authors to the subject matter, providing a guide through the diverse range of topics presented at the workshop.
Автор: Marat Akhmet Название: Nonlinear Hybrid Continuous/Discrete-Time Models ISBN: 9491216384 ISBN-13(EAN): 9789491216381 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines the author`s recently-introduced theory of equations with piece-wise constant argument of generalized type, demonstrating its use in the modeling of such real world problems as neural networks, blood pressure distribution and others.
Описание: Engineering systems operate through actuators, most of which will exhibit phenomena such as saturation or zones of no operation, commonly known as dead zones. These are examples of piecewise-affine characteristics, and they can have a considerable impact on the stability and performance of engineering systems. This book targets controller design for piecewise affine systems, fulfilling both stability and performance requirements.The authors present a unified computational methodology for the analysis and synthesis of piecewise affine controllers, taking an approach that is capable of handling sliding modes, sampled-data, and networked systems. They introduce algorithms that will be applicable to nonlinear systems approximated by piecewise affine systems, and they feature several examples from areas such as switching electronic circuits, autonomous vehicles, neural networks, and aerospace applications.Piecewise Affine Control: Continuous-Time, Sampled-Data, and Networked Systems is intended for graduate students, advanced senior undergraduate students, and researchers in academia and industry. It is also appropriate for engineers working on applications where switched linear and affine models are important.
Автор: Wang Qiying Название: Limit Theorems For Nonlinear Cointegrating Regression ISBN: 9814675628 ISBN-13(EAN): 9789814675628 Издательство: World Scientific Publishing Рейтинг: Цена: 15523.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides the limit theorems that can be used in the development of nonlinear cointegrating regression.
Автор: J. Franke; W. H?rdle; D. Martin Название: Robust and Nonlinear Time Series Analysis ISBN: 038796102X ISBN-13(EAN): 9780387961026 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Classical time series methods are based on the assumption that a particular stochastic process model generates the observed data.
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