Identification in Dynamic Shock-Error Models, A. Maravall
Автор: F.J.III Doyle; R.K. Pearson; B.A. Ogunnaike Название: Identification and Control Using Volterra Models ISBN: 1447110633 ISBN-13(EAN): 9781447110637 Издательство: Springer Рейтинг: Цена: 30745.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Much has been written about the general difficulty of developing the models required for model-based control of processes whose dynamics exhibit signif- icant nonlinearity (for further discussion and references, see Chapter 1). In fact, the development ofthese models stands as a significant practical imped- iment to widespread industrial application oftechniques like nonlinear model predictive control (NMPC), whoselinear counterpart has profoundly changed industrial practice. One ofthe reasons for this difficulty lies in the enormous variety of "nonlinear models," different classes of which can be less similar to each other than they are to the class of linear models. Consequently, it is a practical necessity to restrict consideration to one or a few specific nonlinear model classes if we are to succeed in developing, understanding, and using nonlinear models as a basis for practical control schemes. Because they repre- sent a highly structured extension ofthe class oflinear finite impulse response (FIR) models on which industrially popular linear MPC implementations are based, this book is devoted to the class of discrete-time Volterra models and a fewother, closelyrelated, nonlinear model classes. The objective ofthis book is to provide a useful reference for researchers in the field of process control and closely related areas, collecting a reasonably wide variety of results that may be found in different parts of the large literature that exists on the gen- eral topics of process control, nonlinear systems theory, statistical time-series models, biomedical engineering, and digital signal processing, among others.
Автор: D. Hawkins Название: Identification of Outliers ISBN: 9401539960 ISBN-13(EAN): 9789401539968 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The problem of outliers is one of the oldest in statistics, and during the last century and a half interest in it has waxed and waned several times. Currently it is once again an active research area after some years of relative neglect, and recent work has solved a number of old problems in outlier theory, and identified new ones.
Автор: Achilleas Zapranis; Apostolos-Paul N. Refenes Название: Principles of Neural Model Identification, Selection and Adequacy ISBN: 1852331399 ISBN-13(EAN): 9781852331399 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Based on developments in estimation theory, model selection and the theory of mis-specified models, this volume develops neural networks into a financial econometrics tool for non-parametric modelling. It provides the theoretical framework and uses neural networks for complex financial phenomena.
Автор: Abonyi JГЎnos, Feil BalГЎzs Название: Cluster Analysis for Data Mining and System Identification ISBN: 3764379871 ISBN-13(EAN): 9783764379872 Издательство: Springer Рейтинг: Цена: 13969.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents new approaches to data mining and system identification. Algorithmsthat can be used for the clustering of data have been overviewed. New techniques andtools are presented for the clustering, classification, regression and visualization ofcomplex datasets. Special attention is given to the analysis of historical process data,tailored algorithms are presented for the data driven modeling of dynamical systems,determining the model order of nonlinear input-output black box models, and thesegmentation of multivariate time-series. The main methods and techniques areillustrated through several simulated and real-world applications from data mining andprocess engineering practice.The books is aimed primarily at practitioners, researches, and professionals in statistics,data mining, business intelligence, and systems engineering, but it is also accessible tograduate and undergraduate students in applied mathematics, computer science, electricaland process engineering. Familiarity with the basics of system identification and fuzzysystems is helpful but not required.
Автор: Hugues Garnier; Liuping Wang Название: Identification of Continuous-time Models from Sampled Data ISBN: 1849967407 ISBN-13(EAN): 9781849967402 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is the first book dedicated to direct continuous-time model identification for 15 years. The CONTSID toolbox discussed in the final chapter gives an overview of developments and practical examples in which MATLAB (R) can be used for direct time-domain identification of continuous-time systems.
Описание: Dedicated to the pioneering Prof. Peter Young, this volume features cutting-edge research in systems and control subjects he has covered in 45 years of research, including system identification, time-series analysis, environmetric modelling and system design.
Автор: Sergio Bittanti; Giorgio Picci Название: Identification, Adaptation, Learning ISBN: 3642082483 ISBN-13(EAN): 9783642082481 Издательство: Springer Рейтинг: Цена: 38992.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Christiaan Heij Название: Deterministic Identification of Dynamical Systems ISBN: 354051323X ISBN-13(EAN): 9783540513230 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In deterministic identification the identified system is determined on the basis of a complexity measure of models and a misfit measure of models with respect to data. For the case of exact modelling a procedure is presented which is inspired by objectives of simplicity and corroboration.
Автор: ByoungSeon Choi Название: ARMA Model Identification ISBN: 1461397472 ISBN-13(EAN): 9781461397472 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The main topics covered include: Box-Jenkins` method, inverse autocorrelation functions, penalty function identification such as AIC, BIC techniques and Hannan and Quinn`s method, instrumental regression, and a range of pattern identification methods.
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