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Recursive Identification and Parameter Estimation, 


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Название:  Recursive Identification and Parameter Estimation
ISBN: 9781138034280
Издательство: Taylor&Francis
Классификация:

ISBN-10: 1138034282
Обложка/Формат: Paperback
Страницы: 429
Вес: 0.64 кг.
Дата издания: 12.10.2017
Язык: English
Иллюстрации: 2 tables, black and white; 75 illustrations, black and white
Размер: 156 x 234 x 31
Ссылка на Издательство: Link
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Поставляется из: Европейский союз


Recursive Identification and Parameter Estimation

Автор: Chen, Han-Fu
Название: Recursive Identification and Parameter Estimation
ISBN: 1466568844 ISBN-13(EAN): 9781466568846
Издательство: Taylor&Francis
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Цена: 22202.00 р.
Наличие на складе: Нет в наличии.

Optimal Measurement Methods for Distributed Parameter System Identification

Автор: Ucinski, Dariusz
Название: Optimal Measurement Methods for Distributed Parameter System Identification
ISBN: 0849323134 ISBN-13(EAN): 9780849323133
Издательство: Taylor&Francis
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Цена: 24499.00 р.
Наличие на складе: Нет в наличии.

Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking

Автор: Van Trees
Название: Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking
ISBN: 0470120959 ISBN-13(EAN): 9780470120958
Издательство: Wiley
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Цена: 24404.00 р.
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Описание: Bayesian Bounds provides a collection of the important papers dealing with the theory and application of Bayesian bounds.  The book will be useful to both engineers and statisticians whether they are practicioners or theorists. The organization of the book and selection criteria is covered in the preface.  Each part is introduced with the contributions of each selected paper and their interrelationship. Part 1contains a short history of Reverend Thomas Bayes and his classic paper that established the field. Part 2 contains the original derivation of the Bayesian Cramer-Rao bound and a simple derivation of the multiple parameter Bayesian CRB. Part 3 discusses global Bayesian bounds to provide broad coverage of this important area. Part 4 considers the case in which some of the parameters are deterministic and some are random.  Hybrid Bayesian bounds are derived, as they are particularly important in the study of model mismatch problems. Part 5 considers generalized Cramer-Rao bounds. Part 6 discusses nonlinear stochastic dynamic systems. This type of system is a major component of most radar, sonar, and navigation systems.  They are also encountered in nonlinear filtering problems. Applications of various Bayesian bounds to static parameter estimation problems are covered in Part 7 and to dynamic systems in Part 8. The book concludes with papers from the statistics literature that focus on Bayesian bounds in various models in Part 9. 

Bayesian Inference

Автор: Hanns L. Harney
Название: Bayesian Inference
ISBN: 364205577X ISBN-13(EAN): 9783642055775
Издательство: Springer
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Цена: 13270.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Solving a longstanding problem in the physical sciences, this text and reference generalizes Gaussian error intervals to situations in which the data follow distributions other than Gaussian. The text is written at introductory level, with many examples and exercises.

Principles of Signal Detection and Parameter Estimation

Автор: Bernard C. Levy
Название: Principles of Signal Detection and Parameter Estimation
ISBN: 1441945652 ISBN-13(EAN): 9781441945655
Издательство: Springer
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Цена: 10447.00 р.
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Описание: This comprehensive text addresses signal processing and communication applications with an emphasis on fundamental principles. It also looks at recent advances in the field such as sequential testing, Gaussian and Robust detection, and detection of Markov Chains.

Recursive Nonlinear Estimation

Автор: Rudolph Kulhavy
Название: Recursive Nonlinear Estimation
ISBN: 3540760636 ISBN-13(EAN): 9783540760634
Издательство: Springer
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Цена: 14365.00 р.
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Описание: In a close analogy to matching data in Euclidean space, this monograph views parameter estimation as matching of the empirical distribution of data with a model-based distribution. The book suggests a solution to the problem of recursive estimation of non-Gaussian and nonlinear models.

Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series

Автор: K. Dzhaparidze; Samuel Kotz
Название: Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series
ISBN: 1461293251 ISBN-13(EAN): 9781461293255
Издательство: Springer
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Цена: 16769.00 р.
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Описание: of the spectral density I obtained by applying a certain statistical procedure to the observed values of the variables Xl` . , X , usually depends in n a complicated manner on the cyclic frequency). , are approximated by values of a certain sufficiently simple function 1 = 1

Parameter Estimation and Hypothesis Testing in Linear Models

Автор: Karl-Rudolf Koch
Название: Parameter Estimation and Hypothesis Testing in Linear Models
ISBN: 3642084613 ISBN-13(EAN): 9783642084614
Издательство: Springer
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Цена: 14667.00 р.
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Описание: Readers will find here presentations of the Gauss-Markoff model, the analysis of variance, the multivariate model, the model with unknown variance and covariance components and the regression model as well as the mixed model for estimating random parameters.

Parameter Estimation in Fractional Diffusion Models

Автор: Kubilius
Название: Parameter Estimation in Fractional Diffusion Models
ISBN: 331971029X ISBN-13(EAN): 9783319710297
Издательство: Springer
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Цена: 16769.00 р.
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Описание: This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. In particular, models of financial markets demonstrate various kinds of memory and usually this memory is modeled by fractional Brownian diffusion.

Capture-Recapture: Parameter Estimation for Open Animal Populations

Автор: Seber George A. F., Schofield Matthew R.
Название: Capture-Recapture: Parameter Estimation for Open Animal Populations
ISBN: 3030181863 ISBN-13(EAN): 9783030181864
Издательство: Springer
Рейтинг:
Цена: 12577.00 р.
Наличие на складе: Поставка под заказ.

Описание: This comprehensive book, rich with applications, offers a quantitative framework for the analysis of the various capture-recapture models for open animal populations, while also addressing associated computational methods. The state of our wildlife populations provides a litmus test for the state of our environment, especially in light of global warming and the increasing pollution of our land, seas, and air. In addition to monitoring our food resources such as fisheries, we need to protect endangered species from the effects of human activities (e.g. rhinos, whales, or encroachments on the habitat of orangutans). Pests must be be controlled, whether insects or viruses, and we need to cope with growing feral populations such as opossums, rabbits, and pigs.Accordingly, we need to obtain information about a given population’s dynamics, concerning e.g. mortality, birth, growth, breeding, sex, and migration, and determine whether the respective population is increasing , static, or declining. There are many methods for obtaining population information, but the most useful (and most work-intensive) is generically known as “capture-recapture,” where we mark or tag a representative sample of individuals from the population and follow that sample over time using recaptures, resightings, or dead recoveries. Marks can be natural, such as stripes, fin profiles, and even DNA; or artificial, such as spots on insects. Attached tags can, for example, be simple bands or streamers, or more sophisticated variants such as radio and sonic transmitters. To estimate population parameters, sophisticated and complex mathematical models have been devised on the basis of recapture information and computer packages. This book addresses the analysis of such models. It is primarily intended for ecologists and wildlife managers who wish to apply the methods to the types of problems discussed above, though it will also benefit researchers and graduate students in ecology. Familiarity with basic statistical concepts is essential.

Parameter Estimation in Fractional Diffusion Models

Автор: Kubilius Kęstutis, Mishura Yuliya, Ralchenko Kostiantyn
Название: Parameter Estimation in Fractional Diffusion Models
ISBN: 331989031X ISBN-13(EAN): 9783319890319
Издательство: Springer
Рейтинг:
Цена: 16769.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. In particular, models of financial markets demonstrate various kinds of memory and usually this memory is modeled by fractional Brownian diffusion.

Capture-Recapture: Parameter Estimation for Open Animal Populations

Автор: Seber George A. F., Schofield Matthew R.
Название: Capture-Recapture: Parameter Estimation for Open Animal Populations
ISBN: 3030181898 ISBN-13(EAN): 9783030181895
Издательство: Springer
Рейтинг:
Цена: 12577.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This comprehensive book, rich with applications, offers a quantitative framework for the analysis of the various capture-recapture models for open animal populations, while also addressing associated computational methods. The state of our wildlife populations provides a litmus test for the state of our environment, especially in light of global warming and the increasing pollution of our land, seas, and air. In addition to monitoring our food resources such as fisheries, we need to protect endangered species from the effects of human activities (e.g. rhinos, whales, or encroachments on the habitat of orangutans). Pests must be be controlled, whether insects or viruses, and we need to cope with growing feral populations such as opossums, rabbits, and pigs. Accordingly, we need to obtain information about a given population’s dynamics, concerning e.g. mortality, birth, growth, breeding, sex, and migration, and determine whether the respective population is increasing , static, or declining. There are many methods for obtaining population information, but the most useful (and most work-intensive) is generically known as “capture-recapture,” where we mark or tag a representative sample of individuals from the population and follow that sample over time using recaptures, resightings, or dead recoveries. Marks can be natural, such as stripes, fin profiles, and even DNA; or artificial, such as spots on insects. Attached tags can, for example, be simple bands or streamers, or more sophisticated variants such as radio and sonic transmitters. To estimate population parameters, sophisticated and complex mathematical models have been devised on the basis of recapture information and computer packages. This book addresses the analysis of such models. It is primarily intended for ecologists and wildlife managers who wish to apply the methods to the types of problems discussed above, though it will also benefit researchers and graduate students in ecology. Familiarity with basic statistical concepts is essential.


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