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Author : Robert Kalaba
Publisher :
ISBN 13 :
Total Pages : 26 pages
Book Rating : 4.:/5 (833 download)
Download or read book Exact Sequential Filtering, Smoothing and Prediction for Nonlinear Systems written by Robert Kalaba and published by . This book was released on 1985 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : J. S. Meditch
Publisher :
ISBN 13 :
Total Pages : 21 pages
Book Rating : 4.:/5 (227 download)
Download or read book Sequential Estimation for Discrete-time Nonlinear Systems written by J. S. Meditch and published by . This book was released on 1969 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of state and parameter estimation for noisy discrete-time nonlinear dynamic systems is examined from the viewpoint of marginal maximum likelihood estimation. Approximate algorithms for sequential prediction, filtering, and smoothing are developed. The former two are in agreement with previous results; the latter is new. A technique for iterative-sequential filtering and smoothing using Newton's method is indicated. A numerical example is included to illustrate the results. (Author).
Author : David M Trujillo
Publisher : CRC Press
ISBN 13 : 1351359150
Total Pages : 209 pages
Book Rating : 4.3/5 (513 download)
Download or read book Practical Inverse Analysis in Engineering (1997) written by David M Trujillo and published by CRC Press. This book was released on 2017-11-22 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continuing advances in computer technology have made it possible for engineers and scientists to construct increasingly realistic models of physical processes. Practical Inverse Analysis in Engineering addresses an important area of engineering that will become even more significant to engineers and scientists - combining measurements with engineering models. This self-contained text presents applied mathematical tools for bridging the gap between real-world measurements and mathematical models. The book demonstrates how to treat "ill-conditioned" inverse analysis problems - those problems where the solution is extremely sensitive to the data - with the powerful theory of dynamic programming. A second theory, generalized-cross-validation, is also discussed as a useful partner in handling real data. The material in the book, much of it published for the first time, presents theories in a general unified setting, so readers can apply the information to their models. A disk containing DYNAVAL programming software lets readers try the methods presented in the text.
Author : Simo Särkkä
Publisher : Cambridge University Press
ISBN 13 : 110703065X
Total Pages : 255 pages
Book Rating : 4.1/5 (7 download)
Download or read book Bayesian Filtering and Smoothing written by Simo Särkkä and published by Cambridge University Press. This book was released on 2013-09-05 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.
Author : Norman Morrison
Publisher : McGraw-Hill Companies
ISBN 13 :
Total Pages : 680 pages
Book Rating : 4.:/5 (318 download)
Download or read book Introduction to Sequential Smoothing and Prediction written by Norman Morrison and published by McGraw-Hill Companies. This book was released on 1969 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Sueo Sugimoto
Publisher : Ohmsha, Ltd.
ISBN 13 : 4274805026
Total Pages : 457 pages
Book Rating : 4.2/5 (748 download)
Download or read book Nonlinear Filters written by Sueo Sugimoto and published by Ohmsha, Ltd.. This book was released on 2020-12-10 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers a broad range of filter theories, algorithms, and numerical examples. The representative linear and nonlinear filters such as the Kalman filter, the steady-state Kalman filter, the H infinity filter, the extended Kalman filter, the Gaussian sum filter, the statistically linearized Kalman filter, the unscented Kalman filter, the Gaussian filter, the cubature Kalman filter are first visited. Then, the non-Gaussian filters such as the ensemble Kalman filter and the particle filters based on the sequential Bayesian filter and the sequential importance resampling are described, together with their recent advances. Moreover, the information matrix in the nonlinear filtering, the nonlinear smoother based on the Markov Chain Monte Carlo, the continuous-discrete filters, factorized filters, and nonlinear filters based on stochastic approximation method are detailed. 1 Review of the Kalman Filter and Related Filters 2 Information Matrix in Nonlinear Filtering 3 Extended Kalman Filter and Gaussian Sum Filter 4 Statistically Linearized Kalman Filter 5 The Unscented Kalman Filter 6 General Gaussian Filters and Applications 7 The Ensemble Kalman Filter 8 Particle Filter 9 Nonlinear Smoother with Markov Chain Monte Carlo 10 Continuous-Discrete Filters 11 Factorized Filters 12 Nonlinear Filters Based on Stochastic Approximation Method
Author : S. Mittnik
Publisher : Elsevier
ISBN 13 : 1483296229
Total Pages : 194 pages
Book Rating : 4.4/5 (832 download)
Download or read book System-Theoretic Methods in Economic Modelling I written by S. Mittnik and published by Elsevier. This book was released on 2014-06-28 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: The value of applying system-theoretic concepts to economic modelling problems arises from the fact that it offers a unifying framework for modelling dynamic systems. In addition to offering this powerful conceptual framework, it provides a wide range of tools useful in applied work. System-theoretic techniques enter predominantly two stages of economic modelling efforts: the stage of model construction and the stage of model application in accordance with the modelling. The objective of this and subsequent volumes on System-Theoretic Methods in Economic Modelling I is to initiate and/or intensify dialogues between researchers and practitioners within and across the disciplines involved. This first volume brings together papers exhibiting a wide range of system-theoretic techniques and applications to economic problems. The papers have been divided into two groups, following roughly--but not necessarily--the above classification into the construction and application stages of economic modelling. The papers in the first group focus on the identification of dynamic and static systems, while the papers in the second group address dynamic optimization problems.
Author : Peyman Setoodeh
Publisher : John Wiley & Sons
ISBN 13 : 1119078156
Total Pages : 308 pages
Book Rating : 4.1/5 (19 download)
Download or read book Nonlinear Filters written by Peyman Setoodeh and published by John Wiley & Sons. This book was released on 2022-03-04 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: NONLINEAR FILTERS Discover the utility of using deep learning and (deep) reinforcement learning in deriving filtering algorithms with this insightful and powerful new resource Nonlinear Filters: Theory and Applications delivers an insightful view on state and parameter estimation by merging ideas from control theory, statistical signal processing, and machine learning. Taking an algorithmic approach, the book covers both classic and machine learning-based filtering algorithms. Readers of Nonlinear Filters will greatly benefit from the wide spectrum of presented topics including stability, robustness, computability, and algorithmic sufficiency. Readers will also enjoy: Organization that allows the book to act as a stand-alone, self-contained reference A thorough exploration of the notion of observability, nonlinear observers, and the theory of optimal nonlinear filtering that bridges the gap between different science and engineering disciplines A profound account of Bayesian filters including Kalman filter and its variants as well as particle filter A rigorous derivation of the smooth variable structure filter as a predictor-corrector estimator formulated based on a stability theorem, used to confine the estimated states within a neighborhood of their true values A concise tutorial on deep learning and reinforcement learning A detailed presentation of the expectation maximization algorithm and its machine learning-based variants, used for joint state and parameter estimation Guidelines for constructing nonparametric Bayesian models from parametric ones Perfect for researchers, professors, and graduate students in engineering, computer science, applied mathematics, and artificial intelligence, Nonlinear Filters: Theory and Applications will also earn a place in the libraries of those studying or practicing in fields involving pandemic diseases, cybersecurity, information fusion, augmented reality, autonomous driving, urban traffic network, navigation and tracking, robotics, power systems, hybrid technologies, and finance.
Author : Garry Einicke
Publisher : BoD – Books on Demand
ISBN 13 : 9533077522
Total Pages : 290 pages
Book Rating : 4.5/5 (33 download)
Download or read book Smoothing, Filtering and Prediction written by Garry Einicke and published by BoD – Books on Demand. This book was released on 2012-02-24 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the classical smoothing, filtering and prediction techniques together with some more recently developed embellishments for improving performance within applications. It aims to present the subject in an accessible way, so that it can serve as a practical guide for undergraduates and newcomers to the field. The material is organised as a ten-lecture course. The foundations are laid in Chapters 1 and 2, which explain minimum-mean-square-error solution construction and asymptotic behaviour. Chapters 3 and 4 introduce continuous-time and discrete-time minimum-variance filtering. Generalisations for missing data, deterministic inputs, correlated noises, direct feedthrough terms, output estimation and equalisation are described. Chapter 5 simplifies the minimum-variance filtering results for steady-state problems. Observability, Riccati equation solution convergence, asymptotic stability and Wiener filter equivalence are discussed. Chapters 6 and 7 cover the subject of continuous-time and discrete-time smoothing. The main fixed-lag, fixed-point and fixed-interval smoother results are derived. It is shown that the minimum-variance fixed-interval smoother attains the best performance. Chapter 8 attends to parameter estimation. As the above-mentioned approaches all rely on knowledge of the underlying model parameters, maximum-likelihood techniques within expectation-maximisation algorithms for joint state and parameter estimation are described. Chapter 9 is concerned with robust techniques that accommodate uncertainties within problem specifications. An extra term within Riccati equations enables designers to trade-off average error and peak error performance. Chapter 10 rounds off the course by applying the afore-mentioned linear techniques to nonlinear estimation problems. It is demonstrated that step-wise linearisations can be used within predictors, filters and smoothers, albeit by forsaking optimal performance guarantees.
Author :
Publisher :
ISBN 13 :
Total Pages : 1296 pages
Book Rating : 4.:/5 (49 download)
Download or read book Journal of Economic Dynamics & Control written by and published by . This book was released on 1987 with total page 1296 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jitendra R. Raol
Publisher : CRC Press
ISBN 13 : 1498745180
Total Pages : 581 pages
Book Rating : 4.4/5 (987 download)
Download or read book Nonlinear Filtering written by Jitendra R. Raol and published by CRC Press. This book was released on 2017-07-12 with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Filtering covers linear and nonlinear filtering in a comprehensive manner, with appropriate theoretic and practical development. Aspects of modeling, estimation, recursive filtering, linear filtering, and nonlinear filtering are presented with appropriate and sufficient mathematics. A modeling-control-system approach is used when applicable, and detailed practical applications are presented to elucidate the analysis and filtering concepts. MATLAB routines are included, and examples from a wide range of engineering applications - including aerospace, automated manufacturing, robotics, and advanced control systems - are referenced throughout the text.
Author : Venkatarama Krishnan
Publisher : Courier Corporation
ISBN 13 : 0486781836
Total Pages : 353 pages
Book Rating : 4.4/5 (867 download)
Download or read book Nonlinear Filtering and Smoothing written by Venkatarama Krishnan and published by Courier Corporation. This book was released on 2013-10-17 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most useful for graduate students in engineering and finance who have a basic knowledge of probability theory, this volume is designed to give a concise understanding of martingales, stochastic integrals, and estimation. It emphasizes applications. Many theorems feature heuristic proofs; others include rigorous proofs to reinforce physical understanding. Numerous end-of-chapter problems enhance the book's practical value. After introducing the basic measure-theoretic concepts of probability and stochastic processes, the text examines martingales, square integrable martingales, and stopping times. Considerations of white noise and white-noise integrals are followed by examinations of stochastic integrals and stochastic differential equations, as well as the associated Ito calculus and its extensions. After defining the Stratonovich integral, the text derives the correction terms needed for computational purposes to convert the Ito stochastic differential equation to the Stratonovich form. Additional chapters contain the derivation of the optimal nonlinear filtering representation, discuss how the Kalman filter stands as a special case of the general nonlinear filtering representation, apply the nonlinear filtering representations to a class of fault-detection problems, and discuss several optimal smoothing representations.
Author : J. S. Meditch
Publisher :
ISBN 13 :
Total Pages : 18 pages
Book Rating : 4.:/5 (227 download)
Download or read book Formal Algorithms for Continuous-time Nonlinear Filtering and Smoothing written by J. S. Meditch and published by . This book was released on 1969 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman's formal limiting procedure is applied to some recent results in sequential discrete-time nonlinear filtering and smoothing to obtain the corresponding estimation algorithms for continuous-time nonlinear dynamic systems. The resulting filtering algorithm is found to agree with the well-known Detchmendy-Sridhar filter which was obtained via another method. The present smoothing algorithm is a new result. It is argued that the combined filter-smoothing results here lead to an estimation algorithm which is second-order in both system dynamics and measurement function nonlinearity. (Author).
Author :
Publisher :
ISBN 13 :
Total Pages : 832 pages
Book Rating : 4.:/5 (49 download)
Download or read book Journal of Economic Behavior & Organization written by and published by . This book was released on 1992 with total page 832 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : National Research Council (U.S.). Committee on Applied and Theoretical Statistics. Panel on Statistics and Oceanography
Publisher : National Academies
ISBN 13 :
Total Pages : 76 pages
Book Rating : 4.0/5 (21 download)
Download or read book Statistics and Physical Oceanography written by National Research Council (U.S.). Committee on Applied and Theoretical Statistics. Panel on Statistics and Oceanography and published by National Academies. This book was released on 1993 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 :
Total Pages : 892 pages
Book Rating : 4.:/5 (31 download)
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1994 with total page 892 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Tülay Adali
Publisher : John Wiley & Sons
ISBN 13 : 0470575743
Total Pages : 428 pages
Book Rating : 4.4/5 (75 download)
Download or read book Adaptive Signal Processing written by Tülay Adali and published by John Wiley & Sons. This book was released on 2010-06-25 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leading experts present the latest research results in adaptive signal processing Recent developments in signal processing have made it clear that significant performance gains can be achieved beyond those achievable using standard adaptive filtering approaches. Adaptive Signal Processing presents the next generation of algorithms that will produce these desired results, with an emphasis on important applications and theoretical advancements. This highly unique resource brings together leading authorities in the field writing on the key topics of significance, each at the cutting edge of its own area of specialty. It begins by addressing the problem of optimization in the complex domain, fully developing a framework that enables taking full advantage of the power of complex-valued processing. Then, the challenges of multichannel processing of complex-valued signals are explored. This comprehensive volume goes on to cover Turbo processing, tracking in the subspace domain, nonlinear sequential state estimation, and speech-bandwidth extension. Examines the seven most important topics in adaptive filtering that will define the next-generation adaptive filtering solutions Introduces the powerful adaptive signal processing methods developed within the last ten years to account for the characteristics of real-life data: non-Gaussianity, non-circularity, non-stationarity, and non-linearity Features self-contained chapters, numerous examples to clarify concepts, and end-of-chapter problems to reinforce understanding of the material Contains contributions from acknowledged leaders in the field Adaptive Signal Processing is an invaluable tool for graduate students, researchers, and practitioners working in the areas of signal processing, communications, controls, radar, sonar, and biomedical engineering.
