A Kalman Filter Primer
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A Kalman Filter Primer
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Author : Randall L. Eubank
language : en
Publisher: CRC Press
Release Date : 2005-11-29
A Kalman Filter Primer written by Randall L. Eubank and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-11-29 with Mathematics categories.
System state estimation in the presence of noise is critical for control systems, signal processing, and many other applications in a variety of fields. Developed decades ago, the Kalman filter remains an important, powerful tool for estimating the variables in a system in the presence of noise. However, when inundated with theory and vast notation
An Introduction To Kalman Filtering With Matlab Examples
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Author : Narayan Kovvali
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
An Introduction To Kalman Filtering With Matlab Examples written by Narayan Kovvali and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Technology & Engineering categories.
The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a variety of applications, e.g., target tracking, guidance and navigation, and communications systems. The purpose of this book is to present a brief introduction to Kalman filtering. The theoretical framework of the Kalman filter is first presented, followed by examples showing its use in practical applications. Extensions of the method to nonlinear problems and distributed applications are discussed. A software implementation of the algorithm in the MATLAB programming language is provided, as well as MATLAB code for several example applications discussed in the manuscript.
Primer To Kalman Filtering
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Author : Netzer Moriya
language : en
Publisher:
Release Date : 2011
Primer To Kalman Filtering written by Netzer Moriya and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Kalman filtering categories.
Kalman filtering seems quite simple in concept, requires no command of, or special skills in abstract mathematics, and has been discussed in abundance during the last four decades. Nevertheless, we have often found that its technical complexity, combined with the fact that it is usually presented as an iterative algorithm in a non-analytical manner, makes it sometimes difficult for the inexperienced professionals, to fully understand its essence, benefits and drawbacks. This book focuses on the method of kalman filtering itself and the aspects directly related to it.
Kalman Filter
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Author : Víctor M. Moreno
language : en
Publisher: BoD – Books on Demand
Release Date : 2009-04-01
Kalman Filter written by Víctor M. Moreno and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-01 with Computers categories.
The aim of this book is to provide an overview of recent developments in Kalman filter theory and their applications in engineering and scientific fields. The book is divided into 24 chapters and organized in five blocks corresponding to recent advances in Kalman filtering theory, applications in medical and biological sciences, tracking and positioning systems, electrical engineering and, finally, industrial processes and communication networks.
Primer To Kalman Filtering
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Author : Netser Moriyah
language : en
Publisher:
Release Date : 2010
Primer To Kalman Filtering written by Netser Moriyah and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with MATHEMATICS categories.
State Estimation In Chemometrics
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Author : Pierre C. Thijssen
language : en
Publisher: Woodhead Publishing
Release Date : 2020-08-14
State Estimation In Chemometrics written by Pierre C. Thijssen and has been published by Woodhead Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-14 with Science categories.
This unique text blends together state estimation and chemometrics for the application of advanced data-processing techniques. State Estimation in Chemometrics, second edition describes the basic methods for chemical analysis—the multicomponent, calibration and titration systems—from a new perspective. It succinctly reviews the history of state estimation and chemometrics and provides examples of its many applications, including classical estimation, state estimation, nonlinear estimation, the multicomponent, calibration and titration systems and the Kalman filter. The concepts are introduced in a logical way and built up systematically to appeal to specialist post-graduates working in this area as well as professionals in other areas of chemistry and engineering. This new edition covers the latest research in chemometrics, appealing to readers in bio-engineering, food science, pharmacy, and the life sciences fostering cross-disciplinary research. - Features a new chapter surveying the most up-to-date scientific literature on chemometrics, highlighting developments that have occurred since the first edition published - Includes a new chapter devoted to new applications for state estimation in chemometrics - Covers a new chapter entirely devoted to subspace identification methods - Provides several new real-life examples of methods such as multiple modeling, principal component analysis, iterative target transformation factor analysis, and the generalized standard addition method
Identification Of Dynamic Systems
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Author : Rolf Isermann
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-11-22
Identification Of Dynamic Systems written by Rolf Isermann and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-22 with Technology & Engineering categories.
Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.
High Performance Embedded Computing Handbook
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Author : David R. Martinez
language : en
Publisher: CRC Press
Release Date : 2018-10-03
High Performance Embedded Computing Handbook written by David R. Martinez and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-03 with Technology & Engineering categories.
Over the past several decades, applications permeated by advances in digital signal processing have undergone unprecedented growth in capabilities. The editors and authors of High Performance Embedded Computing Handbook: A Systems Perspective have been significant contributors to this field, and the principles and techniques presented in the handbook are reinforced by examples drawn from their work. The chapters cover system components found in today’s HPEC systems by addressing design trade-offs, implementation options, and techniques of the trade, then solidifying the concepts with specific HPEC system examples. This approach provides a more valuable learning tool, Because readers learn about these subject areas through factual implementation cases drawn from the contributing authors’ own experiences. Discussions include: Key subsystems and components Computational characteristics of high performance embedded algorithms and applications Front-end real-time processor technologies such as analog-to-digital conversion, application-specific integrated circuits, field programmable gate arrays, and intellectual property–based design Programmable HPEC systems technology, including interconnection fabrics, parallel and distributed processing, performance metrics and software architecture, and automatic code parallelization and optimization Examples of complex HPEC systems representative of actual prototype developments Application examples, including radar, communications, electro-optical, and sonar applications The handbook is organized around a canonical framework that helps readers navigate through the chapters, and it concludes with a discussion of future trends in HPEC systems. The material is covered at a level suitable for practicing engineers and HPEC computational practitioners and is easily adaptable to their own implementation requirements.
Bayesian Inference Of State Space Models
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Author : Kostas Triantafyllopoulos
language : en
Publisher: Springer Nature
Release Date : 2021-11-12
Bayesian Inference Of State Space Models written by Kostas Triantafyllopoulos and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-12 with Mathematics categories.
Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models. The celebrated Kalman filter, with its numerous extensions, takes centre stage in the book. Univariate and multivariate models, linear Gaussian, non-linear and non-Gaussian models are discussed with applications to signal processing, environmetrics, economics and systems engineering. Over the past years there has been a growing literature on Bayesian inference of state space models, focusing on multivariate models as well as on non-linear and non-Gaussian models. The availability of time series data in many fields of science and industry on the one hand, and the development of low-cost computational capabilities on the other, have resulted in a wealth of statistical methods aimed at parameter estimation and forecasting. This book brings together many of these methods, presenting an accessible and comprehensive introduction to state space models. A number of data sets from different disciplines are used to illustrate the methods and show how they are applied in practice. The R package BTSA, created for the book, includes many of the algorithms and examples presented. The book is essentially self-contained and includes a chapter summarising the prerequisites in undergraduate linear algebra, probability and statistics. An up-to-date and complete account of state space methods, illustrated by real-life data sets and R code, this textbook will appeal to a wide range of students and scientists, notably in the disciplines of statistics, systems engineering, signal processing, data science, finance and econometrics. With numerous exercises in each chapter, and prerequisite knowledge conveniently recalled, it is suitable for upper undergraduate and graduate courses.
Fundamentals Of Adaptive Filtering
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Author : Ali H. Sayed
language : en
Publisher: John Wiley & Sons
Release Date : 2003-06-13
Fundamentals Of Adaptive Filtering written by Ali H. Sayed and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-06-13 with Science categories.
This book is based on a graduate level course offered by the author at UCLA and has been classed tested there and at other universities over a number of years. This will be the most comprehensive book on the market today providing instructors a wide choice in designing their courses. * Offers computer problems to illustrate real life applications for students and professionals alike * An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.