Download or read book Advanced Kalman Filtering Least Squares and Modeling written by Bruce P. Gibbs and published by John Wiley & Sons. This book was released on 2011-03-29 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended primarily as a handbook for engineers who must design practical systems. Its primary goal is to discuss model development in sufficient detail so that the reader may design an estimator that meets all application requirements and is robust to modeling assumptions. Since it is sometimes difficult to a priori determine the best model structure, use of exploratory data analysis to define model structure is discussed. Methods for deciding on the “best” model are also presented. A second goal is to present little known extensions of least squares estimation or Kalman filtering that provide guidance on model structure and parameters, or make the estimator more robust to changes in real-world behavior. A third goal is discussion of implementation issues that make the estimator more accurate or efficient, or that make it flexible so that model alternatives can be easily compared. The fourth goal is to provide the designer/analyst with guidance in evaluating estimator performance and in determining/correcting problems. The final goal is to provide a subroutine library that simplifies implementation, and flexible general purpose high-level drivers that allow both easy analysis of alternative models and access to extensions of the basic filtering. Supplemental materials and up-to-date errata are downloadable at http://booksupport.wiley.com.
Download or read book The Kalman Filter in Finance written by C. Wells and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: A non-technical introduction to the question of modeling with time-varying parameters, using the beta coefficient from Financial Economics as the main example. After a brief introduction to this coefficient for those not versed in finance, the book presents a number of rather well known tests for constant coefficients and then performs these tests on data from the Stockholm Exchange. The Kalman filter is then introduced and a simple example is used to demonstrate the power of the filter. The filter is then used to estimate the market model with time-varying betas. The book concludes with further examples of how the Kalman filter may be used in estimation models used in analyzing other aspects of finance. Since both the programs and the data used in the book are available for downloading, the book is especially valuable for students and other researchers interested in learning the art of modeling with time varying coefficients.
Download or read book Restricted Kalman Filtering written by Adrian Pizzinga and published by Springer Science & Business Media. This book was released on 2012-07-25 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: In statistics, the Kalman filter is a mathematical method whose purpose is to use a series of measurements observed over time, containing random variations and other inaccuracies, and produce estimates that tend to be closer to the true unknown values than those that would be based on a single measurement alone. This Brief offers developments on Kalman filtering subject to general linear constraints. There are essentially three types of contributions: new proofs for results already established; new results within the subject; and applications in investment analysis and macroeconomics, where the proposed methods are illustrated and evaluated. The Brief has a short chapter on linear state space models and the Kalman filter, aiming to make the book self-contained and to give a quick reference to the reader (notation and terminology). The prerequisites would be a contact with time series analysis in the level of Hamilton (1994) or Brockwell & Davis (2002) and also with linear state models and the Kalman filter – each of these books has a chapter entirely dedicated to the subject. The book is intended for graduate students, researchers and practitioners in statistics (specifically: time series analysis and econometrics).
Download or read book Kalman Filtering written by Mohinder S. Grewal and published by John Wiley & Sons. This book was released on 2015-02-02 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: The definitive textbook and professional reference on Kalman Filtering – fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.
Download or read book Estimation with Applications to Tracking and Navigation written by Yaakov Bar-Shalom and published by John Wiley & Sons. This book was released on 2004-04-05 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expert coverage of the design and implementation of state estimation algorithms for tracking and navigation Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics. The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems. Other features include: * Problems that apply theoretical material to real-world applications * In-depth coverage of the Interacting Multiple Model (IMM) estimator * Companion DynaEst(TM) software for MATLAB(TM) implementation of Kalman filters and IMM estimators * Design guidelines for tracking filters Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area.
Download or read book Introduction and Implementations of the Kalman Filter written by Felix Govaers and published by BoD – Books on Demand. This book was released on 2019-05-22 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some "awareness" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not.
Download or read book Kalman Filters written by Ginalber Luiz Serra and published by BoD – Books on Demand. This book was released on 2018-02-21 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent issues on theory and practice of Kalman filters, with a comprehensive treatment of a selected number of concepts, techniques, and advanced applications. From an interdisciplinary point of view, the contents from each chapter bring together an international scientific community to discuss the state of the art on Kalman filter-based methodologies for adaptive/distributed filtering, optimal estimation, dynamic prediction, nonstationarity, robot navigation, global navigation satellite systems, moving object tracking, optical communication systems, and active power filters, among others. The theoretical and methodological foundations combined with extensive experimental explanation make this book a reference suitable for students, practicing engineers, and researchers in sciences and engineering.
Download or read book Fundamentals of Kalman Filtering written by Paul Zarchan and published by AIAA (American Institute of Aeronautics & Astronautics). This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical basics -- Method of least squares -- Recursive least-squares filtering -- Polynomial Kalman filters -- Kalman filters in a nonpolynomial world -- Continuous polynomial Kalman filter -- Extended Kalman filtering -- Drag and falling object -- Cannon-launched projectile tracking problem -- Tracking a sine wave -- Satellite navigation -- Biases -- Linearized Kalman filtering -- Miscellaneous topics -- Fading-memory filter -- Assorted techniques for improving Kalman-filter performance -- Fixed-memory filters -- Chain-rule and least-squares filtering -- Filter bank approach to tracking a sine wave -- Appendix A: Fundamentals of Kalman-filtering software -- Appendix B: Key formula and concept summary
Download or read book Tracking and Kalman Filtering Made Easy written by Eli Brookner and published by Wiley-Interscience. This book was released on 1998 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: TRACKING, PREDICTION, AND SMOOTHING BASICS. g and g-h-k Filters. Kalman Filter. Practical Issues for Radar Tracking. LEAST-SQUARES FILTERING, VOLTAGE PROCESSING, ADAPTIVE ARRAY PROCESSING, AND EXTENDED KALMAN FILTER. Least-Squares and Minimum-Variance Estimates for Linear Time-Invariant Systems. Fixed-Memory Polynomial Filter. Expanding- Memory (Growing-Memory) Polynomial Filters. Fading-Memory (Discounted Least-Squares) Filter. General Form for Linear Time-Invariant System. General Recursive Minimum-Variance Growing-Memory Filter (Bayes and Kalman Filters without Target Process Noise). Voltage Least-Squares Algorithms Revisited. Givens Orthonormal Transformation. Householder Orthonormal Transformation. Gram--Schmidt Orthonormal Transformation. More on Voltage-Processing Techniques. Linear Time-Variant System. Nonlinear Observation Scheme and Dynamic Model (Extended Kalman Filter). Bayes Algorithm with Iterative Differential Correction for Nonlinear Systems. Kalman Filter Revisited. Appendix. Problems. Symbols and Acronyms. Solution to Selected Problems. References. Index.
Download or read book Optimal Filtering written by Brian D. O. Anderson and published by Courier Corporation. This book was released on 2012-05-23 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graduate-level text extends studies of signal processing, particularly regarding communication systems and digital filtering theory. Topics include filtering, linear systems, and estimation; discrete-time Kalman filter; time-invariant filters; more. 1979 edition.
Download or read book Advanced Technologies Systems and Applications VII written by Naida Ademović and published by Springer Nature. This book was released on 2022-10-15 with total page 789 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of articles on the advanced and interdisciplinary application of innovative technologies. Scientific investigations and results of the conference 13th Days of Bosnian-Herzegovinian American Academy of Art and Sciences held in Sarajevo, Bosnia and Herzegovina, June 23-26, 2022, are presented in this book. The up-to-date advances in various fields of engineering have been presented through numerous papers spanning the disciplines of civil engineering, mechanical engineering, advanced electrical power systems, computer modeling and simulations for engineering applications, computer science and artificial intelligence, geodesy and geoinformation, data science and geographic information systems and information and communication technologies. The editors would like to extend special gratitude to all the chairs of the planned symposia of the 13th Days of BHAAAS for their dedicated work in the production of this book.
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.
Download or read book Next Generation Arithmetic written by John Gustafson and published by Springer Nature. This book was released on 2023-05-11 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Conference on Next Generation Arithmetic, CoNGA 2023, held in Singapore, during March 1-2, 2023. The 11 full papers in this book were carefully reviewed and selected from 16 submissions. They were organized in topical sections as follows: Lossless FFTs Using Posit Arithmetic, PLAUs: Posit Logarithmic Approximate Units to Implement Low-Cost Operations with Real Numbers.
Download or read book Probabilistic Machine Learning for Civil Engineers written by James-A. Goulet and published by MIT Press. This book was released on 2020-03-16 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step examples, illustrations, and exercises. This book introduces probabilistic machine learning concepts to civil engineering students and professionals, presenting key approaches and techniques in a way that is accessible to readers without a specialized background in statistics or computer science. It presents different methods clearly and directly, through step-by-step examples, illustrations, and exercises. Having mastered the material, readers will be able to understand the more advanced machine learning literature from which this book draws. The book presents key approaches in the three subfields of probabilistic machine learning: supervised learning, unsupervised learning, and reinforcement learning. It first covers the background knowledge required to understand machine learning, including linear algebra and probability theory. It goes on to present Bayesian estimation, which is behind the formulation of both supervised and unsupervised learning methods, and Markov chain Monte Carlo methods, which enable Bayesian estimation in certain complex cases. The book then covers approaches associated with supervised learning, including regression methods and classification methods, and notions associated with unsupervised learning, including clustering, dimensionality reduction, Bayesian networks, state-space models, and model calibration. Finally, the book introduces fundamental concepts of rational decisions in uncertain contexts and rational decision-making in uncertain and sequential contexts. Building on this, the book describes the basics of reinforcement learning, whereby a virtual agent learns how to make optimal decisions through trial and error while interacting with its environment.
Download or read book Principles of Data Assimilation written by Seon Ki Park and published by Cambridge University Press. This book was released on 2022-09-29 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data assimilation is theoretically founded on probability, statistics, control theory, information theory, linear algebra, and functional analysis. At the same time, data assimilation is a very practical subject, given its goal of estimating the posterior probability density function in realistic high-dimensional applications. This puts data assimilation at the intersection between the contrasting requirements of theory and practice. Based on over twenty years of teaching courses in data assimilation, Principles of Data Assimilation introduces a unique perspective that is firmly based on mathematical theories, but also acknowledges practical limitations of the theory. With the inclusion of numerous examples and practical case studies throughout, this new perspective will help students and researchers to competently interpret data assimilation results and to identify critical challenges of developing data assimilation algorithms. The benefit of information theory also introduces new pathways for further development, understanding, and improvement of data assimilation methods.
Download or read book Linear Estimation written by Thomas Kailath and published by Pearson. This book was released on 2000 with total page 888 pages. Available in PDF, EPUB and Kindle. Book excerpt: This original work offers the most comprehensive and up-to-date treatment of the important subject of optimal linear estimation, which is encountered in many areas of engineering such as communications, control, and signal processing, and also in several other fields, e.g., econometrics and statistics. The book not only highlights the most significant contributions to this field during the 20th century, including the works of Wiener and Kalman, but it does so in an original and novel manner that paves the way for further developments. This book contains a large collection of problems that complement it and are an important part of piece, in addition to numerous sections that offer interesting historical accounts and insights. The book also includes several results that appear in print for the first time. FEATURES/BENEFITS Takes a geometric point of view. Emphasis on the numerically favored array forms of many algorithms. Emphasis on equivalence and duality concepts for the solution of several related problems in adaptive filtering, estimation, and control. These features are generally absent in most prior treatments, ostensibly on the grounds that they are too abstract and complicated. It is the authors' hope that these misconceptions will be dispelled by the presentation herein, and that the fundamental simplicity and power of these ideas will be more widely recognized and exploited. Among other things, these features already yielded new insights and new results for linear and nonlinear problems in areas such as adaptive filtering, quadratic control, and estimation, including the recent Hà theories.
Download or read book Interaction Design for 3D User Interfaces written by Francisco R. Ortega and published by CRC Press. This book was released on 2016-01-06 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the new interaction modalities that are becoming possible with new devices by looking at user interfaces from an input perspective. It deals with modern input devices and user interaction and design covering in-depth theory, advanced topics for noise reduction using Kalman Filters, a case study, and multiple chapters showing hands-on approaches to relevant technology, including modern devices such as the Leap-Motion, Xbox One Kinect, inertial measurement units, and multi-touch technology. It also discusses theories behind interaction and navigation, past and current techniques, and practical topics about input devices.
