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Author : M. Sami Fadali
Publisher : Springer Nature
ISBN 13 : 9819980631
Total Pages : 489 pages
Book Rating : 4.8/5 (199 download)
Download or read book Introduction to Random Signals, Estimation Theory, and Kalman Filtering written by M. Sami Fadali and published by Springer Nature. This book was released on with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Robert Grover Brown
Publisher : Wiley-Liss
ISBN 13 :
Total Pages : 504 pages
Book Rating : 4.3/5 (91 download)
Download or read book Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises and Solutions written by Robert Grover Brown and published by Wiley-Liss. This book was released on 1997 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this updated edition the main thrust is on applied Kalman filtering. Chapters 1-3 provide a minimal background in random process theory and the response of linear systems to random inputs. The following chapter is devoted to Wiener filtering and the remainder of the text deals with various facets of Kalman filtering with emphasis on applications. Starred problems at the end of each chapter are computer exercises. The authors believe that programming the equations and analyzing the results of specific examples is the best way to obtain the insight that is essential in engineering work.
Author : Jerry M. Mendel
Publisher : Pearson Education
ISBN 13 : 0132440792
Total Pages : 891 pages
Book Rating : 4.1/5 (324 download)
Download or read book Lessons in Estimation Theory for Signal Processing, Communications, and Control written by Jerry M. Mendel and published by Pearson Education. This book was released on 1995-03-14 with total page 891 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimation theory is a product of need and technology. As a result, it is an integral part of many branches of science and engineering. To help readers differentiate among the rich collection of estimation methods and algorithms, this book describes in detail many of the important estimation methods and shows how they are interrelated. Written as a collection of lessons, this book introduces readers o the general field of estimation theory and includes abundant supplementary material.
Author : Mohinder S. Grewal
Publisher : John Wiley & Sons
ISBN 13 : 111898496X
Total Pages : 639 pages
Book Rating : 4.1/5 (189 download)
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 639 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.
Author : Robert Grover Brown
Publisher : Wiley-Liss
ISBN 13 :
Total Pages : 504 pages
Book Rating : 4.3/5 (91 download)
Download or read book Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises and Solutions written by Robert Grover Brown and published by Wiley-Liss. This book was released on 1997 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this updated edition the main thrust is on applied Kalman filtering. Chapters 1-3 provide a minimal background in random process theory and the response of linear systems to random inputs. The following chapter is devoted to Wiener filtering and the remainder of the text deals with various facets of Kalman filtering with emphasis on applications. Starred problems at the end of each chapter are computer exercises. The authors believe that programming the equations and analyzing the results of specific examples is the best way to obtain the insight that is essential in engineering work.
Author : Averil Burton Chatfield
Publisher : AIAA
ISBN 13 : 9781600864278
Total Pages : 368 pages
Book Rating : 4.8/5 (642 download)
Download or read book Fundamentals of High Accuracy Inertial Navigation written by Averil Burton Chatfield and published by AIAA. This book was released on 1997 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Yaakov Bar-Shalom
Publisher : John Wiley & Sons
ISBN 13 : 0471465216
Total Pages : 583 pages
Book Rating : 4.4/5 (714 download)
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.
Author : Lonnie C. Ludeman
Publisher :
ISBN 13 : 9788126527236
Total Pages : 628 pages
Book Rating : 4.5/5 (272 download)
Download or read book RANDOM PROCESSES: FILTERING, ESTIMATION AND DETECTION written by Lonnie C. Ludeman and published by . This book was released on 2010-07-01 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: Market_Desc: Graduate students of electrical and computer engineering. Practicing engineers in communications and signal processing. Special Features: " Covers modern detection and estimation theory as well as the basics of random processes" Emphasizes the use of discrete-time Weiner and Kalman filters and covers nonlinear systems in detail" Includes over 380 class-tested homework exercises About The Book: An understanding of random processes is crucial in the study of many engineering systems, for example analyzing noise in a wireless communications channel. This book covers the basics of probability and random processes for an engineering audience. Importantly, though, the book also presents the details of modern detection and estimation theory, giving it a real edge over existing textbooks. The author has a proven track record. His book Fundamentals of Digital Signal Processing has sold 15,000 copies and won Choice magazine's Outstanding Engineering Book of the Year award.
Author : The Analytic Sciences Corporation
Publisher : MIT Press
ISBN 13 : 9780262570480
Total Pages : 388 pages
Book Rating : 4.5/5 (74 download)
Download or read book Applied Optimal Estimation written by The Analytic Sciences Corporation and published by MIT Press. This book was released on 1974-05-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book on the optimal estimation that places its major emphasis on practical applications, treating the subject more from an engineering than a mathematical orientation. Even so, theoretical and mathematical concepts are introduced and developed sufficiently to make the book a self-contained source of instruction for readers without prior knowledge of the basic principles of the field. The work is the product of the technical staff of The Analytic Sciences Corporation (TASC), an organization whose success has resulted largely from its applications of optimal estimation techniques to a wide variety of real situations involving large-scale systems. Arthur Gelb writes in the Foreword that "It is our intent throughout to provide a simple and interesting picture of the central issues underlying modern estimation theory and practice. Heuristic, rather than theoretically elegant, arguments are used extensively, with emphasis on physical insights and key questions of practical importance." Numerous illustrative examples, many based on actual applications, have been interspersed throughout the text to lead the student to a concrete understanding of the theoretical material. The inclusion of problems with "built-in" answers at the end of each of the nine chapters further enhances the self-study potential of the text. After a brief historical prelude, the book introduces the mathematics underlying random process theory and state-space characterization of linear dynamic systems. The theory and practice of optimal estimation is them presented, including filtering, smoothing, and prediction. Both linear and non-linear systems, and continuous- and discrete-time cases, are covered in considerable detail. New results are described concerning the application of covariance analysis to non-linear systems and the connection between observers and optimal estimators. The final chapters treat such practical and often pivotal issues as suboptimal structure, and computer loading considerations. This book is an outgrowth of a course given by TASC at a number of US Government facilities. Virtually all of the members of the TASC technical staff have, at one time and in one way or another, contributed to the material contained in the work.
Author : John J. Shynk
Publisher : John Wiley & Sons
ISBN 13 : 1118393953
Total Pages : 850 pages
Book Rating : 4.1/5 (183 download)
Download or read book Probability, Random Variables, and Random Processes written by John J. Shynk and published by John Wiley & Sons. This book was released on 2012-10-15 with total page 850 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability, Random Variables, and Random Processes is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some familiarity with probability and random variables, though not necessarily of random processes and systems that operate on random signals. It is also appropriate for advanced undergraduate students who have a strong mathematical background. The book has the following features: Several appendices include related material on integration, important inequalities and identities, frequency-domain transforms, and linear algebra. These topics have been included so that the book is relatively self-contained. One appendix contains an extensive summary of 33 random variables and their properties such as moments, characteristic functions, and entropy. Unlike most books on probability, numerous figures have been included to clarify and expand upon important points. Over 600 illustrations and MATLAB plots have been designed to reinforce the material and illustrate the various characterizations and properties of random quantities. Sufficient statistics are covered in detail, as is their connection to parameter estimation techniques. These include classical Bayesian estimation and several optimality criteria: mean-square error, mean-absolute error, maximum likelihood, method of moments, and least squares. The last four chapters provide an introduction to several topics usually studied in subsequent engineering courses: communication systems and information theory; optimal filtering (Wiener and Kalman); adaptive filtering (FIR and IIR); and antenna beamforming, channel equalization, and direction finding. This material is available electronically at the companion website. Probability, Random Variables, and Random Processes is the only textbook on probability for engineers that includes relevant background material, provides extensive summaries of key results, and extends various statistical techniques to a range of applications in signal processing.
Author : Dwight F. Mix
Publisher : Macmillan College
ISBN 13 :
Total Pages : 472 pages
Book Rating : 4.3/5 (91 download)
Download or read book Random Signal Processing written by Dwight F. Mix and published by Macmillan College. This book was released on 1995 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing detailed coverage of Wiener filtering and Kalman filtering, this book presents a coherent treatment of estimation theory and an in-depth look at detection theory for communication and pattern recognition.
Author : Brian D. O. Anderson
Publisher : Courier Corporation
ISBN 13 : 0486136892
Total Pages : 370 pages
Book Rating : 4.4/5 (861 download)
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.
Author : Dan Simon
Publisher : John Wiley & Sons
ISBN 13 : 0470045337
Total Pages : 554 pages
Book Rating : 4.4/5 (7 download)
Download or read book Optimal State Estimation written by Dan Simon and published by John Wiley & Sons. This book was released on 2006-06-19 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering. While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning: * Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimation * Simple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practice * MATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering. Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries.
Author : Steven M. Kay
Publisher : Pearson Education
ISBN 13 : 013280803X
Total Pages : 496 pages
Book Rating : 4.1/5 (328 download)
Download or read book Fundamentals of Statistical Signal Processing written by Steven M. Kay and published by Pearson Education. This book was released on 2013 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: "For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for obtaining an optimal estimator and analyzing its performance. Author Steven M. Kay discusses classical estimation followed by Bayesian estimation, and illustrates the theory with numerous pedagogical and real-world examples."--Cover, volume 1.
Author : Osvaldo Gervasi
Publisher : Springer
ISBN 13 : 3319951653
Total Pages : 804 pages
Book Rating : 4.3/5 (199 download)
Download or read book Computational Science and Its Applications – ICCSA 2018 written by Osvaldo Gervasi and published by Springer. This book was released on 2018-07-03 with total page 804 pages. Available in PDF, EPUB and Kindle. Book excerpt: The five volume set LNCS 10960 until 10964 constitutes the refereed proceedings of the 18th International Conference on Computational Science and Its Applications, ICCSA 2018, held in Melbourne, Australia, in July 2018. Apart from the general tracks, ICCSA 2018 also includes 34 international workshops in various areas of computational sciences, ranging from computational science technologies, to specific areas of computational sciences, such as computer graphics and virtual reality. The total of 265 full papers and 10 short papers presented in the 5-volume proceedings set of ICCSA 2018, were carefully reviewed and selected from 892 submissions.
Author : James V. Candy
Publisher : John Wiley & Sons
ISBN 13 : 1118210549
Total Pages : 404 pages
Book Rating : 4.1/5 (182 download)
Download or read book Bayesian Signal Processing written by James V. Candy and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: New Bayesian approach helps you solve tough problems in signal processing with ease Signal processing is based on this fundamental concept—the extraction of critical information from noisy, uncertain data. Most techniques rely on underlying Gaussian assumptions for a solution, but what happens when these assumptions are erroneous? Bayesian techniques circumvent this limitation by offering a completely different approach that can easily incorporate non-Gaussian and nonlinear processes along with all of the usual methods currently available. This text enables readers to fully exploit the many advantages of the "Bayesian approach" to model-based signal processing. It clearly demonstrates the features of this powerful approach compared to the pure statistical methods found in other texts. Readers will discover how easily and effectively the Bayesian approach, coupled with the hierarchy of physics-based models developed throughout, can be applied to signal processing problems that previously seemed unsolvable. Bayesian Signal Processing features the latest generation of processors (particle filters) that have been enabled by the advent of high-speed/high-throughput computers. The Bayesian approach is uniformly developed in this book's algorithms, examples, applications, and case studies. Throughout this book, the emphasis is on nonlinear/non-Gaussian problems; however, some classical techniques (e.g. Kalman filters, unscented Kalman filters, Gaussian sums, grid-based filters, et al) are included to enable readers familiar with those methods to draw parallels between the two approaches. Special features include: Unified Bayesian treatment starting from the basics (Bayes's rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation techniques (sequential Monte Carlo sampling) Incorporates "classical" Kalman filtering for linear, linearized, and nonlinear systems; "modern" unscented Kalman filters; and the "next-generation" Bayesian particle filters Examples illustrate how theory can be applied directly to a variety of processing problems Case studies demonstrate how the Bayesian approach solves real-world problems in practice MATLAB notes at the end of each chapter help readers solve complex problems using readily available software commands and point out software packages available Problem sets test readers' knowledge and help them put their new skills into practice The basic Bayesian approach is emphasized throughout this text in order to enable the processor to rethink the approach to formulating and solving signal processing problems from the Bayesian perspective. This text brings readers from the classical methods of model-based signal processing to the next generation of processors that will clearly dominate the future of signal processing for years to come. With its many illustrations demonstrating the applicability of the Bayesian approach to real-world problems in signal processing, this text is essential for all students, scientists, and engineers who investigate and apply signal processing to their everyday problems.
Author : Robert Grover Brown
Publisher :
ISBN 13 :
Total Pages : 522 pages
Book Rating : 4.3/5 (91 download)
Download or read book Introduction to Random Signals and Applied Kalman Filtering written by Robert Grover Brown and published by . This book was released on 1992 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on applied Kalman filtering and its random signal analysis. Important to all control system and communication engineers, it emphasizes applications, computer software and associated sets of special computer problems to aid in tying together both theory and practice. Along with actual case studies, a diskette is included to enable readers to actually see how Kalman filtering works.
