Download or read book Factorization Methods for Discrete Sequential Estimation written by Gerald J. Bierman and published by Courier Corporation. This book was released on 2006-05-26 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: This estimation reference text thoroughly describes matrix factorization methods successfully employed by numerical analysts, familiarizing readers with the techniques that lead to efficient, economical, reliable, and flexible estimation algorithms. Topics include a review of least squares data processing and the Kalman filter algorithm; positive definite matrices, the Cholesky decomposition, and some of their applications; Householder orthogonal transformations; sequential square root data processing; mapping effects and process noise; biases and correlated process noise; and covariance analysis of effects due to mismodeled variables and incorrect filter a priori statistics. The concluding chapters explore SRIF error analysis of effects due to mismodeled variables and incorrect filter a priori statistics as well as square root information smoothing. Geared toward advanced undergraduates and graduate students, this pragmatically oriented and detailed presentation is also a useful reference, featuring numerous helpful appendixes throughout the text.

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 Challenges for Next Generation Network Operations and Service Management written by Yan Ma and published by Springer Science & Business Media. This book was released on 2008-10-06 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th Asia-Pacific Network Operations and Management Symposium, APNOMS 2008, held in Beijing, China, in October 2008. The 43 revised full papers and 34 revised short papers presented were carefully reviewed and selected from 195 submissions. The papers are organized in topical sections on routing and topology management; fault management; community and virtual group management; autonomous and distributed control; sensor network management; traffic identification; QoS management; policy and service management; wireless and mobile network management; security management; short papers.

Download or read book Planetary Spacecraft Navigation written by James Miller and published by Springer. This book was released on 2018-09-03 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook introduces the theories and practical procedures used in planetary spacecraft navigation. Written by a former member of NASA's Jet Propulsion Laboratory (JPL) navigation team, it delves into the mathematics behind modern digital navigation programs, as well as the numerous technological resources used by JPL as a key player in the field. In addition, the text offers an analysis of navigation theory application in recent missions, with the goal of showing students the relationship between navigation theory and the real-world orchestration of mission operations.

Download or read book Flight Mechanics Estimation Theory Symposium 1992 written by and published by . This book was released on 1993 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Automatic Control in Space 1982 written by P. Th. L. M. Van Woerkom and published by Elsevier. This book was released on 2014-05-23 with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic Control in Space 1982 covers the proceedings of the Ninth IFAC/ESA Symposium. Comprised of 62 chapters, this book covers issues relevant in aerospace, such as engineering, hardware, operations, and theories. This book discusses several topics that concern space explorations, such as L-SAT attitude and orbit control system; methods of dynamic flight control; methods of satellite attitude control using a bias-momentum; and ion sensor signal fluctuations. This text will be of great interest to engineers, researchers, and professionals whose work is in line with aerospace.

Download or read book Data Assimilation for the Earth System written by Richard Swinbank and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data assimilation is the combination of information from observations and models of a particular physical system in order to get the best possible estimate of the state of that system. The technique has wide applications across a range of earth sciences, a major application being the production of operational weather forecasts. Others include oceanography, atmospheric chemistry, climate studies, and hydrology. Data Assimilation for the Earth System is a comprehensive survey of both the theory of data assimilation and its application in a range of earth system sciences. Data assimilation is a key technique in the analysis of remote sensing observations and is thus particularly useful for those analysing the wealth of measurements from recent research satellites. This book is suitable for postgraduate students and those working on the application of data assimilation in meteorology, oceanography and other earth sciences.

Download or read book Machine Learning written by Sergios Theodoridis and published by Academic Press. This book was released on 2020-02-19 with total page 1162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning: A Bayesian and Optimization Perspective, 2nd edition, gives a unified perspective on machine learning by covering both pillars of supervised learning, namely regression and classification. The book starts with the basics, including mean square, least squares and maximum likelihood methods, ridge regression, Bayesian decision theory classification, logistic regression, and decision trees. It then progresses to more recent techniques, covering sparse modelling methods, learning in reproducing kernel Hilbert spaces and support vector machines, Bayesian inference with a focus on the EM algorithm and its approximate inference variational versions, Monte Carlo methods, probabilistic graphical models focusing on Bayesian networks, hidden Markov models and particle filtering. Dimensionality reduction and latent variables modelling are also considered in depth. This palette of techniques concludes with an extended chapter on neural networks and deep learning architectures. The book also covers the fundamentals of statistical parameter estimation, Wiener and Kalman filtering, convexity and convex optimization, including a chapter on stochastic approximation and the gradient descent family of algorithms, presenting related online learning techniques as well as concepts and algorithmic versions for distributed optimization. Focusing on the physical reasoning behind the mathematics, without sacrificing rigor, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. Most of the chapters include typical case studies and computer exercises, both in MATLAB and Python. The chapters are written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as courses on sparse modeling, deep learning, and probabilistic graphical models. New to this edition: - Complete re-write of the chapter on Neural Networks and Deep Learning to reflect the latest advances since the 1st edition. The chapter, starting from the basic perceptron and feed-forward neural networks concepts, now presents an in depth treatment of deep networks, including recent optimization algorithms, batch normalization, regularization techniques such as the dropout method, convolutional neural networks, recurrent neural networks, attention mechanisms, adversarial examples and training, capsule networks and generative architectures, such as restricted Boltzman machines (RBMs), variational autoencoders and generative adversarial networks (GANs). - Expanded treatment of Bayesian learning to include nonparametric Bayesian methods, with a focus on the Chinese restaurant and the Indian buffet processes. - Presents the physical reasoning, mathematical modeling and algorithmic implementation of each method - Updates on the latest trends, including sparsity, convex analysis and optimization, online distributed algorithms, learning in RKH spaces, Bayesian inference, graphical and hidden Markov models, particle filtering, deep learning, dictionary learning and latent variables modeling - Provides case studies on a variety of topics, including protein folding prediction, optical character recognition, text authorship identification, fMRI data analysis, change point detection, hyperspectral image unmixing, target localization, and more

Download or read book Technical Abstract Bulletin written by and published by . This book was released on 1980 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modelling and Parameter Estimation of Dynamic Systems written by J.R. Raol and published by IET. This book was released on 2004-08-13 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a detailed examination of the estimation techniques and modeling problems. The theory is furnished with several illustrations and computer programs to promote better understanding of system modeling and parameter estimation.

Download or read book Flight Mechanics Modeling and Analysis written by Jitendra R. Raol and published by CRC Press. This book was released on 2023-03-31 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: Flight Mechanics Modeling and Analysis comprehensively covers flight mechanics and flight dynamics using a systems approach. This book focuses on applied mathematics and control theory in its discussion of flight mechanics to build a strong foundation for solving design and control problems in the areas of flight simulation and flight data analysis. The second edition has been expanded to include two new chapters and coverage of aeroservoelastic topics and engineering mechanics, presenting more concepts of flight control and aircraft parameter estimation. This book is intended for senior undergraduate aerospace students taking Aircraft Mechanics, Flight Dynamics & Controls, and Flight Mechanics courses. It will also be of interest to research students and R&D project-scientists of the same disciplines. Including end-of-chapter exercises and illustrative examples with a MATLAB®-based approach, this book also includes a Solutions Manual and Figure Slides for adopting instructors. Features: • Covers flight mechanics, flight simulation, flight testing, flight control, and aeroservoelasticity. • Features artificial neural network- and fuzzy logic-based aspects in modeling and analysis of flight mechanics systems: aircraft parameter estimation and reconfiguration of control. • Focuses on a systems-based approach. • Includes two new chapters, numerical simulation examples with MATLAB®-based implementations, and end-of-chapter exercises. • Includes a Solutions Manual and Figure Slides for adopting instructors.

Download or read book Modern Signal Processing written by Thomas Kailath and published by CRC Press. This book was released on 1986-08 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bayesian Filtering and Smoothing written by Simo Särkkä and published by Cambridge University Press. This book was released on 2023-05-31 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.

Download or read book Adaptive Control written by Ioan Doré Landau and published by Springer Science & Business Media. This book was released on 2011-06-06 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the application of the ideas presented. The second edition is thoroughly revised to throw light on recent developments in theory and applications with new chapters on: multimodel adaptive control with switching, direct and indirect adaptive regulation and adaptive feedforward disturbance compensation. Many algorithms are newly presented in MATLAB® m-file format to facilitate their employment in real systems. Classroom-tested slides for instructors to use in teaching this material are also now provided. All of this supplementary electronic material can be downloaded from fill in URL. The core material is also up-dated and re-edited to keep its perspective in line with modern ideas and more closely to associate algorithms with their applications giving the reader a solid grounding in: synthesis and analysis of parameter adaptation algorithms, recursive plant model identification in open and closed loop, robust digital control for adaptive control; • robust parameter adaptation algorithms, practical considerations and applications, including flexible transmission systems, active vibration control and broadband disturbance rejection and a supplementary introduction on hot dip galvanizing and a phosphate drying furnace. Control researchers and applied mathematicians will find Adaptive Control of significant and enduring interest and its use of example and application will appeal to practitioners working with unknown- and variable-parameter plant. Praise for the first edition: ...well written, interesting and easy to follow, so that it constitutes a valuable addition to the monographies in adaptive control for discrete-time linear systems... suitable (at least in part) for use in graduate courses in adaptive control.

Download or read book Lectures on Wiener and Kalman Filtering written by T. Kailath and published by Springer. This book was released on 2014-05-04 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 250 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.

Download or read book Identification of Dynamic Systems written by Rolf Isermann and published by Springer Science & Business Media. This book was released on 2010-11-22 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.