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Book New Frontiers in Nonlinear Filtering

Download or read book New Frontiers in Nonlinear Filtering written by Richard S. Bucy and published by . This book was released on 1978 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examples of two and three dimensional phase demodulation problems are presented. Computer realizations for the optimal nonlinear phase estimator are discussed in detail, with emphasis on parallel computer architectures. Implementation of the nonlinear filter on various computer architectures, including the CDC6600/7600, CDC STAR-100, Illiac IV, the CRAY-1, and the Floating Point System AP120B is reviewed. Detailed Monte Carlo performance analysis is presented for the two-dimensional system, while partial results are included for the three dimensional case. Implications concerning the ideal computer architecture for nonlinear filter realization are discussed. (Author).

Book New Frontiers in Cryptography

Download or read book New Frontiers in Cryptography written by Khaled Salah Mohamed and published by Springer Nature. This book was released on 2020-10-16 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive coverage of various Cryptography topics, while highlighting the most recent trends such as quantum, blockchain, lightweight, Chaotic and DNA cryptography. Moreover, this book covers cryptography primitives and its usage and applications and focuses on the fundamental principles of modern cryptography such as Stream Ciphers, block ciphers, public key algorithms and digital signatures. Readers will gain a solid foundation in cryptography and security. This book presents the fundamental mathematical concepts of cryptography. Moreover, this book presents hiding data techniques such as steganography and watermarking. The author also provides a comparative study of the different cryptographic methods, which can be used to solve security problems.

Book Nonlinear Filters

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.

Book Nonlinear Filters

    Book Details:
  • Author : Sueo Sugimoto
  • Publisher : Ohmsha, Ltd.
  • Release : 2020-12-10
  • ISBN : 4274805026
  • Pages : 457 pages

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

Book Scientific and Technical Aerospace Reports

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1994 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.

Book Nonlinear Filtering

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.

Book Nonlinear Digital Filtering with Python

Download or read book Nonlinear Digital Filtering with Python written by Ronald K. Pearson and published by CRC Press. This book was released on 2018-09-03 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Digital Filtering with Python: An Introduction discusses important structural filter classes including the median filter and a number of its extensions (e.g., weighted and recursive median filters), and Volterra filters based on polynomial nonlinearities. Adopting both structural and behavioral approaches in characterizing and designing nonlinear digital filters, this book: Begins with an expedient introduction to programming in the free, open-source computing environment of Python Uses results from algebra and the theory of functional equations to construct and characterize behaviorally defined nonlinear filter classes Analyzes the impact of a range of useful interconnection strategies on filter behavior, providing Python implementations of the presented filters and interconnection strategies Proposes practical, bottom-up strategies for designing more complex and capable filters from simpler components in a way that preserves the key properties of these components Illustrates the behavioral consequences of allowing recursive (i.e., feedback) interconnections in nonlinear digital filters while highlighting a challenging but promising research frontier Nonlinear Digital Filtering with Python: An Introduction supplies essential knowledge useful for developing and implementing data cleaning filters for dynamic data analysis and time-series modeling.

Book New Numerical Algorithms for Nonlinear Filtering

Download or read book New Numerical Algorithms for Nonlinear Filtering written by Chin-Pang Alex Fung and published by . This book was released on 1995 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book New Frontiers in Computational Intelligence and Its Applications

Download or read book New Frontiers in Computational Intelligence and Its Applications written by Masoud Mohammadian and published by IOS Press. This book was released on 2000 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence is a broad and active research area that is growing rapidly due to the many successful applications of these new techniques in very diverse problems. Many industries have benefited from adopting this technology. The increased number of patents and diverse range of products developed using computational intelligence methods is evidence of this fact. The goal of this book is to provide highlights of the current research in computational intelligence area. The book consists of research papers in the fields of neural networks, fuzzy logic, evolutionary computing, hybrid evolutionary computing-fuzzy logic systems, hybrid neural networks-evolutionary computing and fuzzy logic systems, image processing and vision, advances in robotics, control and manufacturing, and rough sets.

Book Linear and Nonlinear Filtering for Scientists and Engineers

Download or read book Linear and Nonlinear Filtering for Scientists and Engineers written by Nasir Uddin Ahmed and published by World Scientific. This book was released on 1998 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: "many new results, especially on nonlinear filtering problems and their numerical techniques, are included in book form for the first time it will serve as a useful reference book on the recent progress in this field. The book can be used for teaching graduate courses to students in mathematics, probability, statistics, and engineering. And finally, doctoral students and young researchers in the area of filtering theory and its applications can find inspiring ideas and techniques".Journal of Applied Mathematics and Stochastic Analysis, 2000

Book Nonlinear Filters

Download or read book Nonlinear Filters written by Hisashi Tanizaki and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: For a nonlinear filtering problem, the most heuristic and easiest approximation is to use the Taylor series expansion and apply the conventional linear recursive Kalman filter algorithm directly to the linearized nonlinear measurement and transition equations. First, it is discussed that the Taylor series expansion approach gives us the biased estimators. Next, a Monte-Carlo simulation filter is proposed, where each expectation of the nonlinear functions is evaluated generating random draws. It is shown from Monte-Carlo experiments that the Monte-Carlo simulation filter yields the unbiased but inefficient estimator. Anotherapproach to the nonlinear filtering problem is to approximate the underlyingdensity functions of the state vector. In this monograph, a nonlinear and nonnormal filter is proposed by utilizing Monte-Carlo integration, in which a recursive algorithm of the weighting functions is derived. The densityapproximation approach gives us an asymptotically unbiased estimator. Moreover, in terms of programming and computational time, the nonlinear filter using Monte-Carlo integration can be easily extended to higher dimensional cases, compared with Kitagawa's nonlinear filter using numericalintegration.

Book Fundamentals of Adaptive Signal Processing

Download or read book Fundamentals of Adaptive Signal Processing written by Aurelio Uncini and published by Springer. This book was released on 2014-12-30 with total page 725 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an accessible guide to adaptive signal processing methods that equips the reader with advanced theoretical and practical tools for the study and development of circuit structures and provides robust algorithms relevant to a wide variety of application scenarios. Examples include multimodal and multimedia communications, the biological and biomedical fields, economic models, environmental sciences, acoustics, telecommunications, remote sensing, monitoring and in general, the modeling and prediction of complex physical phenomena. The reader will learn not only how to design and implement the algorithms but also how to evaluate their performance for specific applications utilizing the tools provided. While using a simple mathematical language, the employed approach is very rigorous. The text will be of value both for research purposes and for courses of study.

Book Markov Chain Monte Carlo

Download or read book Markov Chain Monte Carlo written by W. S. Kendall and published by World Scientific. This book was released on 2005 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markov Chain Monte Carlo (MCMC) originated in statistical physics, but has spilled over into various application areas, leading to a corresponding variety of techniques and methods. That variety stimulates new ideas and developments from many different places, and there is much to be gained from cross-fertilization. This book presents five expository essays by leaders in the field, drawing from perspectives in physics, statistics and genetics, and showing how different aspects of MCMC come to the fore in different contexts. The essays derive from tutorial lectures at an interdisciplinary program at the Institute for Mathematical Sciences, Singapore, which exploited the exciting ways in which MCMC spreads across different disciplines.

Book Nonlinear Image Processing

Download or read book Nonlinear Image Processing written by Sanjit Mitra and published by Academic Press. This book was released on 2001 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: This state-of-the-art book deals with the most important aspects of non-linear imaging challenges. The need for engineering and mathematical methods is essential for defining non-linear effects involved in such areas as computer vision, optical imaging, computer pattern recognition, and industrial automation challenges.

Book Performance and Implementation Aspects of Nonlinear Filtering

Download or read book Performance and Implementation Aspects of Nonlinear Filtering written by Gustaf Hendeby and published by Linköping University Electronic Press. This book was released on 2008-02-15 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear filtering is an important standard tool for information and sensor fusion applications, e.g., localization, navigation, and tracking. It is an essential component in surveillance systems and of increasing importance for standard consumer products, such as cellular phones with localization, car navigation systems, and augmented reality. This thesis addresses several issues related to nonlinear filtering, including performance analysis of filtering and detection, algorithm analysis, and various implementation details. The most commonly used measure of filtering performance is the root mean square error (RMSE), which is bounded from below by the Cramér-Rao lower bound (CRLB). This thesis presents a methodology to determine the effect different noise distributions have on the CRLB. This leads up to an analysis of the intrinsic accuracy (IA), the informativeness of a noise distribution. For linear systems the resulting expressions are direct and can be used to determine whether a problem is feasible or not, and to indicate the efficacy of nonlinear methods such as the particle filter (PF). A similar analysis is used for change detection performance analysis, which once again shows the importance of IA. A problem with the RMSE evaluation is that it captures only one aspect of the resulting estimate and the distribution of the estimates can differ substantially. To solve this problem, the Kullback divergence has been evaluated demonstrating the shortcomings of pure RMSE evaluation. Two estimation algorithms have been analyzed in more detail; the Rao-Blackwellized particle filter (RBPF) by some authors referred to as the marginalized particle filter (MPF) and the unscented Kalman filter (UKF). The RBPF analysis leads to a new way of presenting the algorithm, thereby making it easier to implement. In addition the presentation can possibly give new intuition for the RBPF as being a stochastic Kalman filter bank. In the analysis of the UKF the focus is on the unscented transform (UT). The results include several simulation studies and a comparison with the Gauss approximation of the first and second order in the limit case. This thesis presents an implementation of a parallelized PF and outlines an object-oriented framework for filtering. The PF has been implemented on a graphics processing unit (GPU), i.e., a graphics card. The GPU is a inexpensive parallel computational resource available with most modern computers and is rarely used to its full potential. Being able to implement the PF in parallel makes new applications, where speed and good performance are important, possible. The object-oriented filtering framework provides the flexibility and performance needed for large scale Monte Carlo simulations using modern software design methodology. It can also be used to help to efficiently turn a prototype into a finished product.

Book Fundamentals of Nonlinear Digital Filtering

Download or read book Fundamentals of Nonlinear Digital Filtering written by Jaakko Astola and published by CRC Press. This book was released on 2020-09-10 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Nonlinear Digital Filtering is the first book of its kind, presenting and evaluating current methods and applications in nonlinear digital filtering. Written for professors, researchers, and application engineers, as well as for serious students of signal processing, this is the only book available that functions as both a reference handbook and a textbook. Solid introductory material, balanced coverage of theoretical and practical aspects, and dozens of examples provide you with a self-contained, comprehensive information source on nonlinear filtering and its applications.

Book International Trends in Optics

Download or read book International Trends in Optics written by Joseph W. Goodman and published by Academic Press. This book was released on 2012-12-02 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: International Trends in Optics provides a broad view of work in the field of optics throughout the world. Topics range from quantum optoelectronics for optical processing to optics in telecommunications, along with microoptics, optical memories, and fiber-optic signal processing. Holographic optical elements for use with semiconductor lasers are also considered. Comprised of 34 chapters, this book begins with an introduction to some of the practical applications of integrated optical circuits, optoelectronic integrated circuits, and photonic integrated circuits. Subsequent chapters deal with quantum optoelectronics for optical processing; fiber-optic signal processing; holographic optical elements for use with semiconductor lasers; potential uses of photorefractives; and adaptive interferometry that makes use of photorefractive crystals. Water wave optics and diffraction are also examined, together with the essential journals of optics and the opposition effect in volume and surface scattering. The final chapter is devoted to optical computing, with emphasis on its processing functions and architecture. This monograph will be of interest to students, practitioners, and researchers in physics and electronics.