optimal filtering (175 Ergebnisse)

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Hard Cover. Zustand: Good. First Hardback Edition. 240 x 160mm. pp. 309. English text. First hardback edition of 'Polynomial Methods in Optimal Control and Filtering'. Bound in original light blue boards. No dust jacket [as published]. Library marks to endpages and base of spine. Light wave to pages and some light wear to boards. Binding strong. No underlining. Ex-Library.

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this volume the investigations of filtering problems, a start on which has been made in [55], are being continued and are devoted to theoretical problems of processing stochastic fields. The derivation of the theory of processing stochastic fields is similar to that of the theory extensively developed for stochastic processes ('stochastic fields with a one-dimensional domain'). Nevertheless there exist essential distinctions between these cases making a construction of the theory for the multi-dimensional case in such a way difficult. Among these are the absence of the notion of the 'past-future' in the case of fields, which plays a fundamental role in constructing stochastic processes theory. So attempts to introduce naturally the notion of the causality (non-anticipativity) when synthesising stable filters designed for processing fields have not met with success. Mathematically, principal distinctions between multi-dimensional and one-dimensional cases imply that the set of roots of a multi-variable polyno mial does not necessary consist of a finite number of isolated points. From the main theorem of algebra it follows that in the one-dimensional case every poly nomial of degree n has just n roots (considering their multiplicity) in the com plex plane. As a consequence, in particular, an arbitrary rational function Ct. (.

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book offers an analytical rather than measure-theoretical approach to the derivation of the partial differential equations of nonlinear filtering theory. The basis for this approach is the discrete numerical scheme used in Monte-Carlo simulations of stochastic differential equations and Wiener's associated path integral representation of the transition probability density. Furthermore, it presents analytical methods for constructing asymptotic approximations to their solution and for synthesizing asymptotically optimal filters. It also offers a new approach to the phase tracking problem, based on optimizing the mean time to loss of lock. The book is based on lecture notes from a one-semester special topics course on stochastic processes and their applications that the author taught many times to graduate students of mathematics, applied mathematics, physics, chemistry, computer science, electrical engineering, and other disciplines. The book contains exercises and worked-out examples aimed at illustrating the methods of mathematical modeling and performance analysis of phase trackers.

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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book offers an analytical rather than measure-theoretical approach to the derivation of the partial differential equations of nonlinear filtering theory. The basis for this approach is the discrete numerical scheme used in Monte-Carlo simulations of stochastic differential equations and Wiener's associated path integral representation of the transition probability density. Furthermore, it presents analytical methods for constructing asymptotic approximations to their solution and for synthesizing asymptotically optimal filters. It also offers a new approach to the phase tracking problem, based on optimizing the mean time to loss of lock. The book is based on lecture notes from a one-semester special topics course on stochastic processes and their applications that the author taught many times to graduate students of mathematics, applied mathematics, physics, chemistry, computer science, electrical engineering, and other disciplines. The book contains exercises and worked-out examples aimed at illustrating the methods of mathematical modeling and performance analysis of phase trackers.

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - InhaltsangabeExistence, uniqueness and tail behavior of solutions to Zakai equations with unbounded coefficients.- Optimal stopping under partial observations.- Optimal control of partially observed diffusions.- Accurate evaluation of conditional densities in nonlinear filtering.- An efficient approximation scheme for a class of stochastic differential equations.- Stochastic control with noisy observations.- Applications of duality to measure-valued diffusion processes.- Optimal stopping of controlled Markov processes.- Two parameter filtering equations for jump process semimartingales.- Space-time mixing in a branching model.- Logarithmic transformations and stochastic control.- Generalized Gaussian random solutions of certain evolution equations.- Extremal controls for completely observable diffusions.- Lévy's stochastic area formula in higher dimensions.- Asymptotic nonlinear filtering and large deviations.- Representation and approximation of counting processes.- Approximate invariant measures for the asymptotic distributions of differential equations with wide band noise inputs.- Optimal stochastic control of diffusion type processes and Hamilton-Jacobi-Bellman equations.- On reducing the dimension of control problems by diffusion approximation.- Lie algebraic and approximation methods for some nonlinear filtering problems.- Optimal stopping for two-parameter processes.- Stochastic control problem for reflected diffusions in a convex bounded domain.- Nonlinear filtering of diffusion processes a guided tour.- Note on uniqueness of semigroup associated with Bellman operator.- PDE with random coefficients: Asymptotic expansion for the moments.- A discrete time stochastic decision model.- On the approximation of controlled jump diffusion processes.- On optimal stochastic control problem of large systems.- Unnormalized conditional probabilities and optimality for partially observed controlled jump Markov processes.- On normal approximation in Banach spaces.- A class of problems in the optimal control of diffusions with finitely many controls.- A resumé of some of the applications of Malliavin's calculus.- Large deviations.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this volume the investigations of filtering problems, a start on which has been made in [55], are being continued and are devoted to theoretical problems of processing stochastic fields. The derivation of the theory of processing stochastic fields is similar to that of the theory extensively developed for stochastic processes ('stochastic fields with a one-dimensional domain'). Nevertheless there exist essential distinctions between these cases making a construction of the theory for the multi-dimensional case in such a way difficult. Among these are the absence of the notion of the 'past-future' in the case of fields, which plays a fundamental role in constructing stochastic processes theory. So attempts to introduce naturally the notion of the causality (non-anticipativity) when synthesising stable filters designed for processing fields have not met with success. Mathematically, principal distinctions between multi-dimensional and one-dimensional cases imply that the set of roots of a multi-variable polyno mial does not necessary consist of a finite number of isolated points. From the main theorem of algebra it follows that in the one-dimensional case every poly nomial of degree n has just n roots (considering their multiplicity) in the com plex plane. As a consequence, in particular, an arbitrary rational function Ct. (.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is devoted to an investigation of some important problems of mod ern filtering theory concerned with systems of 'any nature being able to per ceive, store and process an information and apply it for control and regulation'. (The above quotation is taken from the preface to [27]). Despite the fact that filtering theory is l'argely worked out (and its major issues such as the Wiener-Kolmogorov theory of optimal filtering of stationary processes and Kalman-Bucy recursive filtering theory have become classical) a development of the theory is far from complete. A great deal of recent activity in this area is observed, researchers are trying consistently to generalize famous results, extend them to more broad classes of processes, realize and justify more simple procedures for processing measurement data in order to obtain more efficient filtering algorithms. As to nonlinear filter ing, it remains much as fragmentary. Here much progress has been made by R. L. Stratonovich and his successors in the area of filtering of Markov processes. In this volume an effort is made to advance in certain of these issues. The monograph has evolved over many years, coming of age by stages. First it was an impressive job of gathering together the bulk of the impor tant contributions to estimation theory, an understanding and moderniza tion of some of its results and methods, with the intention of applying them to recursive filtering problems.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the study to design, develop, and implement improved PI control techniques using dead-time compensation, structure enhancements, learning functions and fractional ordering parameters. Two fractional-order PI controllers are proposed and designed: fractional-order predictive PI and hybrid iterative learning based fractional-order predictive PI controller. Furthermore, the proposed fractional-order control strategies and filters are simulated over first- and second-order benchmark process models and further validated using the real-time experimentation of the pilot pressure process plant.In this book, five chapters are structured with a proper sequential flow of details to provide a better understanding for the readers. A general introduction to the controllers, filters and optimization techniques is presented in Chapter 1. Reviews of the PI controllers family and their modifications are shown in the initial part of Chapter 2, followed by the development of the proposed fractional-order predictive PI (FOPPI) controller with dead-time compensation ability. In the first part of chapter 3, a review of the PI based iterative learning controllers, modified structures of the ILC and their modifications are presented. Then, the design of the proposed hybrid iterative learning controller-based fractional-order predictive PI controller based on the current cyclic feedback structure is presented. Lastly, the results and discussion of the proposed controller on benchmark process models and the real-time experimentation of the pilot pressure process plant are given. Chapter 4 presents the development of the proposed filtering techniques and their performance comparison with the conventional methods. Chapter 5 proposes the improvement of the existing sine cosine algorithm (SCA) and arithmetic optimization algorithm (AOA) to form a novel arithmetic-trigonometric optimization algorithm (ATOA) to accelerate the rate of convergence in lesser iterations with mitigation towards getting caught in the same local position. The performance analysis of the optimization algorithm will be carried out on benchmark test functions and the real-time pressure process plant.

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paperback. Zustand: New. Language:Chinese.The signal processing method to explore new projects: the optimal frequency and pattern matching method research and application filtering.

paperback. Zustand: New. Paperback.Pub Date:2021-09-01 Pages:207 Language:Chinese Publisher:Science Press Optimal Estimation and Filtering and Its Applications is based on stochastic process theory. and systematically discusses the optimal estimation and filtering of random signals. Basic theory and methods. focusing on the optimal estimation and beamforming (spatial filtering) of the direction of arrival and polarization parameters of radar signals. the vector and spatial smoothing methods of sonar signals. and the .

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paperback. Zustand: New. Ship out in 2 business day, And Fast shipping, Free Tracking number will be provided after the shipment.Paperback. Pub Date :2013-05-01 Pages: 377 Language: Chinese Publisher: National Defense Industry Press . optimal state estimation : H and nonlinear Kalman filtering is divided into four parts. a comprehensive introduction to the optimal state theories and methods to estimate. Part 1 of the basics . recalling the linear systems . probability theory and stochastic processes related knowledge. introduces the least squares method . the statistical properties of the Wiener filter . the state with.Four Satisfaction guaranteed,or money back.

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