Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Download Optimal Parameter Adaptive Estimation Of Stochastic Processes full books in PDF, epub, and Kindle. Read online Optimal Parameter Adaptive Estimation Of Stochastic Processes ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author : Alper Kamil Caglayan
Publisher :
ISBN 13 :
Total Pages : 256 pages
Book Rating : 4.:/5 (211 download)
Download or read book Optimal parameter adaptive Estimation of stochastic processes written by Alper Kamil Caglayan and published by . This book was released on 1974 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Stanford University. Stanford Electronics Laboratories
Publisher :
ISBN 13 :
Total Pages : 84 pages
Book Rating : 4.F/5 ( download)
Download or read book Optimal Adaptive Estimation of Sampled Stochastic Processes written by Stanford University. Stanford Electronics Laboratories and published by . This book was released on 1963 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work presents an adaptive approach to the problem of estimating a sampled, scalar-valued, stochastic process described by an initially unknown parameter vector. Knowledge of this quantity completely specifies the statistics of the proc ess, and consequently the optimal estimator must learn the value of the parameter vector. In order that construction of the optimal estimator be feasible it is necessary to consider only those processes whose parameter vector comes from a finite set of a priori known values. Fortunately, many practical problems may be represented or adequately approximated by such a model. The optimal estimator is found to be composed of a set of elemental estimators and a corresponding set of weighting coefficients, one pair for each possible value of the parameter vector. This structure is derived using properties of the conditional mean operator. For gauss-markov processes the elemental estimators are linear, dynamic systems, and evaluation of the weighting coefficients involves relatively simple, nonlinear calculations. The resulting system is optimum in the sense that it minimizes the expected value of a positive-definite, quadratic form in terms of the error (a generalized mean-square-error criterion). Because the system described in this work is optimal, it differs from previous attempts at adaptive estimation, all of which have used approximation techniques or suboptimal, sequential, optimization procedures. (Author).
Author : P. R. Kumar
Publisher : SIAM
ISBN 13 : 1611974267
Total Pages : 371 pages
Book Rating : 4.6/5 (119 download)
Download or read book Stochastic Systems written by P. R. Kumar and published by SIAM. This book was released on 2015-12-15 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area. This book provides succinct and rigorous treatment of the foundations of stochastic control; a unified approach to filtering, estimation, prediction, and stochastic and adaptive control; and the conceptual framework necessary to understand current trends in stochastic control, data mining, machine learning, and robotics.?
Author : Yu. A. Kutoyants
Publisher :
ISBN 13 :
Total Pages : 224 pages
Book Rating : 4.3/5 (91 download)
Download or read book Parameter Estimation for Stochastic Processes written by Yu. A. Kutoyants and published by . This book was released on 1984 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Kaddour Najim
Publisher : Elsevier
ISBN 13 : 008051779X
Total Pages : 345 pages
Book Rating : 4.0/5 (85 download)
Download or read book Stochastic Processes written by Kaddour Najim and published by Elsevier. This book was released on 2004-07-01 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: A ‘stochastic’ process is a ‘random’ or ‘conjectural’ process, and this book is concerned with applied probability and statistics. Whilst maintaining the mathematical rigour this subject requires, it addresses topics of interest to engineers, such as problems in modelling, control, reliability maintenance, data analysis and engineering involvement with insurance.This book deals with the tools and techniques used in the stochastic process – estimation, optimisation and recursive logarithms – in a form accessible to engineers and which can also be applied to Matlab. Amongst the themes covered in the chapters are mathematical expectation arising from increasing information patterns, the estimation of probability distribution, the treatment of distribution of real random phenomena (in engineering, economics, biology and medicine etc), and expectation maximisation. The latter part of the book considers optimization algorithms, which can be used, for example, to help in the better utilization of resources, and stochastic approximation algorithms, which can provide prototype models in many practical applications. * An engineering approach to applied probabilities and statistics * Presents examples related to practical engineering applications, such as reliability, randomness and use of resources* Readers with varying interests and mathematical backgrounds will find this book accessible
Author : Charles Gene Hilborn
Publisher :
ISBN 13 :
Total Pages : 103 pages
Book Rating : 4.:/5 (219 download)
Download or read book Learning systems for minimum risk adaptive pattern classification and optimal adaptive estimation written by Charles Gene Hilborn and published by . This book was released on 1968 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two problems of unsupervised learning, sequential multi-category pattern classification and adaptive estimation of a sampled stochastic process are jointly investigated. An unknown parameter model is developed which, for the pattern classification problem, allows for (i) both constant and time-varying unknown parameters, (ii) partially unknown probability laws of the hypotheses and time-varying parameter sequences, (iii) dependence of the observations on past as well as present hypotheses and parameters, and most significantly (iv) sequential dependencies in the observations arising from either (or both) dependency in the pattern or information source (context independence) or in the observation medium (measurement correlation), these dependencies being up to any finite Markov orders. For the adaptive estimation problem the same model is employed without any distinction between 'hypotheses' and 'time-varying parameters.' For finite parameter spaces, the solutions which are Bayes optimal (minimum risk) at each step are found for both problems and shown to be realizable in recursive form with fixed memory requirements. The recursive 'learning' portion of the solutions is the same for both problems. The asymptotic properties of the optimal systems are studied and conditions established for these systems (in addition to making best use of available data at each step) to converge in performance to systems operating with knowledge of the (unobservable) constant unknown parameters. (Author).
Author : Keigo Watanabe
Publisher :
ISBN 13 :
Total Pages : 618 pages
Book Rating : 4.3/5 (91 download)
Download or read book Adaptive Estimation and Control written by Keigo Watanabe and published by . This book was released on 1991 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unifies the partitioned adaptive estimators for stochastic systems and applies them to other estimation and control problems. The techniques, not restricted to lumped-parameter systems with unknown constant parameters, serve as a starting point for more complicated problems.
Author : Albert Benveniste
Publisher : Springer Science & Business Media
ISBN 13 : 3642758940
Total Pages : 373 pages
Book Rating : 4.6/5 (427 download)
Download or read book Adaptive Algorithms and Stochastic Approximations written by Albert Benveniste and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive systems are widely encountered in many applications ranging through adaptive filtering and more generally adaptive signal processing, systems identification and adaptive control, to pattern recognition and machine intelligence: adaptation is now recognised as keystone of "intelligence" within computerised systems. These diverse areas echo the classes of models which conveniently describe each corresponding system. Thus although there can hardly be a "general theory of adaptive systems" encompassing both the modelling task and the design of the adaptation procedure, nevertheless, these diverse issues have a major common component: namely the use of adaptive algorithms, also known as stochastic approximations in the mathematical statistics literature, that is to say the adaptation procedure (once all modelling problems have been resolved). The juxtaposition of these two expressions in the title reflects the ambition of the authors to produce a reference work, both for engineers who use these adaptive algorithms and for probabilists or statisticians who would like to study stochastic approximations in terms of problems arising from real applications. Hence the book is organised in two parts, the first one user-oriented, and the second providing the mathematical foundations to support the practice described in the first part. The book covers the topcis of convergence, convergence rate, permanent adaptation and tracking, change detection, and is illustrated by various realistic applications originating from these areas of applications.
Author : Denis Belomestny
Publisher : Springer
ISBN 13 : 3319123734
Total Pages : 303 pages
Book Rating : 4.3/5 (191 download)
Download or read book Lévy Matters IV written by Denis Belomestny and published by Springer. This book was released on 2014-12-05 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this volume is to provide an extensive account of the most recent advances in statistics for discretely observed Lévy processes. These days, statistics for stochastic processes is a lively topic, driven by the needs of various fields of application, such as finance, the biosciences, and telecommunication. The three chapters of this volume are completely dedicated to the estimation of Lévy processes, and are written by experts in the field. The first chapter by Denis Belomestny and Markus Reiß treats the low frequency situation, and estimation methods are based on the empirical characteristic function. The second chapter by Fabienne Comte and Valery Genon-Catalon is dedicated to non-parametric estimation mainly covering the high-frequency data case. A distinctive feature of this part is the construction of adaptive estimators, based on deconvolution or projection or kernel methods. The last chapter by Hiroki Masuda considers the parametric situation. The chapters cover the main aspects of the estimation of discretely observed Lévy processes, when the observation scheme is regular, from an up-to-date viewpoint.
Author : David Edward Meer
Publisher :
ISBN 13 :
Total Pages : 231 pages
Book Rating : 4.:/5 (227 download)
Download or read book Multiple Model Adaptive Estimation for Space-time Point Process Observations written by David Edward Meer and published by . This book was released on 1982 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem addressed by this research is one of estimating parameters of an underlying stochastic process from observations of a point process where the point process is dependent on the underlying process and the observations are corrupted by point process noise. A second, closely related problem is that of allowing feedback control for a system in which observations of a point process signal are corrupted by point process noise. This will provide a method for investignating the optimal stochastic adaptive controller for the system. The major contribution of this research is a method for developing an estimator for the above mentioned point process signal in point process noise environment. The method allows feedback to the model from the observations thus providing a means for control. This method is used to develop the estimator for the neutral particle beam pointing and tracking problem which motivated this research. (Author).
Author : Robert B. Asher
Publisher :
ISBN 13 :
Total Pages : 28 pages
Book Rating : 4.:/5 (227 download)
Download or read book Adaptive Estimation of Doubly Stochastic Poisson Processes with Application to Adaptive Optics written by Robert B. Asher and published by . This book was released on 1976 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: The optimal adaptive estimator structures for a class of doubly stochastic Poisson processes (DSPP) are presented. The structure is used along with a moment assumption to obtain implementable estimators. The class of DSPP considered is that of a linear Markov diffusion process modulating a linear intensity rate. The uncertainty for which the adaptation process is developed includes both structure uncertainty in the Markov diffusion process, and parameter uncertainty in the Markov diffusion process and the intensity rate process. Results are given on the problem of adaptation of which of a finite number of Markov realizations is modulating the intensity process. The nonlinear adaptive estimator structures are obtained by use of a particular theorem that yields an optimal structure for the adaptive estimator. The structure is used to obtain a quasi-optimal adaptive estimator for the problem by use of a zero third central moment assumption. The estimator structure consists of a nonlinear, nonadaptive part, and a nonlinear, adaptive part which contains the parameter structure adaptations.
Author : Bozenna Pasik-Duncan
Publisher : Springer
ISBN 13 : 3540480226
Total Pages : 563 pages
Book Rating : 4.5/5 (44 download)
Download or read book Stochastic Theory and Control written by Bozenna Pasik-Duncan and published by Springer. This book was released on 2003-07-01 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains almost all of the papers that were presented at the Workshop on Stochastic Theory and Control that was held at the Univ- sity of Kansas, 18–20 October 2001. This three-day event gathered a group of leading scholars in the ?eld of stochastic theory and control to discuss leading-edge topics of stochastic control, which include risk sensitive control, adaptive control, mathematics of ?nance, estimation, identi?cation, optimal control, nonlinear ?ltering, stochastic di?erential equations, stochastic p- tial di?erential equations, and stochastic theory and its applications. The workshop provided an opportunity for many stochastic control researchers to network and discuss cutting-edge technologies and applications, teaching and future directions of stochastic control. Furthermore, the workshop focused on promoting control theory, in particular stochastic control, and it promoted collaborative initiatives in stochastic theory and control and stochastic c- trol education. The lecture on “Adaptation of Real-Time Seizure Detection Algorithm” was videotaped by the PBS. Participants of the workshop have been involved in contributing to the documentary being ?lmed by PBS which highlights the extraordinary work on “Math, Medicine and the Mind: Discovering Tre- ments for Epilepsy” that examines the e?orts of the multidisciplinary team on which several of the participants of the workshop have been working for many years to solve one of the world’s most dramatic neurological conditions. Invited high school teachers of Math and Science were among the part- ipants of this professional meeting.
Author :
Publisher : Academic Press
ISBN 13 : 0080956351
Total Pages : 606 pages
Book Rating : 4.0/5 (89 download)
Download or read book System Identification Advances and Case Studies written by and published by Academic Press. This book was released on 1977-02-21 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; andmethods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory.As a result, the book represents a blend of new methods in general computational analysis,and specific, but also generic, techniques for study of systems theory ant its particularbranches, such as optimal filtering and information compression. - Best operator approximation,- Non-Lagrange interpolation,- Generic Karhunen-Loeve transform- Generalised low-rank matrix approximation- Optimal data compression- Optimal nonlinear filtering
Author : Peter E. Caines
Publisher : SIAM
ISBN 13 : 1611974712
Total Pages : 874 pages
Book Rating : 4.6/5 (119 download)
Download or read book Linear Stochastic Systems written by Peter E. Caines and published by SIAM. This book was released on 2018-06-12 with total page 874 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear Stochastic Systems, originally published in 1988, is today as comprehensive a reference to the theory of linear discrete-time-parameter systems as ever. Its most outstanding feature is the unified presentation, including both input-output and state space representations of stochastic linear systems, together with their interrelationships. The author first covers the foundations of linear stochastic systems and then continues through to more sophisticated topics including the fundamentals of stochastic processes and the construction of stochastic systems; an integrated exposition of the theories of prediction, realization (modeling), parameter estimation, and control; and a presentation of stochastic adaptive control theory. Written in a clear, concise manner and accessible to graduate students, researchers, and teachers, this classic volume also includes background material to make it self-contained and has complete proofs for all the principal results of the book. Furthermore, this edition includes many corrections of errata collected over the years.
Author : Maksym Luz
Publisher : John Wiley & Sons
ISBN 13 : 1786305038
Total Pages : 308 pages
Book Rating : 4.7/5 (863 download)
Download or read book Estimation of Stochastic Processes with Stationary Increments and Cointegrated Sequences written by Maksym Luz and published by John Wiley & Sons. This book was released on 2019-12-12 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimation of Stochastic Processes is intended for researchers in the field of econometrics, financial mathematics, statistics or signal processing. This book gives a deep understanding of spectral theory and estimation techniques for stochastic processes with stationary increments. It focuses on the estimation of functionals of unobserved values for stochastic processes with stationary increments, including ARIMA processes, seasonal time series and a class of cointegrated sequences. Furthermore, this book presents solutions to extrapolation (forecast), interpolation (missed values estimation) and filtering (smoothing) problems based on observations with and without noise, in discrete and continuous time domains. Extending the classical approach applied when the spectral densities of the processes are known, the minimax method of estimation is developed for a case where the spectral information is incomplete and the relations that determine the least favorable spectral densities for the optimal estimations are found.
Author : T. E. Duncan
Publisher : Springer
ISBN 13 :
Total Pages : 526 pages
Book Rating : 4.3/5 (91 download)
Download or read book Stochastic Theory and Adaptive Control written by T. E. Duncan and published by Springer. This book was released on 1992 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: This workshop on stochastic theory and adaptive control assembled many of the leading researchers on stochastic control and stochastic adaptive control to increase scientific exchange and cooperative research between these two subfields of stochastic analysis. The papers included in the proceedings include survey and research. They describe both theoretical results and applications of adaptive control. There are theoretical results in identification, filtering, control, adaptive control and various other related topics. Some applications to manufacturing systems, queues, networks, medicine and other topics are gien.
Author : Jianqing Fan
Publisher : Springer Science & Business Media
ISBN 13 : 1461455448
Total Pages : 626 pages
Book Rating : 4.4/5 (614 download)
Download or read book Selected Works of Peter J. Bickel written by Jianqing Fan and published by Springer Science & Business Media. This book was released on 2012-11-28 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents selections of Peter J. Bickel’s major papers, along with comments on their novelty and impact on the subsequent development of statistics as a discipline. Each of the eight parts concerns a particular area of research and provides new commentary by experts in the area. The parts range from Rank-Based Nonparametrics to Function Estimation and Bootstrap Resampling. Peter’s amazing career encompasses the majority of statistical developments in the last half-century or about about half of the entire history of the systematic development of statistics. This volume shares insights on these exciting statistical developments with future generations of statisticians. The compilation of supporting material about Peter’s life and work help readers understand the environment under which his research was conducted. The material will also inspire readers in their own research-based pursuits. This volume includes new photos of Peter Bickel, his biography, publication list, and a list of his students. These give the reader a more complete picture of Peter Bickel as a teacher, a friend, a colleague, and a family man.
