Linear Prediction Theory
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The Theory Of Linear Prediction
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Author : P. P. Vaidyanathan
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2008
The Theory Of Linear Prediction written by P. P. Vaidyanathan and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Prediction theory categories.
Of Properties Relating to Levinson's Recursion.
Linear Prediction Theory
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Author : Peter Strobach
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Linear Prediction Theory written by Peter Strobach and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
Lnear prediction theory and the related algorithms have matured to the point where they now form an integral part of many real-world adaptive systems. When it is necessary to extract information from a random process, we are frequently faced with the problem of analyzing and solving special systems of linear equations. In the general case these systems are overdetermined and may be characterized by additional properties, such as update and shift-invariance properties. Usually, one employs exact or approximate least-squares methods to solve the resulting class of linear equations. Mainly during the last decade, researchers in various fields have contributed techniques and nomenclature for this type of least-squares problem. This body of methods now constitutes what we call the theory of linear prediction. The immense interest that it has aroused clearly emerges from recent advances in processor technology, which provide the means to implement linear prediction algorithms, and to operate them in real time. The practical effect is the occurrence of a new class of high-performance adaptive systems for control, communications and system identification applications. This monograph presumes a background in discrete-time digital signal processing, including Z-transforms, and a basic knowledge of discrete-time random processes. One of the difficulties I have en countered while writing this book is that many engineers and computer scientists lack knowledge of fundamental mathematics and geometry.
New Methods And Results In Linear Prediction And Filtering Theory
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Author : Rudolf Emil Kalman (Mathematician, United States, Switzerland)
language : en
Publisher:
Release Date : 1961
New Methods And Results In Linear Prediction And Filtering Theory written by Rudolf Emil Kalman (Mathematician, United States, Switzerland) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1961 with categories.
New Methods And Results In Linear Prediction And Filtering Theory
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Author : Rudolf Emil Kalman
language : en
Publisher:
Release Date : 1961
New Methods And Results In Linear Prediction And Filtering Theory written by Rudolf Emil Kalman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1961 with Probabilities categories.
The Theory Of Linear Prediction
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Author : P. Vaidyanathan
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
The Theory Of Linear Prediction written by P. Vaidyanathan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Technology & Engineering categories.
Linear prediction theory has had a profound impact in the field of digital signal processing. Although the theory dates back to the early 1940s, its influence can still be seen in applications today. The theory is based on very elegant mathematics and leads to many beautiful insights into statistical signal processing. Although prediction is only a part of the more general topics of linear estimation, filtering, and smoothing, this book focuses on linear prediction. This has enabled detailed discussion of a number of issues that are normally not found in texts. For example, the theory of vector linear prediction is explained in considerable detail and so is the theory of line spectral processes. This focus and its small size make the book different from many excellent texts which cover the topic, including a few that are actually dedicated to linear prediction. There are several examples and computer-based demonstrations of the theory. Applications are mentioned wherever appropriate, but the focus is not on the detailed development of these applications. The writing style is meant to be suitable for self-study as well as for classroom use at the senior and first-year graduate levels. The text is self-contained for readers with introductory exposure to signal processing, random processes, and the theory of matrices, and a historical perspective and detailed outline are given in the first chapter. Table of Contents: Introduction / The Optimal Linear Prediction Problem / Levinson's Recursion / Lattice Structures for Linear Prediction / Autoregressive Modeling / Prediction Error Bound and Spectral Flatness / Line Spectral Processes / Linear Prediction Theory for Vector Processes / Appendix A: Linear Estimation of Random Variables / B: Proof of a Property of Autocorrelations / C: Stability of the Inverse Filter / Recursion Satisfied by AR Autocorrelations
Linear Prediction On A Finite Past Of A Multivariate Stationary Process
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Author : Ray G. Langebartel
language : en
Publisher:
Release Date : 1966
Linear Prediction On A Finite Past Of A Multivariate Stationary Process written by Ray G. Langebartel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1966 with Multivariate analysis categories.
An overview is given of multivariate, wide-sense, stationary, stochastic process, linear prediction theory with emphasis on the mean square error of prediction based on a finite past. Examples of several different types of processes are examined with specific formulas for the prediction errors obtained in some cases. A discussion is given concerning the effect on the prediction error of basing the prediction on a subprocess of the given process instead of on the entire original process.
Linear Prediction Theory For Digital Simulation In Structural Dynamics Applications
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Author : Jerry Edward Hansen
language : en
Publisher:
Release Date : 1981
Linear Prediction Theory For Digital Simulation In Structural Dynamics Applications written by Jerry Edward Hansen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1981 with Structural dynamics categories.
Dynamic Programming And Linear Prediction Theory
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Author : Richard Bellman
language : en
Publisher:
Release Date : 1961
Dynamic Programming And Linear Prediction Theory written by Richard Bellman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1961 with Dynamic programming categories.
The application is considered of the theory of dynamic programming to a discrete form of the linear prediction problem, that of minimizing over u sub k a given quadratic form.
The Linear Prediction Of Deterministic Signals
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Author : Samuel Zahl
language : en
Publisher:
Release Date : 1964
The Linear Prediction Of Deterministic Signals written by Samuel Zahl and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1964 with Decision theory categories.
The exact algebraic solution is given for prediction of linear signals for up to three observations and is compared with the solution based on Wiener's theory.
Linear Data Smoothing And Prediction In Theory And Practice
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Author : Ralph Beebe Blackman
language : en
Publisher:
Release Date : 1965
Linear Data Smoothing And Prediction In Theory And Practice written by Ralph Beebe Blackman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1965 with Digital filters categories.