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Acoustic Echo and Noise Control

methods to control echo and noise Develops a statistical theory for optimal control parameters and presents practical estimation and approximation;

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Optimal Estimation in Approximation Theory

The papers in this volume were presented at an International Symposium on Optimal Estimation in Approximation Theory which was held;

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Approximate Iterative Algorithms

Iterative algorithms often rely on approximate evaluation techniques, which may include statistical estimation, computer simulation or;

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Approximate Iterative Algorithms

Iterative algorithms often rely on approximate evaluation techniques, which may include statistical estimation, computer simulation or;

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An Engineering Approach to Optimal Control and Estimation Theory

Optimal control and optimal estimation are methods used to estimate unknown variables such as velocity and altitude, and are essential to;

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Computational Methods for Modeling of Nonlinear Systems by Anatoli Torokhti and Phil Howlett

estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation;

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Interpolation and Extrapolation Optimal Designs V1

approximation of functions, the authors introduce the basic elements to design planning and link the statistical theory of optimal design and the theory;

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Advanced Signal Processing

explains the necessary underlying mathematics. Coverage includes representation and approximation theory in vector spaces, the orthogonality;

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Journal of Approximation Theory and Applied Mathematics - 2013 Vol. 1 and Vol. 2

Journal of Approximation Theory and Applied Mathematics (ISSN 2196-1581) is a journal which started in 2013. Themes of our journal are;

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Optimal Estimation Of Parameters

This book presents a comprehensive and consistent theory of estimation. The framework described leads naturally to a generalized maximum;

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Optimal Design

realized. Nevertheless discussion in this monograph is limited to the theory of design optimal for parameter estimation.;

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Linear and Non-Linear System Theory

Linear and Non-Linear System Theory focuses on the basics of linear and non-linear systems, optimal control and optimal estimation with an;

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Interpolation and Extrapolation Optimal Designs 2

algorithms leading to optimal designs in multivariate models. Elfving s theory and the theorem of equivalence are presented extensively. The volume;

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Estimation Problems in Hybrid Systems

a practical, finite-dimensional approximation to an optimal estimator. Throughout the book, they illustrate theoretical results by;

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Estimation Problems in Hybrid Systems

a practical, finite-dimensional approximation to an optimal estimator. Throughout the book, they illustrate theoretical results by;

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Optimal and Robust Estimation

today's high-performance systems. A Classic Revisited Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second;

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Encyclopedia of Mathematics and its Applications

of approximation theory that is concerned with exact constants. The results apply mainly to extremal problems in approximation theory, which in turn are;

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Encyclopedia of Mathematics and its Applications

of approximation theory that is concerned with exact constants. The results apply mainly to extremal problems in approximation theory, which in turn are;

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Optimal State Estimation

-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a;

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Mathematical Foundations of Infinite-Dimensional Statistical Models

'mini-courses' on the theory of Gaussian and empirical processes, approximation and wavelet theory, and the basic theory of function spaces. The;

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Modern Trends in Constructive Function Theory

, Nashville, TN, in honor of Ed Saff's 70th birthday. The papers in this volume contain results on polynomial approximation, rational approximation;

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Optimal Control of Stochastic Difference Volterra Equations

their past history; it is an introduction to the mathematical theory of optimal control for stochastic difference Volterra equations of neutral;

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Optimal Estimation of Dynamic Systems

, the text presents the central concepts and methods of optimal estimation theory and applies the methods to problems with varying degrees;

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Reproducing Kernel Hilbert Spaces in Probability and Statistics

theorems, learning theory and some applications at the fringe between Statistics and Approximation Theory. It is geared to graduate students;

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Low Rank Approximation

This book is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local;

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Multisensor Fusion Estimation Theory and Application

This book focuses on the basic theory and methods of multisensor data fusion state estimation and its application. It consists of four;

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Introduction to the Theory of Nonlinear Optimization

presents fundamentals with particular emphasis on the application to problems in the calculus of variations, approximation and optimal control;

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