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Functional Gaussian Approximation for Dependent Structures

Functional Gaussian Approximation for Dependent Structures develops and analyses mathematical models for phenomena that evolve in time and;

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Current-Mode Analog Nonlinear Function Synthesizer Structures

-order approximation functions. A variety of analog function synthesizer structures are discussed, based on accurate approximation functions;

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Gaussian Process Regression Analysis for Functional Data

Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis;

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Statistical Modeling Using Local Gaussian Approximation

Statistical Modeling using Local Gaussian Approximation extends powerful characteristics of the Gaussian distribution, perhaps, the;

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Theory and Applications of Gaussian Quadrature Methods

Gaussian quadrature is a powerful technique for numerical integration that falls under the broad category of spectral methods. The purpose;

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Differential Geometry, Functional Analysis and Applications

This book discusses Submanifolds theory, Fibre bundle, Harmonic morphisms, Homogeneous and symmetric spaces, Structures on manifolds;

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Functional Integrals

processes. This monograph is devoted to numerical approximation methods of continual integration. A systematic description is given of the;

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Large Deviations for Gaussian Queues

Gaussian traffic model enables the analysis, in a single mathematical framework, of systems with both long-range and short-range dependent input;

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Orthogonal Functions

functions, moment theory, and integral transforms. Describes links between continued fractions. Pade approximation, special functions, and Gaussian;

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Functional Analysis, Holomorphy, and Approximation Theory

Functional Analysis, Holomorphy, and Approximation Theory held in 1979. It is addressed to mathematicians and advanced graduate students;

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Functional Analysis, Holomorphy, and Approximation Theory

Functional Analysis, Holomorphy, and Approximation Theory held in 1979. It is addressed to mathematicians and advanced graduate students;

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Orthogonal Functions

functions, moment theory, and integral transforms. Describes links between continued fractions. Pade approximation, special functions, and Gaussian;

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The Best Approximation Method in Computational Mechanics

publication assists the computer modeller in his search for the best approximation by presenting functional analysis concepts. Computer programs are;

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Neural Approximations for Optimal Control and Decision

Neural Approximations for Optimal Control and Decision provides a comprehensive methodology for the approximate solution of functional;

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Approximate Iterative Algorithms

functional approximation. This volume presents methods for the study of approximate iterative algorithms, providing tools for the derivation of error;

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Approximate Iterative Algorithms

functional approximation. This volume presents methods for the study of approximate iterative algorithms, providing tools for the derivation of error;

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Purely Functional Data Structures

Most books on data structures assume an imperative language like C or C++. However, data structures for these languages do not always;

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Purely Functional Data Structures

Most books on data structures assume an imperative language like C or C++. However, data structures for these languages do not always;

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Computational Mathematics and Variational Analysis

, operations research, game theory, differential equations, functional analysis, operator theory, approximation theory, numerical analysis, asymptotic;

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Sparse Approximation with Bases

approximation. Taking into account the theoretical and practical demand for this kind of theory, the book systematically elaborates a theoretical;

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Stochastic Optimal Control of Structures

by engineering excitations in the nature of non-stationary and non-Gaussian processes. Further, it establishes the theory of and methods for;

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Stochastic Optimal Control of Structures

by engineering excitations in the nature of non-stationary and non-Gaussian processes. Further, it establishes the theory of and methods for;

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VaR Methodology for Non-Gaussian Finance

assumptions leading to what is called non-Gaussian finance. With the growing importance of Solvency II, Basel II and III regulatory rules for;

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Multilevel and Longitudinal Modeling Using Stata, Volumes I and II, Third Edition

mixed because they allow fixed and random effects, and they are generalized because they are appropriate for continuous Gaussian responses as;

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Stochastic Analysis & Applications

Weak Law of Large Numbers for Weighted Sums of Pairwise Negative Quadrant Dependent Random Variables; The Moduli of Continuity & Large;

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Gaussian Measures in Hilbert Space

measure and via a characteristic functional based on Minlos-Sazonov theorem. As such, it can be utilized for obtaining results for topological;

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Gaussian Hilbert Spaces

This book treats the very special and fundamental mathematical properties that hold for a family of Gaussian (or normal) random variables;

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