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Stochastic Analysis for Gaussian Random Processes and Fields

Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic;

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Stochastic Analysis for Gaussian Random Processes and Fields

Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic;

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Simulation of Stochastic Processes with Given Accuracy and Reliability

reliability in functional spaces. The authors explore analysis of the theory of Sub-Gaussian (including Gaussian one) and Square Gaussian random;

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Advances in Stochastic Structural Dynamics

during May 26-28, 2003. Topics include direct transfer substructure method for random response analysis, generation of bounded stochastic;

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Stochastic Analysis & Applications

Increments of a Class of Gaussian Processes; Random Walk Tests & Pseudorandom Number Generators; Increments Theory on Gaussian Processes; The Law;

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Statistical Mechanics & Random Walks

algorithm for diffusion processes and application of random walks for the analysis of graphs, musical composition and language phylogeny.;

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Stochastic Dynamics and Control

processes Random vibrations Structural reliability and fatigue, Non-Gaussian fatigue Monte Carlo methods Stochastic calculus;

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Random Fields for Spatial Data Modeling

analysis are integral parts of many scientific and engineering disciplines. Random fields provide a general theoretical framework for the;

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Fundamentals of Stochastic Nature Sciences

analysis of Gaussian random fields, as well as stochastic structure formation in dynamic systems with parametric excitation of positive random;

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Fundamentals of Stochastic Nature Sciences

analysis of Gaussian random fields, as well as stochastic structure formation in dynamic systems with parametric excitation of positive random;

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Level Sets and Extrema of Random Processes and Fields

. Level Sets and Extrema of Random Processes and Fields is an excellent book for courses on probability theory, spatial statistics, Gaussian;

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Theory and Statistical Applications of Stochastic Processes

Gaussian processes, Ito integration, stochastic analysis, stochastic differential equations, fractional Brownian motion and parameter estimation;

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Stochastic Analysis of Mixed Fractional Gaussian Processes

Stochastic Analysis of Mixed Fractional Gaussian Processes presents the main tools necessary to characterize Gaussian processes. The book;

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Stochastic Tools in Turbulence

proceeds to examinations of moments, characteristic functions, and the Gaussian distribution; random functions; and random processes in more;

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Random Fields On The Sphere

harmonic analysis, beginning with the representation theory for the group of rotations SO(3). Many recent developments on the method of moments and;

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Random Processes By Example

. The toolbox includes Gaussian processes, independently scattered measures such as Gaussian white noise and Poisson random measures, stochastic;

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Intro To Computational Stochastic PDEs

This book gives a comprehensive introduction to numerical methods and analysis of stochastic processes, random fields and stochastic;

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An Introduction to Computational Stochastic PDEs

This book gives a comprehensive introduction to numerical methods and analysis of stochastic processes, random fields and stochastic;

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Gaussian and Non-Gaussian Linear Time Series and Random Fields

with problems of prediction and estimation. New results for nonminimum phase non-Gaussian processes are exposited and open questions are noted;

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Non-Gaussian Random Vibration Fatigue Analysis and Accelerated Test

This book discusses the theory, method and application of non-Gaussian random vibration fatigue analysis and test. The main contents;

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Probability And Stochastic Processes

for random variables and processes: Bernoulli, multinomial, exponential, Gamma, Beta, Dirichlet, Poisson, Gaussian, Chi2, ordered variables;

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Probability And Stochastic Processes

for random variables and processes: Bernoulli, multinomial, exponential, Gamma, Beta, Dirichlet, Poisson, Gaussian, Chi2, ordered variables;

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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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Stochastic Processes and their Applications

Stochastic Processes and their Applications illustrates the theoretical knowledge of random variables along with some practical skills to;

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Real And Stochastic Analysis

Processes (H Soedjak)Readership: Graduate students and researchers in Probability and Stochastic Analysis.

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Mathematical Physics at Saint-Flour

Gross, Leonard: Thermodynamics, statistical mechanics, and random fields.-Foellmer, Hans: Random fields and diffusion processes.- Nelson;

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Introduction to the Theory of Random Processes

respect to random orthogonal measures. In particular, it is used for spectral representation of trajectories of stationary processes and for;

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