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Stable Non-Gaussian Random Processes

This book presents similarity between Gaussian and non-Gaussian stable multivariate distributions and introduces the one-dimensional stable;

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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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Stable Non Gaussian Self Similar Processes with Stationary Increments

sections in the book review random variables, stochastic processes, and integrals, moving on to rigidity and flows, and finally ending with mixed;

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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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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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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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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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Statistical Mechanics & Random Walks

; subordinated Gaussian processes; random walk models in biophysical science; non-equilibrium dynamics and diffusion processes; global random walk;

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Gaussian Random Processes

The book deals mainly with three problems involving Gaussian stationary processes. The first problem consists of clarifying the conditions;

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Some Random Series of Functions

Hilbert spaces, random Taylor or Fourier series, Brownian motion and other Gaussian processes, plus certain types of random sets and measures. The;

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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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Probability

limiting theorems, Bayesian computational methods, as well as a modern view on sampling and reconstruction of Gaussian and non-Gaussian 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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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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Random Fields for Spatial Data Modeling

representations, perturbation and variational methods). The book also explores links between random fields, Gaussian processes and neural networks used;

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Random Fourier Series with Applications to Harmonic Analysis. (AM-101), Volume 101

locally compact Abelian groups and on compact non-Abelian groups. They also obtain many related results. For example, whenever a random Fourier;

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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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Advances in Stochastic Structural Dynamics

processes, and sample path behavior of Gaussian processes. For scientists and researchers.;

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Functional Gaussian Approximation for Dependent Structures

of dependent random variables which satisfy invariance principles, making possible the statistical study of data coming from stochastic processes both;

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Modeling Fluctuations in Scattered Waves

statistics. The following chapters describe Gaussian processes and the random walk model, address multiple scattering effects and propagation through;

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Advanced Probability Theory for Biomedical Engineers

This is the third in a series of short books on probability theory and random processes for biomedical engineers. This book focuses on;

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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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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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Statistical Inference in Financial and Insurance Mathematics with R

, the Generalized Linear Models are studied. They extend the standard regression model to non-Gaussian distributions. Statistical experiments;

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Advanced Signal Processing and Digital Noise Reduction

measures. The concepts of stationary, non-stationary and ergodic processes are introduced in this chapter, and some important classes of random;

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