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Periodically Correlated Random Sequences

, communications, economics, and machine diagnostics. Periodically Correlated Random Sequences presents the main ideas of these processes through the use;

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Estimates of Periodically Correlated Isotropic Random Fields

unknown values of periodically correlated isotropic random fields. Estimates are based on observations of the fields with a noise. Formulas for;

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Order and Random Sequences

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Algebraic Shift Register Sequences

Pseudo-random sequences are essential ingredients of every modern digital communication system including cellular telephones, GPS, secure;

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Random Graphs

, quasirandom graphs, random walks on trees, degree sequences, random matroids, central limit theorems, percolations and random subgraphs of the n-cube;

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Probability, Random Variables, And Random Signal Principles

student exercises and practical applications for engineers to understand probability concepts. It covers discrete-time random processes and;

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Shift Register Sequences

Shift register sequences cover a broad range of applications, from radar signal design, pseudo-random number generator, digital wireless;

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Asymptotics of Random Matrices and Related Models

asymptotics of the sum of independent variables. However, there are many models of strongly correlated random variables: for instance, the eigenvalues;

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What Is Random?

of coin tosses, it turns out, are determined from the start, and only our incomplete knowledge makes them look random. Random sequences;

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Probability, Statistics, and Random Processes for Engineers

-level calculus, the book develops all the tools needed to understand more advanced topics such as random sequences, continuous-time random;

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Variant Construction from Theoretical Foundation to Applications

, variant stream ciphers, quantum interference, classical/quantum random sequences, whole DNA sequences, and multiple-valued pulse sequences;

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Trellis Based Quantization using the BCJR Algorithm

tailbiting sequences to combat the negative e ects of a xed initial state or an explicit storage of the initial state. The tailbiting BCJR algorithm;

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Random Matrices And Random Partitions

, martingale differences sequences and Markov chains, etc. These classical theorems are frequently used in the study of random matrices and random;

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Elementary Applications of Probability Theory

simulation. Chapter six contains a lucid account of the convergence of sequences of random variables, with emphasis on the central limit theorem and;

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Elementary Applications of Probability Theory

simulation. Chapter six contains a lucid account of the convergence of sequences of random variables, with emphasis on the central limit theorem and;

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Global Seismicity Dynamics and Data Driven Science

deterministic terms and random Gaussian noises. A deterministic term is composed minimally with correlated seismicity rate vectors of a linear term and;

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Global Seismicity Dynamics and Data Driven Science

deterministic terms and random Gaussian noises. A deterministic term is composed minimally with correlated seismicity rate vectors of a linear term and;

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Products of Random Variables

functions Probes sequences of prime divisors and prime numbers Discusses Markov chains, Hilbert spaces, and quotients of random variables;

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Probability And Stochastic Processes

provide direct proofs of the main convergence results for sequences of random variables.The book studies a large range of distribution functions;

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Probability And Stochastic Processes

provide direct proofs of the main convergence results for sequences of random variables.The book studies a large range of distribution functions;

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Probability and Random Processes

; multiple random variables; random sequences and series; random processes in linear systems; Markov processes; and power spectral density.

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Lower Previsions

random quantities by a sequences of bounded ones, and, in essence, we identify those for which the induced lower prevision limit does not depend;

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Basic Probability Theory

of expectation, conditional probability and expectation, and characteristic functions. Subsequent topics include infinite sequences of random variables;

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Intro To Computational Stochastic PDEs

. Later chapters apply the theory of random fields to the numerical solution of elliptic PDEs with correlated random data, discuss the Monte Carlo;

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An Introduction to Computational Stochastic PDEs

. Later chapters apply the theory of random fields to the numerical solution of elliptic PDEs with correlated random data, discuss the Monte Carlo;

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Large Deviations

theorems are presented for i.i.d. sequences, Markov sequences, and sequences with moderate dependence. The rate function is computed explicitly;

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Modeling Survival Data

multiplecorrelated event data using marginal and random effects. The focus is on actual data examples, the analysis and interpretation of results;

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