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Linear Algebra, Markov Chains, and Queueing Models

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Cover of 'Linear Algebra, Markov Chains, and Queueing Models'

Table of Contents

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    Book Overview
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    Chapter 1 Error Bounds for the Computation of Null Vectors with Applications to Markov Chains
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    Chapter 2 The Influence of Nonnormality on Matrix Computations
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    Chapter 3 Componentwise Error Analysis for Stationary Iterative Methods
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    Chapter 4 The Character of a Finite Markov Chain
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    Chapter 5 Gaussian Elimination, Perturbation Theory, and Markov Chains
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    Chapter 6 Algorithms for Periodic Markov Chains
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    Chapter 7 Iterative Methods for Queueing Networks with Irregular State-Spaces
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    Chapter 8 Analysis of P -Cyclic Iterations for Markov Chains
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    Chapter 9 Iterative Methods for Finding the Stationary Vector for Markov Chains
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    Chapter 10 Local Convergence of (Exact and Inexact) Iterative Aggregation
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    Chapter 11 Automated Generation and Analysis of Markov Reward Models Using Stochastic Reward Nets
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    Chapter 12 Means and Variances in Markov Reward Systems
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    Chapter 13 A Direct Algorithm for Computing the Stationary Distribution of a P -Cyclic Markov Chain
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    Chapter 14 Approximate Analysis of a Discrete-Time Queueing Model of the Shared Buffer ATM Switch
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    Chapter 15 Algorithms for Infinite Markov Chains with Repeating Columns
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    Chapter 16 CRAY-2 Memory Organization and Interprocessor Memory Contention
Attention for Chapter 16: CRAY-2 Memory Organization and Interprocessor Memory Contention
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Chapter title
CRAY-2 Memory Organization and Interprocessor Memory Contention
Chapter number 16
Book title
Linear Algebra, Markov Chains, and Queueing Models
Published by
Springer, New York, NY, January 1993
DOI 10.1007/978-1-4613-8351-2_16
Book ISBNs
978-1-4613-8353-6, 978-1-4613-8351-2
Authors

Robert W. Numrich

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 100%
Readers by discipline Count As %
Computer Science 1 100%

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