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Books on the topic 'Discrete-Event models'

Author: Grafiati
Published: 1 February 2023

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1

Erminia, Vaccari, ed. Dynamic models and discrete event simulation. New York: M. Dekker, 1989.

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2

Varaiya, Pravin, and Alexander B. Kurzhanski, eds. Discrete Event Systems: Models and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/bfb0042300.

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3

Keith, Park Stephen, ed. Discrete-event simulation: A first course. Upper Saddle River, N.J: Pearson Prentice Hall, 2006.

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4

Wainer, Gabriel A. Discrete-event modeling and simulation: A practitioner's approach. Boca Raton: CRC Press, 2009.

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5

Kumar, Ratnesh. Modeling and control of logical discrete event systems. Boston: Kluwer Academic Publishers, 1995.

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6

Kedem, Zvi M. Relational database behavior: utilizing relational discrete event systems and models. New York: Courant Institute of Mathematical Sciences, New York University, 1988.

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7

Yucesan, Enver. "Simulation graphs for design and analysis of discrete event simulation models". Fontainbleau: INSEAD, 1986.

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8

Yücesan, Enver. On the intractability of verifying structural properties of discrete event simulation models. Fontainebleau: INSEAD, 1992.

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9

Zhou, MengChu. Petri net synthesis for discrete event control of manufacturing systems. Boston: Kluwer Academic, 1993.

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10

R, Kumar P., and Varaiya P. P, eds. Discrete event systems, manufacturing systems, and communication networks. New York: Springer Verlag, 1995.

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11

Nicol, David. The cost of conservative synchronization in parallel discrete event simulations. Hampton, Va: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1990.

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12

B, Kurzhanskiĭ A., Varaiya P. P, and International Institute for Applied Systems Analysis., eds. Discrete event systems: Models and applications : IIASA Conference, Sopron, Hungary, August 3-7, 1987. Berlin: Springer-Verlag, 1988.

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13

IFAC Workshop on Discrete Event System Theory and Applications in Manufacturing and Social Phenomena (1991 Shen-yang shih, China). Proceedings of the 1991 IFAC Workshop on Discrete Event System Theory and Applications in Manufacturing and Social Phenomena: June 25-27, 1991, Shenyang, China. Beijing, China: International Academic Publishers, 1991.

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14

Salfner, Felix. Modeling event-driven time series with generalized hidden semi-Markov models. Berlin: Humboldt-Universität zu Berlin, 2006.

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15

Yuriy, Greg M. Discrete-event simulation of mine equipment systems combined with a reliability assessment model /by Greg M. Yuriy. Sudbury, Ont: Laurentian University, School of Graduate Studies, 2005.

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16

service), SpringerLink (Online, ed. SynDEVS Co-Design Flow: A Hardware / Software Co-Design Flow Based on the Discrete Event System Specification Model of Computation. Wiesbaden: Springer Fachmedien Wiesbaden, 2012.

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17

Delaney, W. Dynamic Models and Discrete Event Simulation. Taylor & Francis Group, 2020.

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18

Delaney, W. Dynamic Models and Discrete Event Simulation. Taylor & Francis Group, 2020.

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19

Delaney, W. Dynamic Models and Discrete Event Simulation. Taylor & Francis Group, 2020.

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20

Delaney, W. Dynamic Models and Discrete Event Simulation. Taylor & Francis Group, 2020.

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21

Discrete-Event Modeling and Simulation. CRC, 2008.

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22

Wainer, Gabriel A., and Pieter J. Mosterman. Discrete-Event Modeling and Simulation. Taylor & Francis Group, 2010.

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23

Park, Stephen K., and Lawrence M. Leemis. Discrete-Event Simulation: A First Course. Prentice Hall, 2005.

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24

Park, Stephen K., and Lawrence M. Leemis. Discrete-Event Simulation: A First Course. Prentice Hall, 2005.

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25

Wainer, Gabriel A. Discrete-Event Modeling and Simulation: A Practitioner's Approach. Taylor & Francis Group, 2017.

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26

Wainer, Gabriel A. Discrete-Event Modeling and Simulation: A Practitioner's Approach. Taylor & Francis Group, 2017.

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27

Wainer, Gabriel A. Discrete-Event Modeling and Simulation: A Practitioner's Approach. Taylor & Francis Group, 2017.

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28

Wainer, Gabriel A., and Pieter J. Mosterman. Discrete-Event Modeling and Simulation: Theory and Applications. Taylor & Francis Group, 2018.

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29

Wainer, Gabriel A. Discrete-Event Modeling and Simulation: A Practitioner's Approach. Taylor & Francis Group, 2017.

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30

Wainer, Gabriel A., and Pieter J. Mosterman. Discrete-Event Modeling and Simulation: Theory and Applications. Taylor & Francis Group, 2018.

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31

Wainer, Gabriel A., and Pieter J. Mosterman. Discrete-Event Modeling and Simulation: Theory and Applications. Taylor & Francis Group, 2018.

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32

Wainer, Gabriel A., and Pieter J. Mosterman. Discrete-Event Modeling and Simulation: Theory and Applications. Taylor & Francis Group, 2018.

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33

Mahulea, Cristian, Marius Kloetzer, and Ramon Gonzalez. Path Planning of Cooperative Mobile Robots Using Discrete Event Models. Wiley & Sons, Incorporated, John, 2020.

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34

Mahulea, Cristian, Marius Kloetzer, and Ramon Gonzalez. Path Planning of Cooperative Mobile Robots Using Discrete Event Models. Wiley-Interscience, 2020.

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35

Mahulea, Cristian, Marius Kloetzer, and Ramon Gonzalez. Path Planning of Cooperative Mobile Robots Using Discrete Event Models. Wiley & Sons, Limited, John, 2020.

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36

Mahulea, Cristian, Marius Kloetzer, and Ramon Gonzalez. Path Planning of Cooperative Mobile Robots Using Discrete Event Models. Wiley & Sons, Incorporated, John, 2020.

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37

Varaiya, P. Discrete Event Systems: Models and Applications (Lecture Notes in Control and Information Sciences). Springer-Verlag, 1988.

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38

Discrete Event Systems: Models and Applications, IASA Conference, Sopron, Hungary, August 3-7, 1987. Berlin: Springer-Verlag, 1988.

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39

Analysis, Design, Implementation and Evaluation of Graphical Design Tool to Develop Discrete Event Simulation Models Using Event Graphs and Simkit. Storming Media, 2001.

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40

(Editor), Hessam S. Sarjoughian, and Francois E. Cellier (Editor), eds. Discrete Event Modeling and Simulation Technologies: A Tapestry of Systems and AI-Based Theories and Methodologies. Springer, 2001.

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41

Chen, Chun Hung. Stochastic Simulation Optimization for Discrete Event Systems: Perturbation Analysis, Ordinal Optimization and Beyond. World Scientific Publishing Co Pte Ltd, 2013.

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42

Cao, Xi-Ren. Stochastic Learning and Optimization: A Sensitivity-Based Approach (International Series on Discrete Event Dynamic Systems). Springer, 2007.

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43

Modeling and Control of Discrete-event Dynamic Systems: With Petri Nets and Other Tools (Advanced Textbooks in Control and Signal Processing). Springer, 2007.

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44

Discrete Event Simulation and Modeling (Model-Based Design). CRC, 2009.

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45

Hadjicostis, Christoforos N. Estimation and Inference in Discrete Event Systems: A Model-Based Approach with Finite Automata. Springer, 2019.

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46

Hadjicostis, Christoforos N. Estimation and Inference in Discrete Event Systems: A Model-Based Approach with Finite Automata. Springer International Publishing AG, 2020.

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47

Elwood, Mark. Chance variation. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199682898.003.0008.

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This chapter explains chance variation and statistical tests, including discrete and continuous measures, the concept of significance, one and two sided test, exact tests, precision and confidence limits. It shows tests of differences in proportions and chi-square tests, the Mantel-Haenszel test, and calculation of confidence limits, for simple tables and for stratified data. It covers heterogeneity tests, multiplicative and additive models, ordered exposure variables and tests of trend. It explains statistical tests for matched studies and in multivariate models. Multiple testing, the Bonferroni correction, issues of hypothesis testing and hypothesis generation, and subgroup analyses are discussed. Stopping rules and repeated testing in trials is covered. It explains how to calculate study power and the necessary size of the study. The chapter describes time to event analysis, including survival curves, product-limit and actuarial or life-table methods, and the calculation of confidence limits, relative survival ratios, the log rank test with control for confounding, and multivariate analysis.
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48

Syndevs Codesign Flow A Hardwaresoftware Codesign Flow Based On Discrete Event System Specification Model Of Computation. Springer Vieweg, 2013.

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49

P, Roderick, National Co-ordinating Centre for HTA (Great Britain), and Health Technology Assessment Programme, eds. The Cost-effectiveness of screening for helicobacter pylori to reduce mortality and morbidity from gastric cancer and peptic ulcer disease: A discrete-event simulation model. Alton: Core Research on behalf of the NCCHTA, 2003.

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50

Wright, A. G. Electronics for PMTs. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199565092.003.0014.

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Photomultipliers (PMTs) are current generators characterized by high gain, wide bandwidth, and high-output impedance. The role of preamplifiers and amplifiers is generally one of conditioning the PMT output. Either the time signature is preserved using a fast voltage preamplifier, or a voltage proportional to the charge in each event is generated with a charge-sensitive preamplifier. Both preamplifier types are generally of low-output impedance, suitable for driving matched coaxial cable. Preamplifiers and amplifiers are available as modular units (e.g. nuclear instrument module), stand alone, or are incorporated in a module including the PMT. Shaping amplifiers are used to further condition preamplifier signals, using integrating and differentiating circuits—particularly relevant to scintillation spectrometers. Discrete-component amplifiers and current-feedback operational amplifiers serve fast applications. Digital signal processing has overtaken many of the classical electronic techniques involving resolution and in pulse shape discrimination. Electronic circuitry for generating fast LED pulses is discussed.
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