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Dissertations / Theses on the topic 'Stochastic processing networks'

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1

Lin, Wuqin. "Dynamic Control in Stochastic Processing Networks." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7105.

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A stochastic processing network is a system that takes materials of various kinds as inputs, and uses processing resources to produce other materials as outputs. Such a network provides a powerful abstraction of a wide range of real world, complex systems, including semiconductor wafer fabrication facilities, networks of data switches, and large-scale call centers. Key performance measures of a stochastic processing network include throughput, cycle time, and holding cost. The network performance can dramatically be affected by the choice of operational policies. We propose a family of operat
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2

Zhong, Yuan Ph D. Massachusetts Institute of Technology Operations Research Center. "Resource allocation in stochastic processing networks : performance and scaling." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/77828.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2012.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 189-193).<br>This thesis addresses the design and analysis of resource allocation policies in largescale stochastic systems, motivated by examples such as the Internet, cloud facilities, wireless networks, etc. A canonical framework for modeling many such systems is provided by "stochastic processing networks" (SPN) (Harrison [28, 29]). In this context, the key operational challenge is efficient
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3

Rising, Barry John Paul. "Hardware architectures for stochastic bit-stream neural networks : design and implementation." Thesis, Royal Holloway, University of London, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326219.

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4

Ling, Hong. "Implementation of Stochastic Neural Networks for Approximating Random Processes." Master's thesis, Lincoln University. Environment, Society and Design Division, 2007. http://theses.lincoln.ac.nz/public/adt-NZLIU20080108.124352/.

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Artificial Neural Networks (ANNs) can be viewed as a mathematical model to simulate natural and biological systems on the basis of mimicking the information processing methods in the human brain. The capability of current ANNs only focuses on approximating arbitrary deterministic input-output mappings. However, these ANNs do not adequately represent the variability which is observed in the systems’ natural settings as well as capture the complexity of the whole system behaviour. This thesis addresses the development of a new class of neural networks called Stochastic Neural Networks (SNNs) in
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5

Rogge-Solti, Andreas, Ronny S. Mans, der Aalst Wil M. P. van, and Mathias Weske. "Repairing event logs using stochastic process models." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6679/.

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Companies strive to improve their business processes in order to remain competitive. Process mining aims to infer meaningful insights from process-related data and attracted the attention of practitioners, tool-vendors, and researchers in recent years. Traditionally, event logs are assumed to describe the as-is situation. But this is not necessarily the case in environments where logging may be compromised due to manual logging. For example, hospital staff may need to manually enter information regarding the patient’s treatment. As a result, events or timestamps may be missing or incorrect. I
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6

Liu, Kai. "Detecting stochastic motifs in network and sequence data for human behavior analysis." HKBU Institutional Repository, 2014. https://repository.hkbu.edu.hk/etd_oa/60.

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With the recent advent of Web 2.0, mobile computing, and pervasive sensing technologies, human activities can readily be logged, leaving digital traces of di.erent forms. For instance, human communication activities recorded in online social networks allow user interactions to be represented as “network” data. Also, human daily activities can be tracked in a smart house, where the log of sensor triggering events can be represented as “sequence” data. This thesis research aims to develop computational data mining algorithms using the generative modeling approach to extract salient patterns (mot
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7

Brown, Louise Eleanor. "Asymptotic behaviour of an overloading queueing network with resource pooling." Diss., Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/25644.

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8

Rogge-Solti, Andreas. "Probabilistic Estimation of Unobserved Process Events." Phd thesis, Universität Potsdam, 2014. http://opus.kobv.de/ubp/volltexte/2014/7042/.

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Organizations try to gain competitive advantages, and to increase customer satisfaction. To ensure the quality and efficiency of their business processes, they perform business process management. An important part of process management that happens on the daily operational level is process controlling. A prerequisite of controlling is process monitoring, i.e., keeping track of the performed activities in running process instances. Only by process monitoring can business analysts detect delays and react to deviations from the expected or guaranteed performance of a process instance. To enable
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9

Aguiar, Eliane Martins de. "Aplicação do Word2vec e do Gradiente descendente dstocástico em tradução automática." reponame:Repositório Institucional do FGV, 2016. http://hdl.handle.net/10438/16798.

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Submitted by Eliane Martins de Aguiar (elianemart@gmail.com) on 2016-08-01T21:03:09Z No. of bitstreams: 1 dissertacao-ElianeMartins.pdf: 6062037 bytes, checksum: 14567c2feca25a81d6942be3b8bc8a65 (MD5)<br>Approved for entry into archive by Janete de Oliveira Feitosa (janete.feitosa@fgv.br) on 2016-08-03T20:29:34Z (GMT) No. of bitstreams: 1 dissertacao-ElianeMartins.pdf: 6062037 bytes, checksum: 14567c2feca25a81d6942be3b8bc8a65 (MD5)<br>Approved for entry into archive by Maria Almeida (maria.socorro@fgv.br) on 2016-08-23T20:12:35Z (GMT) No. of bitstreams: 1 dissertacao-ElianeMartins.pdf: 606
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10

Dionigi, Pierfrancesco. "A random matrix theory approach to complex networks." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18513/.

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Si presenta un approccio matematico formale ai complex networks tramite l'uso della Random Matrix Theory (RMT). La legge del semicerchio di Wigner viene presentata come una generalizzazione del Teorema del Limite Centrale per determinati ensemble di matrici random. Sono presentati inoltre i principali metodi per calcolare la distribuzione spettrale delle matrici random e se ne sottolineano le differenze. Si è poi studiato come la RMT sia collegata alla Free Probability. Si è studiato come due tipi di grafi random apparentemente uguali, posseggono proprietà spettrali differenti analizzando le l
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11

Malmgren, Henrik. "Revision of an artificial neural network enabling industrial sorting." Thesis, Uppsala universitet, Institutionen för teknikvetenskaper, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-392690.

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Convolutional artificial neural networks can be applied for image-based object classification to inform automated actions, such as handling of objects on a production line. The present thesis describes theoretical background for creating a classifier and explores the effects of introducing a set of relatively recent techniques to an existing ensemble of classifiers in use for an industrial sorting system.The findings indicate that it's important to use spatial variety dropout regularization for high resolution image inputs, and use an optimizer configuration with good convergence properties. T
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12

Bol, Kieran G. "Redundant Input Cancellation by a Bursting Neural Network." Thèse, Université d'Ottawa / University of Ottawa, 2011. http://hdl.handle.net/10393/20061.

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One of the most powerful and important applications that the brain accomplishes is solving the sensory "cocktail party problem:" to adaptively suppress extraneous signals in an environment. Theoretical studies suggest that the solution to the problem involves an adaptive filter, which learns to remove the redundant noise. However, neural learning is also in its infancy and there are still many questions about the stability and application of synaptic learning rules for neural computation. In this thesis, the implementation of an adaptive filter in the brain of a weakly electric fish, A. Lepto
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13

Adusumilli, Kranthi Mitra 1979. "Scheduling and control of stochastic processing networks." Thesis, 2007. http://hdl.handle.net/2152/3167.

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14

Gupta, Manish. "Stochastic Models, Stability And Performance Analysis Of Distributed Simulators Of Queueing Networks." Thesis, 1998. http://etd.iisc.ernet.in/handle/2005/1558.

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15

Ashraf, Manzur. "Channel based medium access control for ad hoc wireless networks." 2009. http://arrow.unisa.edu.au:8081/1959.8/92176.

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Opportunistic communication techniques have shown to provide significant performance improvements in centralised random access wireless networks. The key mechanism of opportunistic communication is to send back-to-back data packets whenever the channel quality is deemed "good". Recently there have been attempts to introduce opportunistic communication techniques in distributed wireless networks such as wireless ad hoc networks. In line of this research, we propose a new paradigm of medium access control, called Channel MAC based on the channel randomness and opportunistic communication princip
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16

Prem, Hema. "Architecting Resource Management Services For Computational Grids : Patterns And Performance Models." Thesis, 2005. http://etd.iisc.ernet.in/handle/2005/1419.

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17

Abdulla, Mohammed Shahid. "Simulation Based Algorithms For Markov Decision Process And Stochastic Optimization." Thesis, 2008. http://hdl.handle.net/2005/812.

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In Chapter 2, we propose several two-timescale simulation-based actor-critic algorithms for solution of infinite horizon Markov Decision Processes (MDPs) with finite state-space under the average cost criterion. On the slower timescale, all the algorithms perform a gradient search over corresponding policy spaces using two different Simultaneous Perturbation Stochastic Approximation (SPSA) gradient estimates. On the faster timescale, the differential cost function corresponding to a given stationary policy is updated and averaged for enhanced performance. A proof of convergence to a locally op
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