Search results for "Markov"

showing 8 items of 628 documents

Can the adaptive Metropolis algorithm collapse without the covariance lower bound?

2011

The Adaptive Metropolis (AM) algorithm is based on the symmetric random-walk Metropolis algorithm. The proposal distribution has the following time-dependent covariance matrix at step $n+1$ \[ S_n = Cov(X_1,...,X_n) + \epsilon I, \] that is, the sample covariance matrix of the history of the chain plus a (small) constant $\epsilon>0$ multiple of the identity matrix $I$. The lower bound on the eigenvalues of $S_n$ induced by the factor $\epsilon I$ is theoretically convenient, but practically cumbersome, as a good value for the parameter $\epsilon$ may not always be easy to choose. This article considers variants of the AM algorithm that do not explicitly bound the eigenvalues of $S_n$ away …

stabiiliusMetropolis-algoritmiAdaptive Markov chain Monte Carlostochastic approximationstokastinen approksimaatiostabilityadaptiivinen Markov chain Monte CarloMetropolis algorithm
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Counting Berg partitions via Sturmian words and substitution tilings

2013

We develop the connection of Berg partitions with special substitution tilings of two tiles. We obtain a new proof that the number of Berg partitions with a fixed connectivity matrix is equal to half of the sum of its entries, [12]. This approach together with the formula of Seebold [10], for the number of substitutions preserving a given Sturmian sequence, shows that all of the combinatorial substitutions can be realized geometrically as Berg partitions. We treat Sturmian tilings as intersection tilings of bi-partitions. Using the symmetries of bi-partitions we obtain geometrically the palindromic properties of Sturmian sequences (Theorem 3) established combinatorially by de Luca and Migno…

substitutionberg partitionstilingssturmian sequencestoral automorphismsmarkov partitions
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The Poisson Point Process

2020

Poisson point processes can be used as a cornerstone in the construction of very different stochastic objects such as, for example, infinitely divisible distributions, Markov processes with complex dynamics, objects of stochastic geometry and so forth.

symbols.namesakeCompound Poisson distributionComputer sciencePoisson point processCompound Poisson processsymbolsMarkov processStatistical physicsFractional Poisson processLévy processStochastic geometryPoint process
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Robust H<inf>∞</inf> control of Markovian jump systems with mixed time delays

2010

In this paper, the problem of stability analysis and control synthesis for Markovian jump linear systems with time delays and norm-bounded uncertainties is studied. The model under consideration consists of different time-invariant discrete, neutral and distributed delays. Delay-dependent sufficient conditions for the design of a mode-dependent delayed state feedback H ∞ control are given in terms of linear matrix inequalities (LMIs). A controller which guarantees stochastic stability and a prescribed level of H ∞ performance for the closed-loop system is then developed. A Lyapunov-Krasovskii functional (LKF) method underlies the control design. A numerical example with simulation results i…

symbols.namesakeExponential stabilityControl theoryRobustness (computer science)Linear systemsymbolsMarkov processState (functional analysis)Robust controlStability (probability)Mathematics49th IEEE Conference on Decision and Control (CDC)
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Predictive control of networked systems with communication delays

2012

This paper studies the problem of predictive output feedback control for networked control systems with random communication delays. A networked predictive control scheme is employed to compensate for random communication delays, which mainly consists of the control prediction generator and network delay compensator. Furthermore, a new strategy of designing the time-varying predictive controller with mixed random delays for networked systems is proposed. Then the system can be formulated as a Markovian jump system. New techniques are presented to deal with the distributed delay in the discrete-time domain. Based on analysis of closed-loop networked predictive control systems, the designed p…

symbols.namesakeModel predictive controlComputer scienceControl theoryControl systemNetwork delaysymbolsMarkov processControl engineeringNetworked control systemData lossStability (probability)2012 IEEE International Symposium on Intelligent Control
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Sliding mode exponential H<inf>∞</inf> synchronization of Markovian jumping master-slave systems with time-delays and nonlinea…

2011

This paper investigates the problem of exponential H ∞ synchronization for a class of master-slave systems with both discrete and distributed time-delays, norm-bounded nonlinear uncertainties and Markovian switching parameters. Using an appropriate Lyapunov-Krasovskii functional, some delay-dependent sufficient conditions and a synchronization law which include the master-slave parameters are established for designing a delay-dependent mode-dependent sliding mode exponential H ∞ synchronization control law in terms of linear matrix inequalities. The controller guarantees the H ∞ synchronization of the two coupled master and slave systems regardless of their initial states. A numerical examp…

symbols.namesakeNonlinear systemControl theorysymbolsMode (statistics)Markov processMaster/slaveSliding mode controlSynchronizationMathematicsExponential functionIEEE Conference on Decision and Control and European Control Conference
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A comparison between two feature selection algorithms

2017

This article provides a comparison of two feature selection algorithms, Information Gain Thresholding and Koller and Sahami's algorithm in the context of text document classification on the Reuters Corpus Volume 1 dataset. The algorithms were evaluated by testing the performance of classifiers trained on the features they select from a given dataset. Results show that Koller and Sahami's algorithm consistently outperforms Information Gain Thresholding by capturing interactions between features and avoiding redundancy among features, although it achieves its gains through increased complexity and longer running time.

symbols.namesakeTruncation selectionRedundancy (information theory)Computer scienceFeature extractionsymbolsMarkov processFeature selectionAlgorithm designThresholdingAlgorithmRunning time2017 21st International Conference on System Theory, Control and Computing (ICSTCC)
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Learn to Cache: Machine Learning for Network Edge Caching in the Big Data Era

2018

The unprecedented growth of wireless data traffic not only challenges the design and evolution of the wireless network architecture, but also brings about profound opportunities to drive and improve future networks. Meanwhile, the evolution of communications and computing technologies can make the network edge, such as BSs or UEs, become intelligent and rich in terms of computing and communications capabilities, which intuitively enables big data analytics at the network edge. In this article, we propose to explore big data analytics to advance edge caching capability, which is considered as a promising approach to improve network efficiency and alleviate the high demand for the radio resou…

wireless networksContent popularityEdge deviceComputer scienceBig data5G-tekniikkaRadio resource02 engineering and technologyWireless network architecturebig data5G mobile communication0202 electrical engineering electronic engineering information engineeringElectrical and Electronic Engineeringta113: Computer science [C05] [Engineering computing & technology]hidden Markov modelsbusiness.industry020208 electrical & electronic engineeringWireless dataanalytical models020206 networking & telecommunications: Sciences informatiques [C05] [Ingénierie informatique & technologie]Computer Science Applicationsdata modelskoneoppiminenmachine learningdevice-to-device communicationEnhanced Data Rates for GSM EvolutionCachebusinesslangattomat verkotComputer networkIEEE Wireless Communications
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