Search results for "Markov"

showing 10 items of 628 documents

Neural Network Based Finite-Time Stabilization for Discrete-Time Markov Jump Nonlinear Systems with Time Delays

2013

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2013/359265 Open Access This paper deals with the finite-time stabilization problem for discrete-time Markov jump nonlinear systems with time delays and norm-bounded exogenous disturbance. The nonlinearities in different jump modes are parameterized by neural networks. Subsequently, a linear difference inclusion state space representation for a class of neural networks is established. Based on this, sufficient conditions are derived in terms of linear matrix inequalities to guarantee stochastic finite-time boundedness and stochastic finite-time stabi…

Time delaysArticle SubjectState-space representationArtificial neural networklcsh:MathematicsApplied MathematicsParameterized complexitylcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Nonlinear systemDiscrete time and continuous timeControl theoryJumpAnalysisMathematicsMarkov jumpAbstract and Applied Analysis
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Notice of Violation of IEEE Publication Principles: Robust Delay-Dependent $H_{\infty}$ Control of Uncertain Time-Delay Systems With Mixed Neutral, D…

2011

The problem of robust mode-dependent delayed state feedback H∞ control is investigated for a class of uncertain time-delay systems with Markovian switching parameters and mixed discrete, neutral, and distributed delays. Based on the Lyapunov-Krasovskii functional theory, new required sufficient conditions are established in terms of delay-dependent linear matrix inequalities for the stochastic stability and stabilization of the considered system using some free matrices. The desired control is derived based on a convex optimization method such that the resulting closed-loop system is stochastically stable and satisfies a prescribed level of H∞ performance, simultaneously. Finally, two numer…

Time delaysMarkov processDelay dependentsymbols.namesakeHardware and ArchitectureRobustness (computer science)Control theoryConvex optimizationsymbolsElectrical and Electronic EngineeringRobust controlMarkovian switchingFunctional theoryMathematicsIEEE Transactions on Circuits and Systems I: Regular Papers
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Exponential stability analysis of Markovian jump nonlinear systems with mixed time delays and partially known transition probabilities

2013

In this paper, the problem of exponential stability is studied for a class of Markovian jump neutral nonlinear systems with mixed neutral and discrete time delays. By Lyapunov-Krasovskii function approach, a novel mean-square exponential stability criterion is derived for the situation that the system's transition rates are partially or completely accessible. Finally, some numerical examples are provided to illustrate the effectiveness of the proposed methods.

Time delayssymbols.namesakeNonlinear systemMarkovian jumpDiscrete time and continuous timeExponential stabilityControl theorysymbolsApplied mathematicsMarkov processCircle criterionFunction (mathematics)Mathematics2013 XXIV International Conference on Information, Communication and Automation Technologies (ICAT)
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A methodology and algorithms for an optimal identification of Tourist Local Systems

2007

In last years, despite the emphasis on the importance of tourism as a leading industry in the development of a country’s economy, there is a lack of criteria and methodologies for the identification, the promotion and the governance of Tourism Local Systems (TLS). Moreover, nowadays an important debate is more and more emerging on the sustainable tourism development which involve three interconnected aspects: environmental, socio-cultural and economic. To this end, in this paper, a rigorous mathematical model is proposed for the optimal identification and dimensioning of TLS. The model here presented consists of a two stage methodology: at first, all the factors that characterize a geograph…

Tourist Local Systems Markov Chain Decision Trees Dynamic Programming
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Learning the structure of HMM's through grammatical inference techniques

2002

A technique is described in which all the components of a hidden Markov model are learnt from training speech data. The structure or topology of the model (i.e. the number of states and the actual transitions) is obtained by means of an error-correcting grammatical inference algorithm (ECGI). This structure is then reduced by using an appropriate state pruning criterion. The statistical parameters that are associated with the obtained topology are estimated from the same training data by means of the standard Baum-Welch algorithm. Experimental results showing the applicability of this technique to speech recognition are presented. >

Training setbusiness.industryComputer scienceEstimation theorySpeech recognitionMarkov processComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)Pattern recognitionGrammar inductionsymbols.namesakeRule-based machine translationsymbolsArtificial intelligencePruning (decision trees)businessBaum–Welch algorithmHidden Markov modelError detection and correctionInternational Conference on Acoustics, Speech, and Signal Processing
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A sliding mode approach to H∞ synchronization of master–slave time-delay systems with Markovian jumping parameters and nonlinear uncertainties

2012

Author's version of an article published in the journal: Journal of the Franklin Institute. Also available from the publisher at: http://dx.doi.org/10.1016/j.jfranklin.2011.09.015 In this paper, a sliding-mode approach is proposed for exponential H∞ synchronization problem of a class of masterslave time-delay systems with both discrete and distributed time-delays, norm-bounded nonlinear uncertainties and Markovian switching parameters. Using an appropriate LyapunovKrasovskii functional, some delay-dependent sufficient conditions and a synchronization law, which include the masterslave parameters are established for designing a delay-dependent mode-dependent sliding mode exponential H∞ synch…

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413Computer Networks and CommunicationsComputer scienceApplied Mathematicssynchronization master-slave systems sliding mode delay H∞ performance nonlinear uncertaintiesVDP::Technology: 500::Mechanical engineering: 570Mode (statistics)Control engineeringMaster/slaveNonlinear systemControl and Systems EngineeringControl theorySignal ProcessingSynchronization (computer science)Markovian jumpingJournal of the Franklin Institute
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On the analysis of a new Markov chain which has applications in AI and machine learning

2011

Accepted version of an article from the conference: 2011 24th Canadian Conference on Electrical and Computer Engineering. Published version available from IEEE: http://dx.doi.org/10.1109/CCECE.2011.6030727 In this paper, we consider the analysis of a fascinating Random Walk (RW) that contains interleaving random steps and random "jumps". The characterizing aspect of such a chain is that every step is paired with its counterpart random jump. RWs of this sort have applications in testing of entities, where the entity is never allowed to make more than a pre-specified number of consecutive failures. This paper contains the analysis of the chain, some fascinating limiting properties, and some i…

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413InterleavingMarkov chainComputer sciencebusiness.industryStochastic processMarkov processVDP::Technology: 500::Information and communication technology: 550Machine learningcomputer.software_genreRandom walksymbols.namesakeChain (algebraic topology)symbolssortArtificial intelligencebusinesscomputer
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Spectral adaptation of hyperspectral flight lines using VHR contextual information

2014

Abstract: Due to technological constraints, hyperspectral earth observation imagery are often a mosaic of overlapping flight lines collected in different passes over the area of interest. This causes variations in aqcuisition conditions such that the reflected spectrum can vary significantly between these flight lines. Partly, this problem is solved by atmospherical correction, but residual spectral differences often remain. A probabilistic domain adaptation framework based on graph matching using Hidden Markov Random Fields was recently proposed for transforming hyperspectral data from one image to better correspond to the other. This paper investigates the use of scale and angle invariant…

VHR imageryHyperspectral imaginggraph matchingComputer sciencebusiness.industrydomain adaptationPhysicsHyperspectral imagingPattern recognitionFilter (signal processing)Rendering (computer graphics)Computer Science::Computer Vision and Pattern RecognitionFull spectral imagingtextural featuresComputer visionArtificial intelligenceHidden Markov random fieldHidden Markov modelbusiness
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Statistical Dependence and Independence

2005

Statistical dependence is a type of relation between different characteristics measured on the same units. At one extreme is deterministic dependence; at the other is statistical independence, where the distribution of one variable is the same for all levels of the other. With more than two variables, an important distinction is between marginal and conditional dependence. In many contexts, the degree of dependence may be summarized by a suitable measure of association, perhaps as part of a general model. Reference is made to graphical models. Keywords: association; correlation; marginal; conditional; exponential family; graphical Markov models

Variable (computer science)Conditional dependenceExponential familyDistribution (mathematics)Variable-order Markov modelStatisticsEconometricsGraphical modelMarkov modelDegree (music)Independence (probability theory)MathematicsEncyclopedia of Biostatistics
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Joint Alignment and Modeling of Correlated Behavior Streams

2013

The Variable Time-Shift Hidden Markov Model (VTS- HMM) is proposed for learning and modeling pairs of cor- related streams. Unlike previous coupled models for time series, the VTS-HMM accounts for varying time shifts be- tween correlated events in pairs of streams having different properties. The VTS-HMM is learned on a set of pairs of unaligned streams and, thus, learning entails simultaneous estimation of the varying time shifts and of the parameters of the model. The formulation is demonstrated in the analysis of videos of dyadic social interactions between children and adults in the Multimodal Dyadic Behavior Dataset (MMDB). In dyadic social interactions, an agent starts an interaction …

Variable (computer science)Series (mathematics)Computer scienceMulti-agent systemSpeech recognitionDyadic interactionBehavior Modeling Autism Dyadic InteractionSTREAMSSet (psychology)Hidden Markov modelVisualization
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