Search results for "VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411"

showing 10 items of 57 documents

A Partial Robust M-Regression-Based Prediction and Fault Detection Method

2014

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/304754 Open Access Due to its simplicity and easy implementation, partial least squares (PLS) serves as an efficient approach in large-scale industrial process. However, like many data-based methods, PLS is quite sensitive to outliers, which is a common abnormal characteristic of the measured process data that can significantly affect the monitoring performance of PLS. In order to develop a robust prediction and fault detection method, this paper employs the partial robust M-regression (PRM) to deal with the outliers. Moreover, to eliminate the …

Article Subjectlcsh:MathematicsApplied MathematicsAnalysis; Applied Mathematicslcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411AnalysisAbstract and Applied Analysis
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A filtering algorithm for maneuvering target tracking based on smoothing spline fitting

2014

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/127643 Open Access Maneuvering target tracking is a challenge. Target's sudden speed or direction changing would make the common filtering tracker divergence. To improve the accuracy of maneuvering target tracking, we propose a tracking algorithm based on spline fitting. Curve fitting, based on historical point trace, reflects the mobility information. The innovation of this paper is assuming that there is no dynamic motion model, and prediction is only based on the curve fitting over the measured data. Monte Carlo simulation results show that, …

Article Subjectlcsh:MathematicsApplied MathematicsMonte Carlo methodSpline fittingAnalysis; Applied MathematicsTracking (particle physics)lcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Smoothing splineCurve fittingPoint (geometry)Divergence (statistics)AlgorithmAnalysisTRACE (psycholinguistics)Mathematics
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Stabilization of positive switched systems with time-varying delays under asynchronous switching

2014

Published version of an article in the journal: International Journal of Control, Automation and Systems. Also available from the publisher at: http://dx.doi.org/10.1007/s12555-013-0486-x This paper investigates the state feedback stabilization problem for a class of positive switched systems with time-varying delays under asynchronous switching in the frameworks of continuous-time and discrete-time dynamics. The so-called asynchronous switching means that the switches between the candidate controllers and system modes are asynchronous. By constructing an appropriate co-positive type Lyapunov-Krasovskii functional and further allowing the functional to increase during the running time of ac…

Asynchronous switchingpositive systemsAsynchronous switching; average dwell time; positive systems; switched systems; time-varying delays; Control and Systems Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognitionbusiness.industryComputer scienceControl (management)time-varying delaysComputer Science Applications1707 Computer Vision and Pattern RecognitionRoboticsControl engineeringPositive systemsMechatronicsVDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411AutomationComputer Science ApplicationsControl and Systems EngineeringAsynchronous communicationswitched systemsArtificial intelligencebusinessaverage dwell timeInternational Journal of Control, Automation and Systems
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Oscillatory Behavior of Second-Order Nonlinear Neutral Differential Equations

2014

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/143614 Open Access We study oscillatory behavior of solutions to a class of second-order nonlinear neutral differential equations under the assumptions that allow applications to differential equations with delayed and advanced arguments. New theorems do not need several restrictive assumptions required in related results reported in the literature. Several examples are provided to show that the results obtained are sharp even for second-order ordinary differential equations and improve related contributions to the subject.

Class (set theory)Article SubjectDifferential equationlcsh:MathematicsApplied MathematicsDelay differential equationlcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Integrating factorExamples of differential equationsStochastic partial differential equationNonlinear systemOrdinary differential equationCalculusApplied mathematicsAnalysisMathematicsAbstract and Applied Analysis
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Asymptotic Behavior of Higher-Order Quasilinear Neutral Differential Equations

2014

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/395368 Open Access We study asymptotic behavior of solutions to a class of higher-order quasilinear neutral differential equations under the assumptions that allow applications to even- and odd-order differential equations with delayed and advanced arguments, as well as to functional differential equations with more complex arguments that may, for instance, alternate indefinitely between delayed and advanced types. New theorems extend a number of results reported in the literature. Illustrative examples are presented.

Class (set theory)Article SubjectDifferential equationlcsh:MathematicsApplied MathematicsMathematical analysisDelay differential equationlcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Stochastic partial differential equationExamples of differential equationsOrder (group theory)Neutral differential equationsAnalysisMathematics
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Model approximation for two-dimensional Markovian jump systems with state-delays and imperfect mode information

2014

Published version of an article in the journal: Multidimensional Systems and Signal Processing. Also available from the publisher at: http://dx.doi.org/10.1007/s11045-013-0276-x This paper is concerned with the problem of {Mathematical expression} model approximation for a class of two-dimensional (2-D) discrete-time Markovian jump linear systems with state-delays and imperfect mode information. The 2-D system is described by the well-known Fornasini-Marchesini local state-space model, and the imperfect mode information in the Markov chain simultaneously involves the exactly known, partially unknown and uncertain transition probabilities. By using the characteristics of the transition proba…

Class (set theory)Mathematical optimizationMarkov chainmodel approximationApplied Mathematicstwo-dimensional systemsMarkovian jump systemsRegular polygonMode (statistics)imperfect mode informationState (functional analysis)VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Computer Science ApplicationsMarkovian jumpMarkovian jump linear systemsArtificial IntelligenceHardware and ArchitectureSignal ProcessingApplied mathematicsstate-delaysImperfectSoftwareInformation SystemsMathematics
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A new paradigm for pattern classification: Nearest Border Techniques

2013

Published version of a chapter in the book: AI 2013: Advances in Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-319-03680-9_44 There are many paradigms for pattern classification. As opposed to these, this paper introduces a paradigm that has not been reported in the literature earlier, which we shall refer to as the Nearest Border (NB) paradigm. The philosophy for developing such a NB strategy is as follows: Given the training data set for each class, we shall first attempt to create borders for each individual class. After that, we advocate that testing is accomplished by assigning the test sample to the class whose border it lies closest to…

Class (set theory)Training setPattern ClassificationComputer sciencebusiness.industrySVMVDP::Mathematics and natural science: 400::Information and communication science: 420::Algorithms and computability theory: 422Centroid02 engineering and technology01 natural sciencesVDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Support vector machine010104 statistics & probabilityExperimental testingOutlier0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligence0101 mathematics10. No inequalitySet (psychology)businessTest sampleBorder Identification
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Finite-Time Distributed Energy-to-Peak Control for Uncertain Multiagent Systems

2014

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/260201 Open Access This paper investigates the finite-time distributed L2-L∞ consensus control problem of multiagent systems with parameter uncertainties. The relative states of neighboring agents are used to construct the control law and some agents know their own states. By substituting the control input into multiagent systems, an augmented closed-loop system is obtained. Then, we analyze its finite-time boundedness (FTB) and finite-time L2-L∞ performance. A sufficient condition for the existence of the designed controller is given with the f…

Computer Science::Multiagent SystemsArticle SubjectApplied Mathematicslcsh:MathematicsAnalysis; Applied Mathematicslcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411AnalysisAbstract and Applied Analysis
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Study on Support Vector Machine-Based Fault Detection in Tennessee Eastman Process

2014

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/836895 Open Access This paper investigates the proficiency of support vector machine (SVM) using datasets generated by Tennessee Eastman process simulation for fault detection. Due to its excellent performance in generalization, the classification performance of SVM is satisfactory. SVM algorithm combined with kernel function has the nonlinear attribute and can better handle the case where samples and attributes are massive. In addition, with forehand optimizing the parameters using the cross-validation technique, SVM can produce high accuracy i…

ComputingMethodologies_PATTERNRECOGNITIONArticle SubjectApplied Mathematicslcsh:MathematicsAnalysis; Applied Mathematicslcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411AnalysisAbstract and Applied Analysis
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A mahalanobis hyperellipsoidal learning machine class incremental learning algorithm

2014

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/894246 Open Access A Mahalanobis hyperellipsoidal learning machine class incremental learning algorithm is proposed. To each class sample, the hyperellipsoidal that encloses as many as possible and pushes the outlier samples away is trained in the feature space. In the process of incremental learning, only one subclassifier is trained with the new class samples. The old models of the classifier are not influenced and can be reused. In the process of classification, considering the information of sample's distribution in the feature space, the Ma…

ComputingMethodologies_PATTERNRECOGNITIONArticle SubjectApplied Mathematicslcsh:MathematicsAnalysis; Applied Mathematicslcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Analysis
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