Search results for "Linear"

showing 10 items of 7165 documents

Backward Frequency Doubling in Periodically Poled Lithium Niobate in the Pulsed Regime

2011

Settore ING-INF/02 - Campi ElettromagneticiSettore ING-INF/01 - ElettronicaNonlinear Optics Backward Frequency Doubling Lithium Niobate
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Adaptive Feedback Linearization Control of SynRM Drives With On-Line Inductance Estimation

2023

This article proposes an adaptive input-output Feedback Linearization Control ( FLC ) techniques for Synchronous Reluctance Motor ( SynRM ) drives, taking into consideration the iron losses. As a main original content, this work proposes a control law based on a new dynamic model of the SynRM including iron losses as well as the on-line estimation of the static inductances. The on-line estimation of the SynRM static inductances permits to inherently take into consideration the magnetic saturation phenomena occuring on both axes. As a major result, it permits a null stator current steady state tracking error even with a proportional derivative controller. The estimation law is obtained thank…

Settore ING-INF/04 - AutomaticaControl and Systems EngineeringAdaptive system feedback linearization control FLC inductances estimation synchronous reluctance motor SynRMElectrical and Electronic EngineeringIndustrial and Manufacturing EngineeringIEEE Transactions on Industry Applications
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Fondamenti di Automatica non Lineare

2009

Settore ING-INF/04 - AutomaticaFondamenti Automatica Lineare
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MRAS Sensorless Techniques for High Performance Linear Induction Motor Drives.

2010

This paper proposes an MRAS (Model reference Adaptive System) speed observer suited for linear induction motors (LIM). Starting from the dynamical equation of the LIM in the synchronous reference frame in literature, the so-called voltage and current models of the LIM in the stationary reference frame, taking into consideration the end effects, have been deduced. These equations have been used respectively as reference and adaptive model of an MRAS observer. As machine under test, a complete dynamic model, based on the constructive elements of the LIM and taking into consideration the end effects by the definition of a proper air-gap function, has been adopted. This model has been previousl…

Settore ING-INF/04 - AutomaticaLinear Induction Motor (LIM) Sensorless control Model Reference Adaptive Systems (MRAS) Field Oriented Control (FOC).
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Innovative Observers for Induction Motor Control

In this thesis the problem of designing observers and controllers for induction motors has been studied and thoroughly discussed using tools from the nonlinear system theory, both for analysis and control purposes. Useful techniques have been used to identify the machine parameters off-line. In the Introduction was dealt the design a control system for a drive of asynchronous machines that uses a voltage source inverter to generate the currents and voltages which carry the drive by making use of an observer of the state rotor variables. The used control algorithms is the \textit{field oriented control} (FOC). The model of the asynchronous induction motor is described starting from the mecha…

Settore ING-INF/04 - AutomaticaObservers Induction Motor Control Asynchronous Motor Luenberger Sliding Kalman Non Linear Observer
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Springs-based Simulation for Image Retargeting

2011

In this paper an efficient method for image retargeting is pro- posed. It relies onto a mechanical model based on springs network. Each pixel displacement (compression or expan- sion) is given by the network response, according to the springs stiffness. The properties of the springs are deter- mined as function of the visual relevance of the pixels. Such model does not require any optimization, since its so- lution is obtained simply from a linear system of equations, allowing real-time application even for large images. The approach is fully automatic, though can be improved by interactively providing cues such as geometric constraints and/or manual relevant object labeling. The results pr…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniImage resizing Image retargeting simu- lation linear algebra visual saliencyPixelComputer sciencebusiness.industryStiffnessImage processingSystem of linear equationsDisplacement (vector)VisualizationSeam carvingmedicineComputer visionArtificial intelligencemedicine.symptombusiness
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Real-Time Object Detection in Embedded Video Surveillance Systems

2008

In this paper we report a new method to detect both moving objects and new stationary objects in video sequences. On the basis of temporal consideration we classify pixels into three classes: background, midground and foreground to distinguish between long-term, medium-term and short-term changes. The algorithm has been implemented on a hardware platform with limited resources and it could be used in a wider system like a wireless sensor networks. Particular care has been put in realizing the algorithm so that the limited available resources are used in an efficient way. Experiments have been conducted on publicly available datasets and performance measures are reported.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniPixelBasis (linear algebra)business.industryComputer scienceReal-time computingVideo sequencevideo surveillance embedded systemsObject detectionTerm (time)Statistical classificationComputer visionArtificial intelligencebusinessWireless sensor networkLimited resources2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services
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Real-time content-aware image resizing using reduced linear model

2010

In this paper an effective and efficient method for contentaware image resizing is proposed. It is based on the solution of a linear system where each pixel displacement (compression or expansion) is determined in dependence of the visual relevance of the pixel itself. The linear nature of the model allows real-time application of the method even for large images. This fully automatic approach can be also improved by interactively providing cues such as geometric constraints and/or manual relevant object labeling. The results have proven that the presented method achieves results comparable or superior to existent strategies, while improving efficiency.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniPixelImage resizing Image retargeting linear optimization visual saliencyPhysics::Instrumentation and Detectorsbusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONLinear modelIterative reconstructionDisplacement (vector)Computer Science::GraphicsSeam carvingComputer Science::Computer Vision and Pattern RecognitionComputer Science::MultimediaComputer visionArtificial intelligencebusinessImage resolutionComputingMethodologies_COMPUTERGRAPHICS2010 IEEE International Conference on Image Processing
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Hankelet-based dynamical systems modeling for 3D action recognition

2015

This paper proposes to model an action as the output of a sequence of atomic Linear Time Invariant (LTI) systems. The sequence of LTI systems generating the action is modeled as a Markov chain, where a Hidden Markov Model (HMM) is used to model the transition from one atomic LTI system to another. In turn, the LTI systems are represented in terms of their Hankel matrices. For classification purposes, the parameters of a set of HMMs (one for each action class) are learned via a discriminative approach. This work proposes a novel method to learn the atomic LTI systems from training data, and analyzes in detail the action representation in terms of a sequence of Hankel matrices. Extensive eval…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSequenceMarkov chainDynamical systems theorySupervised learningHankel MatrixHidden Markov ModelLTI system theoryDiscriminative learningLinear time invariant systemDiscriminative modelActionComputer Science::Systems and ControlControl theorySignal ProcessingComputer Vision and Pattern RecognitionElectrical and Electronic EngineeringHidden Markov modelHankel matrixAlgorithmMathematicsImage and Vision Computing
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On Representing Concepts in High-dimensional Linear Spaces

2017

Producing a mathematical model of concepts is a very important issue in artificial intelligence, because if such a model were found this, besides being a very interesting result in its own right, would also contribute to the emergence of what we could call the ‘mathematics of thought.’ One of the most interesting attempts made in this direction is P. Gardenfors’ theory of conceptual spaces, a ¨ theory which is mostly presented by its author in an informal way. The main aim of the present article is contributing to Gardenfors’ theory of conceptual spaces ¨ by discussing some of the advantages which derive from the possibility of representing concepts in high-dimensional linear spaces.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore M-FIL/02 - Logica E Filosofia Della ScienzaConcepts Linear Spaces Kernels Machine Learning
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