Search results for "input"

showing 10 items of 213 documents

Local Capacity $H_{\infty}$ Control for Production Networks of Autonomous Work Systems With Time-Varying Delays

2010

This paper considers the problem of local capacity H∞ control for a class of production networks of autonomous work systems with time-varying delays in the capacity changes. The system under consideration is modeled in a discrete-time singular form. Attention is focused on the design of a controller gain for the local capacity adjustments which maintains the work-in-progress (WIP) in each work system in the vicinity of planned levels and guarantees the asymptotic stability of the system and reduces the effect of the disturbance input on the controlled output to a prescribed level. In terms of a matrix inequality, a sufficient condition for the solvability of this problem is presented using …

Lyapunov functionInput/outputdelayAutonomous systems; delay; linear matrix inequality (LMI); production networks; Control and Systems Engineering; Electrical and Electronic EngineeringLinear matrix inequalityAutonomous systemssymbols.namesakeExponential stabilityDiscrete time and continuous timeControl and Systems EngineeringControl theoryConvex optimizationsymbolsproduction networksAutomatic gain controlSymmetric matrixElectrical and Electronic Engineeringlinear matrix inequality (LMI)MathematicsIEEE Transactions on Automation Science and Engineering
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Design of unknown inputs proportional integral observers for TS fuzzy models

2014

In this paper the design of unknown inputs proportional integral observers for Takagi-Sugeno (TS) fuzzy models subject to unmeasurable decision variables is proposed. These unknown inputs affect both state and output of the system. The synthesis of these observers is based on two hypotheses that the unknown inputs are under the polynomials form with their kth derivatives zero for the first one and bounded norm for the second one, hence two approaches. The Lyapunov theory and L"2-gain technique are used to develop the stability conditions of such observers in LMIs (linear matrix inequality) formulation. A simulation example is given to validate and compare the proposed design conditions for …

Lyapunov functionUnknown inputs reconstructionCognitive NeuroscienceLinear matrix inequalityComputer Science Applications1707 Computer Vision and Pattern RecognitionFuzzy logicComputer Science ApplicationsStability conditionssymbols.namesakeDecision variablesComputer Science::Systems and ControlArtificial IntelligenceControl theoryBounded functionNorm (mathematics)Unmeasurable decision variablessymbolsTS fuzzy modelsProportional integral observer; TS fuzzy models; Unknown inputs reconstruction; Unmeasurable decision variables; Artificial Intelligence; Computer Science Applications1707 Computer Vision and Pattern Recognition; Cognitive NeuroscienceProportional integral observerMathematicsNeurocomputing
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On integral input-to-state stability for a feedback interconnection of parameterised discrete-time systems

2014

This paper addresses integral input-to-state stability iISS for a feedback interconnection of parameterised discrete-time systems involving two subsystems. Particularly, we give a construction for a smooth iISS Lyapunov function for the whole system from the sum of nonlinearly weighted Lyapunov functions of individual subsystems. Motivations for such a construction are given. We consider two main cases. The first one investigates iISS for the whole system when both subsystems are iISS. The second one gives iISS for the interconnected system when one of subsystems is allowed to be input-to-state stable. The approach is also valid for both discrete-time cascades and a feedback interconnection…

Lyapunov functionsmall-gain conditions0209 industrial biotechnologyInterconnectionStability (learning theory)Computer Science Applications1707 Computer Vision and Pattern Recognition02 engineering and technologyState (functional analysis)Computer Science ApplicationsWhole systems0-global asymptotic stabilityTheoretical Computer Scienceinput-to-state stabilitysymbols.namesakeparameterised discrete-time systems020901 industrial engineering & automationDiscrete time and continuous timeControl theoryControl and Systems Engineering0202 electrical engineering electronic engineering information engineeringsymbols020201 artificial intelligence & image processing0-global asymptotic stability; input-to-state stability; integral input-to-state stability; parameterised discrete-time systems; small-gain conditions; Control and Systems Engineering; Theoretical Computer Science; Computer Science Applications1707 Computer Vision and Pattern Recognitionintegral input-to-state stabilityMathematics
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Cell type-specific circuits of cortical layer IV spiny neurons

2003

Sensory signal processing in cortical layer IV involves two major morphological classes of excitatory neurons: spiny stellate and pyramidal cells. It is essentially unknown how these two cell types are integrated into intracortical networks and whether they play different roles in cortical signal processing. We mapped their cell-specific intracortical afferents in rat somatosensory cortex through a combination of whole-cell patch-clamp recordings and caged glutamate photolysis. Spiny stellate cells received monosynaptic excitation and inhibition originating almost exclusively from neurons located within the same barrel. Pyramidal cells, by contrast, displayed additional excitatory inputs fr…

MaleCell typePatch-Clamp TechniquesModels NeurologicalGlutamic AcidNeural InhibitionSensory systemBiologybiocytinSomatosensory systemInhibitory postsynaptic potentiallayer IVsomatosensoryinhibitory inputsddc:590morphologyAnimalsPatch clampRats WistarARTICLEslicesCells CulturedNeuronspyramidal cellAfferent Pathwayscaged glutamatePyramidal CellsGeneral Neurosciencespiny stellate cellfunctional connectivityExcitatory Postsynaptic PotentialsNeural InhibitionSomatosensory CortexelectrophysiologyJRatsexcitatory inputsExcitatory postsynaptic potentialHepatic stellate cellbarrel cortexNeuroscience
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Information decomposition of multichannel EMG to map functional interactions in the distributed motor system

2019

AbstractThe central nervous system needs to coordinate multiple muscles during postural control. Functional coordination is established through the neural circuitry that interconnects different muscles. Here we used multivariate information decomposition of multichannel EMG acquired from 14 healthy participants during postural tasks to investigate the neural interactions between muscles. A set of information measures were estimated from an instantaneous linear regression model and a time-lagged VAR model fitted to the EMG envelopes of 36 muscles. We used network analysis to quantify the structure of functional interactions between muscles and compared them across experimental conditions. Co…

MaleInformation transferMuscle networkNeurologyTransfer entropyComputer scienceSocial SciencesPostural controlFunctional connectivity0302 clinical medicineCONNECTIVITYNeural PathwaysDecomposition (computer science)Medicine and Health Sciencesmotor controlMuscle activityPostural Balance0303 health sciencesMuscle networksConditional mutual information05 social sciencesmedicine.anatomical_structureNeurologySYNCHRONIZATIONFemaleSpinal reflexAdultCORTEXmedicine.medical_specialtyCognitive NeurosciencePostureCentral nervous systemORGANIZATIONCognitive neuroscienceGRANGER CAUSALITY050105 experimental psychology03 medical and health sciencesReflexMotor systemCOHERENCEBiological neural networkmedicineHumans0501 psychology and cognitive sciencesMuscle SkeletalSet (psychology)signal processing030304 developmental biologyIDENTIFICATIONElectromyographyPostural controlMotor controlINPUTSMUSCLE SYNERGIESBRAIN NETWORKSSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaNeuroscience030217 neurology & neurosurgery
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Food Intake Adaptation to Dietary Fat Involves PSA-Dependent Rewiring of the Arcuate Melanocortin System in Mice

2012

International audience; Hormones such as leptin and ghrelin can rapidly rewire hypothalamic feeding circuits when injected into rodent brains. These experimental manipulations suggest that the hypothalamus might reorganize continually in adulthood to integrate the metabolic status of the whole body. In this study, we examined whether hypothalamic plasticity occurs in naive animals according to their nutritional conditions. For this purpose, we fed mice with a short-term high-fat diet (HFD) and assessed brain remodeling through its molecular and functional signature. We found that HFD for 3 d rewired the hypothalamic arcuate nucleus, increasing the anorexigenic tone due to activated pro-opio…

MaleMESH: Signal TransductionPro-Opiomelanocortin[ SDV.AEN ] Life Sciences [q-bio]/Food and NutritionSYNAPTIC INPUT ORGANIZATIONMESH: Energy IntakeWeight GainMESH: Mice KnockoutMice0302 clinical medicineMESH : Sialic AcidsNPY/AGRP NEURONSMESH: Pro-OpiomelanocortinMESH: AnimalsMESH : Neuronal PlasticityMESH: Neuronal PlasticityPLASTICITYMESH : Pro-OpiomelanocortinMESH : Adaptation PhysiologicalMice KnockoutFEEDING CIRCUITSMESH : Organ Culture TechniquesINSULIN-RESISTANCE0303 health sciencesNeuronal PlasticityPOLYSIALIC ACIDGeneral NeuroscienceLeptinMESH: Energy Metabolismdigestive oral and skin physiologyINDUCED OBESITYMESH : SialyltransferasesMESH : Weight GainArticlesAdaptation PhysiologicalMESH : Mice TransgenicBODY-WEIGHTMESH: Dietary FatsHypothalamusCELL-ADHESION MOLECULEMESH: Weight GainGhrelinENERGY-BALANCEMelanocortinhormones hormone substitutes and hormone antagonistsSignal Transductionmedicine.medical_specialtyMESH: Mice TransgenicMESH : MaleMESH: SialyltransferasesMESH: Arcuate NucleusMice TransgenicMESH : Mice Inbred C57BLBiologyMESH : Arcuate NucleusMESH: Sialic Acids03 medical and health sciencesOrgan Culture TechniquesInsulin resistanceMESH: Mice Inbred C57BLArcuate nucleusInternal medicineMESH : MicemedicineAnimalsMESH: Mice030304 developmental biologyMESH : Signal TransductionArcuate Nucleus of HypothalamusMESH : Energy Intakemedicine.diseaseDietary FatsMESH: Adaptation PhysiologicalSialyltransferasesMESH: Organ Culture TechniquesMESH: MaleMice Inbred C57BLMESH : Energy MetabolismEndocrinologyMESH: Nerve NetSialic AcidsMESH : Nerve NetMESH : Mice KnockoutMESH : AnimalsNerve NetEnergy IntakeEnergy Metabolism[SDV.AEN]Life Sciences [q-bio]/Food and NutritionMESH : Dietary Fats030217 neurology & neurosurgeryHomeostasisHormoneThe Journal of Neuroscience
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Across space and time : infants learn from backward and forward visual statistics

2016

International audience; This study investigates whether infants are sensitive to backward and forward transitional probabilities within temporal and spatial visual streams. Two groups of 8-month-old infants were familiarized with an artificial grammar of shapes, comprising backward and forward base pairs (i.e. two shapes linked by strong backward or forward transitional probability) and part-pairs (i.e. two shapes with weak transitional probabilities in both directions). One group viewed the continuous visual stream as a temporal sequence, while the other group viewed the same stream as a spatial array. Following familiarization, infants looked longer at test trials containing part-pairs th…

MaleTime perspectiveTime FactorsVisual perceptionspatial visual streamsCognitive NeuroscienceSpatial abilityVisual input[SHS.PSY]Humanities and Social Sciences/Psychology[ SCCO.PSYC ] Cognitive science/PsychologyArticle050105 experimental psychologypsyc[ SHS.PSY ] Humanities and Social Sciences/PsychologyChild DevelopmentDevelopmental and Educational PsychologyHumansLearning0501 psychology and cognitive sciences10. No inequalityProbabilityAnalysis of VarianceSequenceCommunicationSpacetimeStatistical learningbusiness.industryExtramural05 social sciencesAge FactorsInfantPattern recognitionsensitivityTemporal sequencesSpace PerceptionTime Perception[SCCO.PSYC]Cognitive science/PsychologyVisual PerceptionFemaleArtificial intelligencePsychologybusinessPhotic Stimulation050104 developmental & child psychology
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Stationary and non-stationary stochastic response of linear fractional viscoelastic systems

2012

Abstract A method is presented to compute the stochastic response of single-degree-of-freedom (SDOF) structural systems with fractional derivative damping, subjected to stationary and non-stationary inputs. Based on a few manipulations involving an appropriate change of variable and a discretization of the fractional derivative operator, the equation of motion is reverted to a set of coupled linear equations involving additional degrees of freedom, the number of which depends on the discretization of the fractional derivative operator. As a result of the proposed variable transformation and discretization, the stochastic analysis becomes very straightforward and simple since, based on stand…

Markov chainDiscretizationStochastic processMechanical EngineeringMathematical analysisDegrees of freedom (statistics)Stochastic calculusAerospace EngineeringOcean EngineeringStatistical and Nonlinear PhysicsViscoelasticity Fractional calculus Stochastic input Non-stationary responseCondensed Matter PhysicsFractional calculusOperator (computer programming)Nuclear Energy and EngineeringSettore ICAR/08 - Scienza Delle CostruzioniLinear equationCivil and Structural EngineeringMathematics
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Tuning of an Optical Dimer Nanoantenna by Electrically Controlling Its Load Impedance

2009

International audience; Optical antennas are elementary units used to direct optical radiation to the nanoscale. Here we demonstrate an active control over individual antenna performances by an external electrical trigger. We find that by an in-plane command of an anisotropic load medium, the electromagnetic interaction between individual elements constituting an optical antenna can be controlled, resulting in a strong polarization and tuning response. An active command of the antenna is a prerequisite for directing light wave through the utilization of such a device.

Materials scienceNanostructureBioengineering02 engineering and technologyMETAL NANOPARTICLESLIQUID-CRYSTALS01 natural sciencesPLASMON RESONANCES010309 opticsOptics[ PHYS.COND.CM-MSQHE ] Physics [physics]/Condensed Matter [cond-mat]/Mesoscopic Systems and Quantum Hall Effect [cond-mat.mes-hall]0103 physical sciencesGeneral Materials Science[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/MicroelectronicsANTENNAAnisotropyNanoscopic scale[PHYS.COND.CM-MSQHE]Physics [physics]/Condensed Matter [cond-mat]/Mesoscopic Systems and Quantum Hall Effect [cond-mat.mes-hall]Computer Science::Information Theorybusiness.industryPAIRSMechanical EngineeringGeneral ChemistryInput impedance021001 nanoscience & nanotechnologyCondensed Matter PhysicsPolarization (waves)LIGHT-SCATTERINGFREEDERICKSZ TRANSITIONNanoelectronics[SPI.OPTI]Engineering Sciences [physics]/Optics / PhotonicOptical radiation[ SPI.NANO ] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics[ SPI.OPTI ] Engineering Sciences [physics]/Optics / PhotonicAntenna (radio)NANOCIRCUIT0210 nano-technologybusinessEMISSION
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A new gas sensor electronic interface with generalized impedance converter

2008

A new gas sensor conditioning circuit that allows a direct resistance-to-frequency conversion, as well as the procedure for the design, is presented. The generalized impedance converter (GIC) proposed is configured as a variable capacitor connected with the capacitor timing terminal of an astable multivibrator implemented by a PSoC (programmable system on chip) microcontroller device. The GIC effective input impedance, which is controlled by the gas sensor resistance, controls the astable output frequency. Good correlation of the experimental output frequency, which depends on the gas concentration, is achieved. The circuit is a simple gas sensor digital interface with frequency output.

Materials sciencebusiness.industryMetals and AlloysElectrical engineeringInput impedanceCondensed Matter PhysicsSurfaces Coatings and FilmsElectronic Optical and Magnetic Materialslaw.inventionMultivibratorCapacitorMicrocontrollerPSoCTerminal (electronics)lawMaterials ChemistryVariable capacitorSystem on a chipElectrical and Electronic EngineeringbusinessInstrumentationSensors and Actuators B: Chemical
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