Search results for "online"

showing 10 items of 4526 documents

Moving Learning Machine Towards Fast Real-Time Applications: A High-Speed FPGA-based Implementation of the OS-ELM Training Algorithm

2018

Currently, there are some emerging online learning applications handling data streams in real-time. The On-line Sequential Extreme Learning Machine (OS-ELM) has been successfully used in real-time condition prediction applications because of its good generalization performance at an extreme learning speed, but the number of trainings by a second (training frequency) achieved in these continuous learning applications has to be further reduced. This paper proposes a performance-optimized implementation of the OS-ELM training algorithm when it is applied to real-time applications. In this case, the natural way of feeding the training of the neural network is one-by-one, i.e., training the neur…

Computer Networks and CommunicationsComputer scienceReal-time computingParameterized complexitylcsh:TK7800-836002 engineering and technologyextreme learning machine0202 electrical engineering electronic engineering information engineeringSensitivity (control systems)Electrical and Electronic EngineeringEnginyeria d'ordinadorsField-programmable gate arrayFPGAExtreme learning machineEnginyeria elèctricaArtificial neural networkData stream mininglcsh:Electronics020206 networking & telecommunicationsOS-ELMreal-time learningHardware and ArchitectureControl and Systems Engineeringon-chip trainingSignal Processingon-line learning020201 artificial intelligence & image processingDistributed memoryonline sequential ELMhardware implementationAlgorithm
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Acoustic spectral hole-burning in a two-level system ensemble

2020

AbstractMicroscopic two-level system (TLS) defects at dielectric surfaces and interfaces are among the dominant sources of loss in superconducting quantum circuits, and their properties have been extensively probed using superconducting resonators and qubits. We report on spectroscopy of TLSs coupling to the strain field in a surface acoustic wave (SAW) resonator. The narrow free spectral range of the resonator allows for two-tone spectroscopy where a strong pump is applied at one resonance, while a weak signal is used to probe a different mode. We map the spectral hole burnt by the pump tone as a function of frequency and extract parameters of the TLS ensemble. Our results suggest that det…

Computer Networks and CommunicationsQC1-999FOS: Physical sciences02 engineering and technologyDielectric01 natural sciencesMolecular physicsResonator0103 physical sciencesMesoscale and Nanoscale Physics (cond-mat.mes-hall)Computer Science (miscellaneous)Coherence (signal processing)010306 general physicsSpectroscopyPhysicsQuantum PhysicsCondensed Matter - Mesoscale and Nanoscale PhysicsPhysicsSurface acoustic waveResonanceStatistical and Nonlinear PhysicsQA75.5-76.95021001 nanoscience & nanotechnologyComputational Theory and MathematicsElectronic computers. Computer scienceSpectral hole burning0210 nano-technologyQuantum Physics (quant-ph)Free spectral range
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Assessment of the Current for a Non-Linear Power Inductor Including Temperature in DC-DC Converters

2023

A method for estimating the current flowing through a non-linear power inductor operating in a DC/DC converter is proposed. The knowledge of such current, that cannot be calculated in closed form as for the linear inductor, is crucial for the design of the converter. The proposed method is based on a third-order polynomial model of the inductor, already developed by the authors; it is exploited to solve the differential equation of the inductor and to implement a flux model in a circuit simulator. The method allows the estimation of the current up to saturation, intended as the point at which the differential inductance is reduced to half of its maximum value. The current profile depends al…

Computer Networks and Communicationsinductorsmagnetic coresnonlinear circuitsnonlinear network analysialgorithmsinductorSettore ING-INF/01 - ElettronicaAlgorithmmagnetic corenumerical simulationsferriteHardware and ArchitectureControl and Systems Engineeringnonlinear network analysisSignal ProcessingElectrical and Electronic Engineeringnonlinear circuitferritesElectronics
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Stackelberg-Cournot and Cournot equilibria in a mixed markets exchange economy

2012

In this note, we compare two strategic general equilibrium concepts: the Stackelberg-Cournot equilibrium and the Cournot equilibrium. We thus consider a market exchange economy including atoms and a continuum of traders, who behave strategically. We show that, when the preferences of the small traders are represented by Cobb-Douglas utility functions and the atoms have the same utility functions and endowments, the Stackelberg-Cournot and the Cournot equilibrium equilibria coincide if and only if the followers’ best responses functions have a zero slope at the SCE.

Computer Science::Computer Science and Game TheoryStackelberg-CournotGeneral equilibrium theoryContinuum (topology)05 social sciencesEconomyCournot competition[SHS.ECO]Humanities and Social Sciences/Economics and FinanceComputer Science::Multiagent SystemsNonlinear Sciences::Adaptation and Self-Organizing SystemsMarket exchange0502 economics and business[No keyword available]EconomicsStackelberg competitionExchange economy[ SHS.ECO ] Humanities and Social Sciences/Economies and finances050207 economics[SHS.ECO] Humanities and Social Sciences/Economics and FinanceMathematical economicsComputingMilieux_MISCELLANEOUS050205 econometrics
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Switching synchronization in 1-D memristive networks: An exact solution

2017

We study a switching synchronization phenomenon taking place in one-dimensional memristive networks when the memristors switch from the high to low resistance state. It is assumed that the distributions of threshold voltages and switching rates of memristors are arbitrary. Using the Laplace transform, a set of non-linear equations describing the memristors dynamics is solved exactly, without any approximations. The time dependencies of memristances are found and it is shown that the voltage falls across memristors are proportional to their threshold voltages. A compact expression for the network switching time is derived.

Computer Science::Emerging TechnologiesCondensed Matter - Mesoscale and Nanoscale PhysicsMesoscale and Nanoscale Physics (cond-mat.mes-hall)FOS: Physical sciencesAdaptation and Self-Organizing Systems (nlin.AO)Nonlinear Sciences - Adaptation and Self-Organizing Systems
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Organized Learning Models (Pursuer Control Optimisation)

1982

Abstract The concept of Organized Learning is defined, and some random models are presented. For Not Transferable Learning, it is necessary to start from an instantaneous learning; by a discrete way, we must form a stochastic model considering the probability of each path; with a continue aproximation, we can study the evolution of the internal state through to consider the relative and absolute probabilities, by means of differential equations systems. For Transferable Learning, the instantaneous learning give us directly the System evolution. So, the Algoritmes for the different models are compared.

Computer Science::Machine LearningComputational learning theoryWake-sleep algorithmActive learning (machine learning)business.industryComputer scienceCompetitive learningAlgorithmic learning theoryStability (learning theory)Online machine learningPursuerArtificial intelligencebusinessIFAC Proceedings Volumes
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Upport vector machines for nonlinear kernel ARMA system identification.

2006

Nonlinear system identification based on support vector machines (SVM) has been usually addressed by means of the standard SVM regression (SVR), which can be seen as an implicit nonlinear autoregressive and moving average (ARMA) model in some reproducing kernel Hilbert space (RKHS). The proposal of this letter is twofold. First, the explicit consideration of an ARMA model in an RKHS (SVM-ARMA 2k) is proposed. We show that stating the ARMA equations in an RKHS leads to solving the regularized normal equations in that RKHS, in terms of the autocorrelation and cross correlation of the (nonlinearly) transformed input and output discrete time processes. Second, a general class of SVM-based syste…

Computer Science::Machine LearningStatistics::TheoryComputer Networks and CommunicationsBiomedical signal processingInformation Storage and RetrievalMachine learningcomputer.software_genrePattern Recognition AutomatedStatistics::Machine LearningArtificial IntelligenceApplied mathematicsStatistics::MethodologyAutoregressive–moving-average modelComputer SimulationMathematicsTelecomunicacionesHardware_MEMORYSTRUCTURESSupport vector machinesModels StatisticalNonlinear system identificationbusiness.industryAutocorrelationSystem identificationSignal Processing Computer-AssistedGeneral MedicineComputer Science ApplicationsSupport vector machineNonlinear systemKernelAutoregressive modelNonlinear DynamicsARMA modelling3325 Tecnología de las TelecomunicacionesArtificial intelligenceNeural Networks ComputerbusinesscomputerSoftwareAlgorithmsReproducing kernel Hilbert spaceIEEE transactions on neural networks
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ORGANIZED LEARNING MODELS (PURSUER CONTROL OPTIMISATION)

1983

Abstract The concept of Organized Learning is defined, and some random models are presented. For Not Transferable Learning, it is necessary to start from an instantaneous learning; by a discrete way, we must form a stochastic model considering the probability of each path; with a continue aproximation, we can study the evolution of the internal state through to consider the relative and absolute probabilities, by means of differential equations systems. For Transferable Learning, the instantaneous learning give us directly the System evolution. So, the Algoritmes for the different models are compared.

Computer Science::Machine LearningStochastic modellingActive learning (machine learning)business.industryDifferential equationPath (graph theory)Control (management)Online machine learningPursuerArtificial intelligenceState (computer science)businessMathematics
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Nonlinear Pulse Shaping in Optical Fibres with a Neural Network

2020

We use a supervised machine-learning model based on a neural network to solve the direct and inverse problems relating to the shaping of optical pulses that occurs upon nonlinear propagation in optical fibres.

Computer Science::Machine Learning[PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics]Optical fiberArtificial neural networkComputer science02 engineering and technologyInverse problem01 natural sciencesPulse shapinglaw.invention010309 opticsNonlinear system020210 optoelectronics & photonicslaw0103 physical sciences0202 electrical engineering electronic engineering information engineeringElectronic engineeringComputingMilieux_MISCELLANEOUS
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Uniqueness of positive multi-lump bound states of nonlinear Schr�dinger equations

2003

In this paper we are concerned with multi-lump bound states of the nonlinear Schrodinger equation

Computer Science::Roboticssymbols.namesakeNonlinear systemGeneral MathematicsMathematical analysisBound statesymbolsApplied mathematicsUniquenessNonlinear Sciences::Pattern Formation and SolitonsNonlinear Schrödinger equationSchrödinger equationMathematicsMathematische Zeitschrift
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