Search results for "machine"

showing 10 items of 2592 documents

Neural networks with non-uniform embedding and explicit validation phase to assess Granger causality

2015

A challenging problem when studying a dynamical system is to find the interdependencies among its individual components. Several algorithms have been proposed to detect directed dynamical influences between time series. Two of the most used approaches are a model-free one (transfer entropy) and a model-based one (Granger causality). Several pitfalls are related to the presence or absence of assumptions in modeling the relevant features of the data. We tried to overcome those pitfalls using a neural network approach in which a model is built without any a priori assumptions. In this sense this method can be seen as a bridge between model-free and model-based approaches. The experiments perfo…

Cognitive NeuroscienceEntropyFOS: Physical sciencesOverfittingcomputer.software_genreMachine learningGranger causalityArtificial IntelligenceMedicine and Health SciencesEntropy (information theory)Non-uniform embeddingComputer SimulationMathematicsArtificial neural networkbusiness.industryProbability and statisticsModels TheoreticalNeural Networks (Computer)ClassificationNeural networkAlgorithmCausalityPhysics - Data Analysis Statistics and ProbabilitySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityEmbeddingA priori and a posterioriTransfer entropyNeural Networks ComputerArtificial intelligenceData miningbusinesscomputerAlgorithmsNeural networksData Analysis Statistics and Probability (physics.data-an)
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Active spike transmission in the neuron model with a winding threshold manifold

2012

International audience; We analyze spiking responses of excitable neuron model with a winding threshold manifold on a pulse stimulation. The model is stimulated with external pulse stimuli and can generate nonlinear integrate-and-fire and resonant responses typical for excitable neuronal cells (all-or-none). In addition we show that for certain parameter range there is a possibility to trigger a spiking sequence with a finite number of spikes (a spiking message) in the response on a short stimulus pulse. So active transformation of N incoming pulses to M (with M>N) outgoing spikes is possible. At the level of single neuron computations such property can provide an active "spike source" comp…

Cognitive Neuroscience[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS][ MATH.MATH-DS ] Mathematics [math]/Dynamical Systems [math.DS][ NLIN.NLIN-CD ] Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD]Threshold manifoldBiological neuron modelMachine learningcomputer.software_genreTopology01 natural sciences010305 fluids & plasmaslaw.inventionSpike encodingArtificial Intelligencelaw0103 physical sciences010306 general physicsSpike transmissionActive responseBifurcationMathematicsExcitabilityQuantitative Biology::Neurons and Cognitionbusiness.industry[SCCO.NEUR]Cognitive science/NeuroscienceDissipationComputer Science ApplicationsPulse (physics)[SPI.TRON]Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/ElectronicsNonlinear systemTransmission (telecommunications)Nonlinear dynamics[NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD][ SCCO.NEUR ] Cognitive science/NeuroscienceSpike (software development)Artificial intelligencebusinessManifold (fluid mechanics)computer
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Contextual neural-network based spectrum prediction for cognitive radio

2015

Cognitive radio is the technique of effective electromagnetic spectrum usage important for future wireless communication including 5G networks. Neural networks are nature-inspired computational models used to solve cognitive radio prediction problems. This paper presents the use of contextual Sigma-if neural network in prediction of channel states for cognitive radio. Our results indicate that Sigma-if neural network confirms better predictions than Multilayer Perceptron (MLP) network and decreases sensing time for the benefit of the increase of the effectiveness of e-m spectrum usage.

Cognitive modelComputational modelArtificial neural networkspectrum sensingbusiness.industryTime delay neural networkComputer scienceComputer Science::Neural and Evolutionary Computationartificial intelligenceCognitive networkMachine learningcomputer.software_genrecontextual predictionCognitive radioMultilayer perceptron5G communicationcontextual processingWirelessArtificial intelligencebusinesscomputer2015 Fourth International Conference on Future Generation Communication Technology (FGCT)
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Gödel and the Blind Watchmaker

2015

While accepting that contingency is key to biological evolution, we wonder how much need there is for it. It is extremely difficult to talk about trends in evolution, but the fact remains that they are found here and there when evolutionary experiments are repeated. But we should ask, for example, whether there is an unavoidable tendency of life towards progressive complexity . This chapter deals with certain theoretical considerations from Logic and Computing on the conditions necessary to formulate a predictive evolutionary theory .

Cognitive scienceComputer scienceBiological evolutionWonderTuring machinesymbols.namesakeSynthetic biologysymbolsKey (cryptography)GödelContingencycomputerEvolutionary theorycomputer.programming_language
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Improving color correction across camera and illumination changes by contextual sample selection

2012

International audience; In many tasks of machine vision applications, it is important that recorded colors remain constant, in the real world scene, even under changes of the illuminants and the cameras. Contrary to the human vision system, a machine vision system exhibits inadequate adaptability to the variation of lighting conditions. Automatic white bal- ance control available in commercial cameras is not sufficient to pro- vide reproducible color classification. We address this problem of color constancy on a large image database acquired with varying digi- tal cameras and lighting conditions. A device-independent color repre- sentation may be obtained by applying a chromatic adaptation…

Color Constancy[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingColor normalizationMachine visionComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONColor balance02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineeringComputer visionElectrical and Electronic EngineeringContextual improvement. Medical applicationsColor constancybusiness.industryColor correctionImage segmentationAtomic and Molecular Physics and OpticsComputer Science ApplicationsChromatic adaptationRGB color model020201 artificial intelligence & image processingArtificial intelligenceSPIEbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Colour segmentation based on a light reflection model to locate citrus fruits for robotic harvesting

1993

Abstract Colour segmentation with a vision system is a good procedure to identify and locate fruits in robotic harvesting. Natural illumination conditions present in these environments produce a very variable illumination of the scene, in addition, fruits are usually partially occluded, and complete visual information about them is not available. The colour segmentation used for these purposes must take into account the appearance of highlights and shadows that natural illumination conditions produce. A method based on the Dichromatic Reflection Model for the light reflected from the surface object is reported here. Through the assumption of this model the light rays reflected from points o…

Color imageMachine visionComputer sciencebusiness.industryForestryImage segmentationHorticultureRayComputer Science ApplicationsPosition (vector)ShadowReflection (physics)SegmentationComputer visionArtificial intelligencebusinessAgronomy and Crop ScienceComputers and Electronics in Agriculture
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LR(k) Parsing

1990

In this chapter we shall generalize the notion of strong LL(k) parsing presented in Chapter 5 and consider a method for deterministic left parsing that applies to a slightly wider class of context-free grammars than does the strong LL(k) parsing method. This method will be called “canonical LL(k) parsing”. As in strong LL(k) parsing, the acronym “LL(k)” means that the input string is parsed (1) in a single Left-to-right scan, (2) producing a Left parse, and (3) using lookahead of length k.

CombinatoricsClass (set theory)ParsingRule-based machine translationComputer scienceString (computer science)Acronym16. Peace & justicecomputer.software_genrecomputer
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Ambainis-Freivalds’ Algorithm for Measure-Once Automata

2001

An algorithm given by Ambainis and Freivalds [1] constructs a quantum finite automaton (QFA) with O(log p) states recognizing the language Lp = {ai| i is divisible by p} with probability 1 - Ɛ , for any Ɛ > 0 and arbitrary prime p. In [4] we gave examples showing that the algorithm is applicable also to quantum automata of very limited size. However, the Ambainis-Freivalds algoritm is tailored to constructing a measure-many QFA (defined by Kondacs andWatrous [2]), which cannot be implemented on existing quantum computers. In this paper we modify the algorithm to construct a measure-once QFA of Moore and Crutchfield [3] and give examples of parameters for this automaton. We show for the lang…

CombinatoricsDiscrete mathematicsFinite-state machineQuantum finite automataSpace (mathematics)QuantumMeasure (mathematics)AlgorithmPrime (order theory)AutomatonMathematicsQuantum computer
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Improved Constructions of Quantum Automata

2008

We present a simple construction of quantum automata which achieve an exponential advantage over classical finite automata. Our automata use $\frac{4}{\epsilon} \log 2p + O(1)$ states to recognize a language that requires p states classically. The construction is both substantially simpler and achieves a better constant in the front of logp than the previously known construction of [2]. Similarly to [2], our construction is by a probabilistic argument. We consider the possibility to derandomize it and present some preliminary results in this direction.

CombinatoricsDiscrete mathematicsFinite-state machineSimple (abstract algebra)Quantum automataProbabilistic logicQuantum finite automataConstant (mathematics)MathematicsAutomatonExponential function
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Tally languages accepted by alternating multitape finite automata

1997

We consider k-tape 1-way alternating finite automata (k-tape lafa). We say that an alternating automaton accepts a language L\(\subseteq\)(Σ*)k with f(n)-bounded maximal (respectively, minimal) leaf-size if arbitrary (respectively, at least one) accepting tree for any (w1, w2,..., wk) ∈ L has no more than $$f\mathop {(\max }\limits_{1 \leqslant i \leqslant k} \left| {w_i } \right|)$$ leaves. The main results of the paper are the following. If k-tape lafa accepts language L over one-letter alphabet with o(log n)-bounded maximal leaf-size or o(log log n)-bounded minimal leaf-size then the language L is semilinear. Moreover, if a language L is accepted with o(log log(n))-bounded minimal (respe…

CombinatoricsTree (descriptive set theory)Finite-state machineLog-log plotAlphabetBinary logarithmComputer Science::Formal Languages and Automata TheoryMathematics
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