Search results for "algorithm"

showing 10 items of 4887 documents

Adaptive motion estimation and video vector quantization based on spatiotemporal non-linearities of human perception

1997

The two main tasks of a video coding system are motion estimation and vector quantization of the signal. In this work a new splitting criterion to control the adaptive decomposition for the non-uniform optical flow estimation is exposed. Also, a novel bit allocation procedure is proposed for the quantization of the DCT transform of the video signal. These new approaches are founded on a perception model that reproduce the relative importance given by the human visual system to any location in the spatial frequency, temporal frequency and amplitude domain of the DCT transform. The experiments show that the proposed procedures behave better than their equivalent (fixed-block-size motion estim…

Signal processingAdaptive algorithmComputer sciencebusiness.industryTrellis quantizationQuantization (signal processing)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONVector quantizationIterative reconstructionOptical flow estimationMotion estimationComputer Science::MultimediaHuman visual system modelDiscrete cosine transformComputer visionArtificial intelligencebusinessQuantization (image processing)
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Cubic Local Splines on Non-uniform Grid

2015

In this chapter, two types of local cubic splines on non-uniform grids are described: 1. The simplest variation-diminishing splines and 2. The quasi-interpolating splines. The splines are computed by a simple fast computational algorithms that utilizes a relation between the splines and cubic interpolation polynomials. Those splines can serve as an efficient tool for real-time signal processing. As an input, they use either clean or noised arbitrarily-spaced samples. On the other hand, the capability to adapt the grid to the structure of an object and minimal requirements to the operating memory are great advantages for off-line processing of signals and multidimensional data arrays.

Signal processingBox splineRelation (database)Computer scienceMathematicsofComputing_NUMERICALANALYSISMonotone cubic interpolationGridMathematics::Numerical AnalysisComputer Science::GraphicsSimple (abstract algebra)Bicubic interpolationSpline interpolationAlgorithmComputingMethodologies_COMPUTERGRAPHICS
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A method for quantifying atrial fibrillation organization based on wave-morphology similarity

2002

A new method for quantifying the organization of single bipolar electrograms recorded in the human atria during atrial fibrillation (AF) is presented. The algorithm relies on the comparison between pairs of local activation waves (LAWs) to estimate their morphological similarity, and returns a regularity index (/spl rho/) which measures the extent of repetitiveness over time of the detected activations. The database consisted of endocardial data from a multipolar basket catheter during AF and intraatrial recordings during atrial flutter. The index showed maximum regularity (/spl rho/=1) for all atrial flutter episodes and decreased significantly when increasing AF complexity as defined by W…

Signal processingBundle of Hismedicine.medical_specialtyMorphological similarityAtrial fibrillation (AF)Biomedical EngineeringSensitivity and SpecificityPattern Recognition AutomatedElectrocardiographySimilarity (network science)Heart RateInternal medicineAtrial Fibrillationotorhinolaryngologic diseasesmedicineHumansClinical treatmentWaveform morphologyMathematicsmedicine.diagnostic_testMinimum distanceModels CardiovascularReproducibility of ResultsSignal Processing Computer-AssistedAtrial fibrillationEndocardial signalmedicine.diseaseTachyarrhythmia organizationCardiologysense organsRhythm classificationBasket catheterElectrocardiographyAlgorithmsAtrial flutterBiomedical engineeringIEEE Transactions on Biomedical Engineering
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On the Fidelity of IEEE 802.11 commercial cards

2006

The IEEE 802.11 D CF protocol is known to be fair in terms of long-term resource repartition among the contending stations. However, when considering real scenarios, where commercial 802.11 cards interact, very unpredictable as well as sometimes surprising behaviors emerge. Motivation of this paper is to investigate the reasons of the very evident disagreement between the theoretical IEEE 802.11 DCF protocol models and its practical implementations. Inparticular, we try to characterize the card behavior not only in terms of perceived throughput, but also in terms of low-level channel access operations. In fact, the simple throughput analysis does not allow to identify what affecting paramet…

Signal processingCommunication channels (information theory); Internet; Signal processing; Wireless telecommunication systems; Baseband signals; Carrier sense function; MAC layer; Network protocolsComputer scienceMAC layerWireless local area networks (WLAN)backoff algorithmCommunication channels (information theory)IEEE 802.11Wireless telecommunication systemsNetwork protocolsThroughput (business)InternetBaseband signalsChannel allocation schemesSIMPLE (military communications protocol)Settore ING-INF/03 - Telecomunicazionibusiness.industryComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSPhysical layerCarrier sense functionThroughputNetwork interface controllerEmbedded systemResource allocationbusinessComputer networkCommunication channel
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Incipient damage identification through characteristics of the analytical signal response

2008

The analytical signal is a complex representation of a time domain signal: the real part is the time domain signal itself, while the imaginary part is its Hilbert transform. It has been observed that damage, even at a very low level, yields clearly detectable variations of analytical signal quantities such as phase and instantaneous frequency. This observation can represent a step toward a quick and effective tool to recognize the presence of incipient damage where other frequency-based techniques fail. In this paper a damage identification procedure based on an adimensional functional of the square of the difference between the characteristics of the analytical theoretical and measured sig…

Signal processingComplex representationSignal processingEstimation theoryAnalytical SignalBuilding and ConstructionInstantaneous phasesymbols.namesakeMechanics of MaterialsRobustness (computer science)symbolsTime domainHilbert transformSignal transfer functionSettore ICAR/08 - Scienza Delle CostruzioniStructural damage identificationAlgorithmCivil and Structural EngineeringMathematicsStructural Control and Health Monitoring
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A fast recursive algorithm to compute local axial moments

2001

The paper describes a fast algorithm to compute local axial moments used in the algorithm of discrete symmetry transform (DST). The basic idea is grounded on fast recursive implementation of respective linear filters by using the so-called primitive kernel functions since the moment computation can be performed in the framework of linear filtering. The main result is that the computation of the local axial moments is independent of the kernel size, i.e. of the order O(1) per data point (pixel). This result is of relevance whenever the DST is used to face with real time computer vision problems. The experimental results confirm the time complexity predicted by the theory.

Signal processingComputationMoment (mathematics)Control and Systems EngineeringFace (geometry)Signal ProcessingPoint (geometry)Computer Vision and Pattern RecognitionElectrical and Electronic EngineeringTime complexityAlgorithmSoftwareLinear filterMathematicsDiscrete symmetrySignal Processing
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Local Splines on Non-uniform Grid

2018

In this Chapter and in the next Chap. 7, we deal with continuous rather than discrete and discrete-time splines. In these and only these chapters, we abandon the assumption that the grid, on which the splines are constructed, is uniform and consider splines on arbitrary grids. Two types of local cubic and quadratic splines on non-uniform grids are described: 1. The simplest variation-diminishing splines and 2. The quasi-interpolating splines. The splines are computed by simple fast computational algorithms that utilize relations between the splines and interpolation polynomials. In addition, these relations provide sharp estimations of splines’ approximation accuracy. These splines can serv…

Signal processingComputer Science::GraphicsQuadratic equationSimple (abstract algebra)Computer scienceStructure (category theory)Multidimensional dataObject (computer science)GridAlgorithmInterpolation
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Algorithm To Calculate Heart Rate By Removing Touch Errors And Algorithm Analysis

2018

Heart rate is one of the important physiological parameter to measure the stability of the health. This study shows analysis of a proposed algorithm to calculate heart rate with miss touch errors to make it more efficient. Android Smart phone with good quality camera has come to reach of common people and has become one of the most necessary and powerful device for today and of course, for future generation. We can use its powerful features to solve or assess heart state monitoring through capturing necessary data in the form of image. Mobile camera has a photo emitting diode and a photo detector. Light source illuminates the tissue and photo-detector calculates the small intensity variatio…

Signal processingComputer science020208 electrical & electronic engineering010401 analytical chemistryFast Fourier transformComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPhotodetector02 engineering and technology01 natural sciencesWindow function0104 chemical sciences0202 electrical engineering electronic engineering information engineeringMATLABInfinite impulse responseAlgorithmcomputerHann functionSmoothingcomputer.programming_language2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)
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An Automatic System for the Analysis and Classification of Human Atrial Fibrillation Patterns from Intracardiac Electrograms

2008

This paper presents an automatic system for the analysis and classification of atrial fibrillation (AF) patterns from bipolar intracardiac signals. The system is made up of: 1) a feature- extraction module that defines and extracts a set of measures potentially useful for characterizing AF types on the basis of their degree of organization; 2) a feature-selection module (based on the Jeffries-Matusita distance and a branch and bound search algorithm) identifying the best subset of features for discriminating different AF types; and 3) a support vector machine technique-based classification module that automatically discriminates the AF types according to the Wells' criteria. The automatic s…

Signal processingComputer scienceFeature extractionBiomedical EngineeringFeature extraction and selectionFeature selectionSensitivity and SpecificityIntracardiac injectionPattern Recognition AutomatedArtificial IntelligenceSearch algorithmAtrial FibrillationmedicineHumansDiagnosis Computer-AssistedIntracardiac ElectrogramArrhythmia organizationSignal processingmedicine.diagnostic_testbusiness.industrySupport vector machines (SVMs)Reproducibility of ResultsPattern recognitionAtrial fibrillationHuman atrial fibrillationmedicine.diseaseSupport vector machineSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaAutomatic classificationArtificial intelligenceIntracardiac electrogrambusinessElectrocardiographyAlgorithmsIEEE Transactions on Biomedical Engineering
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Spectrum cartography using adaptive radial basis functions: Experimental validation

2017

In this paper, we experimentally validate the functionality of a developed algorithm for spectrum cartography using adaptive Gaussian radial basis functions (RBF). The RBF are strategically centered around representative centroid locations in a machine learning context. We assume no prior knowledge about neither the power spectral densities (PSD) of the transmitters nor their locations. Instead, the received signal power at each location is estimated as a linear combination of different RBFs. The weights of the RBFs, their Gaussian decaying parameters and locations are jointly optimized using expectation maximization with a least squares loss function and a quadratic regularizer. The perfor…

Signal processingComputer scienceGaussianCentroid020206 networking & telecommunicationsContext (language use)02 engineering and technologyComputer Science::Computational GeometryLeast squaresComputer Science::Numerical Analysissymbols.namesakeExpectation–maximization algorithm0202 electrical engineering electronic engineering information engineeringsymbolsRadial basis functionLinear combinationCartography
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