Search results for " algorithm"

showing 10 items of 2538 documents

Random Feature Approximation for Online Nonlinear Graph Topology Identification

2021

Online topology estimation of graph-connected time series is challenging, especially since the causal dependencies in many real-world networks are nonlinear. In this paper, we propose a kernel-based algorithm for graph topology estimation. The algorithm uses a Fourier-based Random feature approximation to tackle the curse of dimensionality associated with the kernel representations. Exploiting the fact that the real-world networks often exhibit sparse topologies, we propose a group lasso based optimization framework, which is solve using an iterative composite objective mirror descent method, yielding an online algorithm with fixed computational complexity per iteration. The experiments con…

Signal Processing (eess.SP)FOS: Computer and information sciencesComputer Science - Machine LearningComputational complexity theoryComputer scienceApproximation algorithmTopology (electrical circuits)Network topologyMachine Learning (cs.LG)Kernel (statistics)FOS: Electrical engineering electronic engineering information engineeringTopological graph theoryElectrical Engineering and Systems Science - Signal ProcessingOnline algorithmAlgorithmCurse of dimensionality
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Causal Inference in Geoscience and Remote Sensing From Observational Data

2020

Establishing causal relations between random variables from observational data is perhaps the most important challenge in today’s science. In remote sensing and geosciences, this is of special relevance to better understand the earth’s system and the complex interactions between the governing processes. In this paper, we focus on an observational causal inference, and thus, we try to estimate the correct direction of causation using a finite set of empirical data. In addition, we focus on the more complex bivariate scenario that requires strong assumptions and no conditional independence tests can be used. In particular, we explore the framework of (nondeterministic) additive noise models, …

Signal Processing (eess.SP)FOS: Computer and information sciencesComputer Science - Machine LearningEarth science0211 other engineering and technologiesEstimatorRegression analysis02 engineering and technologyBivariate analysisMachine Learning (cs.LG)Methodology (stat.ME)Nondeterministic algorithmConditional independence13. Climate actionCausal inferenceFOS: Electrical engineering electronic engineering information engineeringGeneral Earth and Planetary SciencesElectrical Engineering and Systems Science - Signal ProcessingElectrical and Electronic EngineeringSpurious relationshipStatistics - MethodologyIndependence (probability theory)021101 geological & geomatics engineeringRemote sensingIEEE Transactions on Geoscience and Remote Sensing
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Energy Efficiency Optimization for Multi-cell Massive MIMO : Centralized and Distributed Power Allocation Algorithms

2021

This paper investigates the energy efficiency (EE) optimization in downlink multi-cell massive multiple-input multiple-output (MIMO). In our research, the statistical channel state information (CSI) is exploited to reduce the signaling overhead. To maximize the minimum EE among the neighbouring cells, we design the transmit covariance matrices for each base station (BS). Specifically, optimization schemes for this max-min EE problem are developed, in the centralized and distributed ways, respectively. To obtain the transmit covariance matrices, we first find out the closed-form optimal transmit eigenmatrices for the BS in each cell, and convert the original transmit covariance matrices desi…

Signal Processing (eess.SP)FOS: Computer and information sciencesmallintaminenComputational complexity theoryComputer scienceenergiatehokkuusComputer Science - Information TheoryMIMO02 engineering and technologyPrecoding0203 mechanical engineeringoptimointistatistical CSIalgoritmit0202 electrical engineering electronic engineering information engineeringFOS: Electrical engineering electronic engineering information engineeringOverhead (computing)Electrical and Electronic EngineeringElectrical Engineering and Systems Science - Signal Processingenergy efficiencymax-min fairnessInformation Theory (cs.IT)020206 networking & telecommunications020302 automobile design & engineeringmulti-cell MIMOCovarianceDistributed algorithmChannel state informationConvex optimizationdistributed processingAlgorithm
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Iterative Reconstruction of Signals on Graph

2020

We propose an iterative algorithm to interpolate graph signals from only a partial set of samples. Our method is derived from the well known Papoulis-Gerchberg algorithm by considering the optimal value of a constant involved in the iteration step. Compared with existing graph signal reconstruction algorithms, the proposed method achieves similar or better performance both in terms of convergence rate and computational efficiency.

Signal Processing (eess.SP)signal processing algorithmIterative methodComputer science02 engineering and technologyIterative reconstructionSettore MAT/08 - Analisi NumericaSettore MAT/05 - Analisi Matematica0202 electrical engineering electronic engineering information engineeringFOS: MathematicsFOS: Electrical engineering electronic engineering information engineeringsignal reconstructionMathematics - Numerical AnalysisElectrical and Electronic EngineeringElectrical Engineering and Systems Science - Signal ProcessingSignal reconstructionApplied Mathematics020206 networking & telecommunicationsNumerical Analysis (math.NA)Graphspectral analysisGraph theoryRate of convergenceSignal ProcessingGraph (abstract data type)Algorithmsignal processing algorithmsInterpolation
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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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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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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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On the Design of Fast Wavelet Transform Algorithms With Low Memory Requirements

2008

In this paper, a new algorithm to efficiently compute the two-dimensional wavelet transform is presented. This algorithm aims at low memory consumption and reduced complexity, meeting these requirements by means of line-by-line processing. In this proposal, we use recursion to automatically place the order in which the wavelet transform is computed. This way, we solve some synchronization problems that have not been tackled by previous proposals. Furthermore, unlike other similar proposals, our proposal can be straightforwardly implemented from the algorithm description. To this end, a general algorithm is given which is further detailed to allow its implementation with a simple filter bank…

Signal processingLifting schemeComputer scienceSecond-generation wavelet transformStationary wavelet transformWavelet transformImage processingCascade algorithmFilter bankWavelet packet decompositionMedia TechnologyDiscrete cosine transformCodecElectrical and Electronic EngineeringFast wavelet transformAlgorithmEncoderData compressionImage compressionIEEE Transactions on Circuits and Systems for Video Technology
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Optical encryption with compressive ghost imaging

2011

Ghost imaging (GI) is a novel technique where the optical information of an object is encoded in the correlation of the intensity fluctuations of a light source. Computational GI (CGI) is a variant of the standard procedure that uses a single bucket detector. Recently, we proposed to use CGI to encrypt and transmit the object information to a remote party [1]. The optical encryption scheme shows compressibility and robustness to eavesdropping attacks. The reconstruction algorithm provides a relative low quality images and requires high acquisitions times. A procedure to overcome such limitations is to combine CGI with compressive sampling (CS), an advanced signal processing theory that expl…

Signal processingLight intensityCompressed sensingbusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingReconstruction algorithmIterative reconstructionGhost imagingEncryptionbusinessAlgorithm2011 Conference on Lasers and Electro-Optics Europe and 12th European Quantum Electronics Conference (CLEO EUROPE/EQEC)
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