Search results for "complex"

showing 10 items of 5889 documents

A Variational Approach for Denoising Hyperspectral Images Corrupted by Poisson Distributed Noise

2014

Poisson distributed noise, such as photon noise is an important noise source in multi- and hyperspectral images. We propose a variational based denoising approach, that accounts the vectorial structure of a spectral image cube, as well as the poisson distributed noise. For this aim, we extend an approach for monochromatic images, by a regularisation term, that is spectrally and spatially adaptive and preserves edges. In order to take the high computational complexity into account, we derive a Split Bregman optimisation for the proposed model. The results show the advantages of the proposed approach compared to a marginal approach on synthetic and real data.

Computational complexity theorybusiness.industryNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHyperspectral imagingPoisson distributionTerm (time)symbols.namesakeNoiseComputer Science::Computer Vision and Pattern RecognitionsymbolsComputer visionArtificial intelligenceMonochromatic colorCubebusinessAlgorithmMathematics
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Space-Frequency Quantization using Directionlets

2007

In our previous work we proposed a construction of critically sampled perfect reconstruction transforms with directional vanishing moments (DVMs) imposed in the corresponding basis functions along different directions, called directionlets. Here, we combine the directionlets with the space-frequency quantization (SFQ) image compression method, originally based on the standard two-dimensional (2-D) wavelet transform (WT). We show that our new compression method outperforms the standard SFQ as well as the state-of-the-art compression methods, like SPIHT and JPEG-2000, in terms of the quality of compressed images, especially in a low-rate compression regime. We also show that the order of comp…

Computational complexity theorybusiness.industryWavelet transformBasis functionIterative reconstructionSet partitioning in hierarchical treesComputer visionArtificial intelligencebusinessQuantization (image processing)AlgorithmData compressionImage compressionMathematics2007 IEEE International Conference on Image Processing
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Datorzinātne un informācijas tehnoloģijas: Datu bāzes un informācijas sistēmas: doktorantu konsorcijs. Sestā Starptautiskā Baltijas konference Baltic…

2004

The Baltic Conference on Databases and Information Systems is a biannual international forum for technical discussion among researchers and developers of database and information systems. The objective of the conference is to bring together researchers as well as practitioners and PhD students in the field of computing research that will improve the construction of future information systems. On the other hand, the conference is giving opportunities to developers, users and researchers of advanced IS technologies to present their work and to exchange their ideas and at the same time providing a feedback to database community.

Computational complexityDatnesQuantum algorithmsDatabasesDataInformation systems:TECHNOLOGY::Information technology::Computer science [Research Subject Categories]DatubāzesQuantum computingBoolean functionsInformācijas sistēmas
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Financial Fragility and Interacting Units: an Exercise

2010

This paper assumes that financial fluctuations are the result of the dynamic interaction between liquidity and solvency conditions of individual financial units. The framework is designed as a heterogeneous agent model which proceeds through discrete time steps within a finite time horizon. The interaction at the microlevel between financial units and the market maker, who is in charge of clearing the market, produces interesting complex dynamics. The model is analyzed by means of numerical simulations and agent-based computational economics (ACE) approach. The behaviour and evolution of financial units are studied for different parameter regimes in order to show the importance of the param…

Computational economicsFinancial economicsmedia_common.quotation_subjectMonetary policyFinancial fragilityagent-based modelMarket makerMarket liquidityInterest rateComplex dynamicsOrder (exchange)EconomicsEconometricsmedia_common
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BELM: Bayesian Extreme Learning Machine

2011

The theory of extreme learning machine (ELM) has become very popular on the last few years. ELM is a new approach for learning the parameters of the hidden layers of a multilayer neural network (as the multilayer perceptron or the radial basis function neural network). Its main advantage is the lower computational cost, which is especially relevant when dealing with many patterns defined in a high-dimensional space. This brief proposes a bayesian approach to ELM, which presents some advantages over other approaches: it allows the introduction of a priori knowledge; obtains the confidence intervals (CIs) without the need of applying methods that are computationally intensive, e.g., bootstrap…

Computer Networks and CommunicationsComputer scienceComputer Science::Neural and Evolutionary ComputationBayesian probabilityOverfittingMachine learningcomputer.software_genrePattern Recognition AutomatedReduction (complexity)Artificial IntelligenceComputer SimulationRadial basis functionExtreme learning machineArtificial neural networkbusiness.industryEstimation theoryBayes TheoremGeneral MedicineComputer Science ApplicationsMultilayer perceptronNeural Networks ComputerArtificial intelligencebusinesscomputerAlgorithmsSoftwareIEEE Transactions on Neural Networks
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A Fly-Inspired Mushroom Bodies Model for Sensory-Motor Control Through Sequence and Subsequence Learning

2016

Classification and sequence learning are relevant capabilities used by living beings to extract complex information from the environment for behavioral control. The insect world is full of examples where the presentation time of specific stimuli shapes the behavioral response. On the basis of previously developed neural models, inspired by Drosophila melanogaster, a new architecture for classification and sequence learning is here presented under the perspective of the Neural Reuse theory. Classification of relevant input stimuli is performed through resonant neurons, activated by the complex dynamics generated in a lattice of recurrent spiking neurons modeling the insect Mushroom Bodies n…

Computer Networks and CommunicationsComputer scienceDecision MakingModels NeurologicalAction PotentialsContext (language use)Insect mushroom bodies bio-inspired control spiking neurons02 engineering and technologyVariation (game tree)Motor Activitybio-inspired control03 medical and health sciences0302 clinical medicineRewardSubsequence0202 electrical engineering electronic engineering information engineeringAnimalsLearningComputer SimulationMushroom BodiesTRACE (psycholinguistics)NeuronsSequencebio-inspired control; Insect mushroom bodies; learning; neural model; resonant neurons; spiking neurons; Action Potentials; Animals; Computer Simulation; Decision Making; Drosophila melanogaster; Learning; Motor Activity; Mushroom Bodies; Neurons; Perception; Reward; Robotics; Models Neurological; Neural Networks Computerspiking neuronsbusiness.industryRoboticsGeneral MedicineInsect mushroom bodiesComplex dynamicsDrosophila melanogasterMushroom bodiesPerception020201 artificial intelligence & image processingNeural Networks ComputerArtificial intelligenceSequence learningbusiness030217 neurology & neurosurgery
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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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A measurement-based study on the correlations of inter-domain Internet application flows

2014

Internet traffic characterization has a profound impact on network engineering and traffic identification. Existing studies are often carried out on a per-flow basis, focusing on the properties of individual flows. In this paper, we study the interaction of Internet traffic flows and network features from a complex network perspective, focusing on six types of applications: P2P file sharing, P2P stream, HTTP, instant messaging, online games and abnormal traffic. With large-volume traffic flow records collected through proprietary line-speed hardware-based monitors, we construct flow graphs of these different application types. Based on the flow graphs, we calculate the correlation coefficie…

Computer Networks and Communicationsbusiness.industryInter-domainComputer scienceAssortativityNetwork engineeringInternet trafficComplex networkTraffic flowcomputer.software_genreFile sharingThe InternetData miningbusinesscomputerTraffic generation modelComputer networkComputer Networks
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An efficient distributed algorithm for generating and updating multicast trees

2006

As group applications are becoming widespread, efficient network utilization becomes a growing concern. Multicast transmission represents a necessary lower network service for the wide diffusion of new multimedia network applications. Multicast transmission may use network resources more efficiently than multiple point-to-point messages; however, creating optimal multicast trees (Steiner Tree Problem in networks) is prohibitively expensive. This paper proposes a distributed algorithm for the heuristic solution of the Steiner Tree Problem, allowing the construction of effective distribution trees using a coordination protocol among the network nodes. Furthermore, we propose a novel distribut…

Computer Networks and Communicationscomputer.internet_protocolComputer scienceDistributed computingNetwork ontology.Distance Vector Multicast Routing ProtocolMultimedia Broadcast Multicast ServiceSteiner tree problemTheoretical Computer Sciencesymbols.namesakeArtificial IntelligenceConvergence (routing)Multicast addressXcastCommunication complexityPragmatic General MulticastIntelligent systemSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMulticast transmissionProtocol Independent MulticastMulticastInter-domainbusiness.industryNode (networking)Programmable networkComputer Graphics and Computer-Aided DesignSource-specific multicastHardware and ArchitectureDistributed algorithmNetwork serviceReliable multicastsymbolsSituation calculuIP multicastbusinesscomputerSoftwareComputer networkParallel Computing
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New separation between $s(f)$ and $bs(f)$

2011

In this note we give a new separation between sensitivity and block sensitivity of Boolean functions: $bs(f)=(2/3)s(f)^2-(1/3)s(f)$.

Computer Science - Computational Complexity
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