Search results for "False alarm"

showing 10 items of 23 documents

Power allocation optimization in OFDM-based cognitive radios based on sensing information

2011

Owing to the non-zero probability of the missed detection and false alarm of active primary transmission, a certain degree of performance degradation of the primary user (PU) from cognitive radio users (CRs) is unavoidable. In this paper, we consider OFDM-based communication systems and present efficient algorithms to maximize the total rate of the CR by optimizing jointly both the detection operation and the power allocation, taking into account the influence of the probabilities of missed detection and false alarm, namely, the sensing accuracy. The optimization problem can be formulated as a two-variable non-convex problem, which can be solved approximately by using an alternating directi…

Mathematical optimizationOptimization problemCognitive radioTransmission (telecommunications)Computer scienceOrthogonal frequency-division multiplexingConvex optimizationFalse alarmCommunications systemInterference (wave propagation)2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Deep learning for core-collapse supernova detection

2021

The detection of gravitational waves from core-collapse supernova (CCSN) explosions is a challenging task, yet to be achieved, in which it is key the connection between multiple messengers, including neutrinos and electromagnetic signals. In this work, we present a method for detecting these kind of signals based on machine learning techniques. We tested its robustness by injecting signals in the real noise data taken by the Advanced LIGO-Virgo network during the second observing run, O2. We trained a newly developed Mini-Inception Resnet neural network using time-frequency images corresponding to injections of simulated phenomenological signals, which mimic the waveforms obtained in 3D num…

PhysicsArtificial neural networkPhysics and Astronomy (miscellaneous)Gravitational wavebusiness.industryDeep learningType II supernovaConstant false alarm rateSupernovaRobustness (computer science)WaveformGravitational waves; machine learning; supernovaArtificial intelligenceNeutrinobusinessAlgorithmPhysical Review D
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Implementation of a two stage fully-blind self-adapted spectrum sensing algorithm

2017

In this paper, an experimental validation of a combined two-stage detector called 2EMC is carried out. The detector is proposed in [1]. The 2EMC is composed of energy detector as a primary stage and maximum-minimum eigenvalue detector as a secondary stage. The 2EMC outperforms the two individual detectors in terms of the probability of detection for the same probability of false alarm. Regarding the complexity measured in the sensing time, the 2EMC sensing time is bounded by the sensing times of the two individual detectors. 2EMC incorporates noise estimation that is used by the energy detector, which makes it fully-blind and self-adapted detector. The noise estimator performance is express…

Physics::Instrumentation and DetectorsComputer scienceDetectorEstimator020206 networking & telecommunications020302 automobile design & engineering02 engineering and technologyStatistical powerNoiseSignal-to-noise ratio0203 mechanical engineeringBounded function0202 electrical engineering electronic engineering information engineeringHigh Energy Physics::ExperimentFalse alarmAlgorithmEnergy (signal processing)2017 11th International Conference on Signal Processing and Communication Systems (ICSPCS)
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Detection and Recognition of Target Signals in Radar Clutter via Adaptive CFAR Tests

2006

In this paper, adaptive CFAR tests are described which allow one to classify radar clutter into one of several major categories, including bird, weather, and target classes. These tests do not require the arbitrary selection of priors as in the Bayesian classifier. The decision rule of the recognition techniques is in the form of associating the p-dimensional vector of observations on the object with one of the m specific classes. When there is the possibility that the object does not belong to any of the m classes, then this object is to be classified as belonging to one of the m classes or to class m+1 whose distribution is unspecified. The tests are invariant to intensity changes in the …

Radar trackerComputer sciencebusiness.industryPattern recognitionlaw.inventionConstant false alarm rateNaive Bayes classifierSpace-time adaptive processinglawStationary target indicationClutterFalse alarmArtificial intelligenceRadarbusiness2006 IEEE International Conference on Industrial Technology
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Deep learning algorithms for gravitational waves core-collapse supernova detection

2021

The detection of gravitational waves from core-collapse supernova (CCSN) explosions is a challenging task, yet to be achieved, in which it is key the connection between multiple messengers, including neutrinos and electromagnetic signals. In this work, we present a method for detecting these kind of signals based on machine learning techniques. We tested its robustness by injecting signals in the real noise data taken by the Advanced LIGO-Virgo network during the second observation run, O2. We trained three newly developed convolutional neural networks using time-frequency images corresponding to injections of simulated phenomenological signals, which mimic the waveforms obtained in 3D nume…

Signal-to-noise ratioNoise (signal processing)Computer sciencebusiness.industryGravitational waveRobustness (computer science)Deep learningArtificial intelligencebusinessConvolutional neural networkAlgorithmTime–frequency analysisConstant false alarm rate2021 International Conference on Content-Based Multimedia Indexing (CBMI)
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PIECEWISE ANOMALY DETECTION USING MINIMAL LEARNING MACHINE FOR HYPERSPECTRAL IMAGES

2021

Abstract. Hyperspectral imaging, with its applications, offers promising tools for remote sensing and Earth observation. Recent development has increased the quality of the sensors. At the same time, the prices of the sensors are lowering. Anomaly detection is one of the popular remote sensing applications, which benefits from real-time solutions. A real-time solution has its limitations, for example, due to a large amount of hyperspectral data, platform’s (drones or a cube satellite) constraints on payload and processing capability. Other examples are the limitations of available energy and the complexity of the machine learning models. When anomalies are detected in real-time from the hyp…

TechnologyMinimal Learning Machinehyperspectral imagingComputer scienceRemote sensing applicationConstant false alarm rateRobustness (computer science)Applied optics. Photonicshyperspektrikuvantaminenbusiness.industryTspektrikuvausPayload (computing)Hyperspectral imagingPattern recognitionEngineering (General). Civil engineering (General)anomaly detectionTA1501-1820piecewise approachmachine learningkoneoppiminenPiecewiseAnomaly detectionNoise (video)Artificial intelligenceTA1-2040businessreal-time computationISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Study time effects in recognition memory.

2004

We empirically tested the assumption that study time increases recognition accuracy because the storage of information is better when study time is longer as Shiffrin and colleagues have reported, an assumption common to parallel models of recognition. In the present study with 123 subjects, we examined the effect of item strength on four measures: hit rate, false alarm rate, d′, and β, for a single-word recognition task with longer study times than those usually used in the literature. Analysis indicated significant increase for hit rate and d′ and a decrease in false alarm rate, as one goes from weak to stronger study conditions, and a change in ln(β) when study time is greater than 1 se…

Time Factorsbusiness.industrySpeech recognition05 social sciencesExperimental and Cognitive PsychologyRecognition Psychology030229 sport sciences050105 experimental psychologySensory SystemsTask (project management)Constant false alarm rate03 medical and health sciences0302 clinical medicineText miningMemoryHit rateHumans0501 psychology and cognitive sciencesPsychologybusinessSocial psychologyRecognition memoryPerceptual and motor skills
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Hydro-Acoustic Target Detection

2014

This chapter presents an example of utilization of the discrete–time wavelet packets, which are described in Sect. 9.1, to classification of acoustic signals and detection of a target. The methodology based on wavelet packets is applied to a problem of detection of a boat of a certain type when other background noises are present. The solution is obtained via analysis of boat’s hydro-acoustic signature against an existing database of recorded and processed hydro-acoustic signals. The signals are characterized by the distribution of their energies among blocks of wavelet packet coefficients.

WaveletComputer scienceNetwork packetbusiness.industryFeature vectorPattern recognitionArtificial intelligenceFalse alarmLinear discriminant analysisbusinessGeneralLiterature_MISCELLANEOUSSignature (logic)Wavelet packet decomposition
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GW170814: A Three-Detector Observation of Gravitational Waves from a Binary Black Hole Coalescence

2017

On August 14, 2017 at 10 30:43 UTC, the Advanced Virgo detector and the two Advanced LIGO detectors coherently observed a transient gravitational-wave signal produced by the coalescence of two stellar mass black holes, with a false-alarm rate of 1 in 27 000 years. The signal was observed with a three-detector network matched-filter signal-to-noise ratio of 18. The inferred masses of the initial black holes are 30.5-3.0+5.7M and 25.3-4.2+2.8M (at the 90% credible level). The luminosity distance of the source is 540-210+130 Mpc, corresponding to a redshift of z=0.11-0.04+0.03. A network of three detectors improves the sky localization of the source, reducing the area of the 90% credible regio…

[ PHYS.ASTR ] Physics [physics]/Astrophysics [astro-ph]AstronomyCredible regionsGeneral Physics and Astronomyadvanced ligoADVANCED LIGOAstrophysicsdetector: network01 natural sciencesGeneral Relativity and Quantum CosmologylocalizationVIRGO detectorFilter signalsGW170814TOOLLIGOInterferometerGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)010303 astronomy & astrophysicsQCchoiceQBHigh Energy Astrophysical Phenomena (astro-ph.HE)PhysicsSignal to noise ratioSettore FIS/01 - Fisica SperimentaleGravitational effectstoolFalse alarm rateCHOICEAntenna responseGravitational-wave signalsDetector networks[PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc]Astrophysics - High Energy Astrophysical Phenomenagravitational radiation: polarizationSignal processingAstrophysics::High Energy Astrophysical Phenomenablack hole: binary: coalescenceFOS: Physical sciencesGeneral Relativity and Quantum Cosmology (gr-qc)Astrophysics::Cosmology and Extragalactic Astrophysicsgravitational radiation: direct detectionGravitational-wave astronomy[ PHYS.GRQC ] Physics [physics]/General Relativity and Quantum Cosmology [gr-qc]General Relativity and Quantum CosmologyPhysics and Astronomy (all)Binary black hole0103 physical sciencesGW151226ddc:530KAGRASTFCGw150914GW170814 Virgo LIGO010308 nuclear & particles physicsGravitational wavePhysiqueVirgogravitational radiationAstronomyRCUKMatched filtersblack hole: massStarsLIGOgravitational radiation detectorBlack holeradiationVIRGOPhysics and AstronomyTesting Relativistic Gravitygravitationgravitational radiation: emissionStellar-mass black holesRADIATIONStellar black holeHigh Energy Physics::ExperimentAntennasDewey Decimal Classification::500 | Naturwissenschaften::530 | Physik[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]
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An Effective Double Sampling Scheme for thecControl Chart

2013

In the present paper is developed a statistical process control inspection procedure based on a new simple-to-implement and effective double sampling scheme for the c control chart, aimed at the minimization of the number of inspected observation units and warranting fixed levels for the type I and II error risks. In particular, the formulations of the false alarm risk α, the power P of the chart, and the expected number of inspected observation units for the developed inspection procedure are given, whereas a macro of Microsoft Excel is adopted to solve the tackled problem. In order to illustrate the application of the developed approach and to investigate on the influence of several opera…

c-chartMathematical optimizationChartComputer scienceControl chartFalse alarmMinificationManagement Science and Operations ResearchMacroSafety Risk Reliability and QualityStatistical process controlShewhart individuals control chartReliability engineeringQuality and Reliability Engineering International
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