832 resultados para recursive filtering


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Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here we present a graphics processor unit (GPU) based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to auto-regressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and 4 times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a 7-day high-resolution ECG is computed within less than 3 seconds. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.

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PURPOSE To observe changes in fundus autofluorescence 2 years after implantation of blue light-filtering (yellow-tinted) and ultraviolet light-filtering (colorless) intraocular lenses (IOLs). SETTING Department of Ophthalmology and Visual Science, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan, and the Department of Ophthalmology, University of Bern, Bern, Switzerland. DESIGN Prospective comparative observational study. METHODS Patients were enrolled who had cataract surgery with implantation of a yellow-tinted or colorless IOL and for whom images were obtained on which the fundus autofluorescence was measurable using the Heidelberg Retina Angiogram 2 postoperatively. The fundus autofluorescence in the images was classified into 8 abnormal patterns based on the classification of the International Fundus Autofluorescence Classification Group, The presence of normal fundus autofluorescence, geographic atrophy, and wet age-related macular degeneration (AMD) also was recorded. The fundus findings at baseline and 2 years postoperatively were compared. RESULTS Fifty-two eyes with a yellow-tinted IOL and 79 eyes with a colorless IOL were included. Abnormal fundus autofluorescence did not develop or increase in the yellow-tinted IOL group; however, progressive abnormal fundus autofluorescence developed or increased in 12 eyes (15.2%) in the colorless IOL group (P = .0016). New drusen, geographic atrophy, and choroidal neovascularization were observed mainly in the colorless IOL group. The incidence of AMD was statistically significantly higher in the colorless IOL group (P = .042). CONCLUSIONS Two years after cataract surgery, significant differences were seen in the progression of abnormal fundus autofluorescence between the 2 groups. The incidence of AMD was lower in eyes with a yellow-tinted IOL. FINANCIAL DISCLOSURE No author has a financial or proprietary interest in any material or method mentioned.

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Theory on plant succession predicts a temporal increase in the complexity of spatial community structure and of competitive interactions: initially random occurrences of early colonising species shift towards spatially and competitively structured plant associations in later successional stages. Here we use long-term data on early plant succession in a German post mining area to disentangle the importance of random colonisation, habitat filtering, and competition on the temporal and spatial development of plant community structure. We used species co-occurrence analysis and a recently developed method for assessing competitive strength and hierarchies (transitive versus intransitive competitive orders) in multispecies communities. We found that species turnover decreased through time within interaction neighbourhoods, but increased through time outside interaction neighbourhoods. Successional change did not lead to modular community structure. After accounting for species richness effects, the strength of competitive interactions and the proportion of transitive competitive hierarchies increased through time. Although effects of habitat filtering were weak, random colonization and subsequent competitive interactions had strong effects on community structure. Because competitive strength and transitivity were poorly correlated with soil characteristics, there was little evidence for context dependent competitive strength associated with intransitive competitive hierarchies.

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We propose dual-domain filtering, an image processing paradigm that couples spatial domain with frequency domain filtering. Our dual-domain defined filter removes artifacts like residual noise of other image denoising methods and compression artifacts. Moreover, iterating the filter achieves state-of-the-art image denoising results, but with a much simpler algorithm than competing approaches. The simplicity and versatility of the dual-domain filter makes it an attractive tool for image processing.

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State of the art methods for disparity estimation achieve good results for single stereo frames, but temporal coherence in stereo videos is often neglected. In this paper we present a method to compute temporally coherent disparity maps. We define an energy over whole stereo sequences and optimize their Conditional Random Field (CRF) distributions using mean-field approximation. We introduce novel terms for smoothness and consistency between the left and right views, and perform CRF optimization by fast, iterative spatio-temporal filtering with linear complexity in the total number of pixels. Our results rank among the state of the art while having significantly less flickering artifacts in stereo sequences.

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Based on an order-theoretic approach, we derive sufficient conditions for the existence, characterization, and computation of Markovian equilibrium decision processes and stationary Markov equilibrium on minimal state spaces for a large class of stochastic overlapping generations models. In contrast to all previous work, we consider reduced-form stochastic production technologies that allow for a broad set of equilibrium distortions such as public policy distortions, social security, monetary equilibrium, and production nonconvexities. Our order-based methods are constructive, and we provide monotone iterative algorithms for computing extremal stationary Markov equilibrium decision processes and equilibrium invariant distributions, while avoiding many of the problems associated with the existence of indeterminacies that have been well-documented in previous work. We provide important results for existence of Markov equilibria for the case where capital income is not increasing in the aggregate stock. Finally, we conclude with examples common in macroeconomics such as models with fiat money and social security. We also show how some of our results extend to settings with unbounded state spaces.

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Climate change mediates marine chemical and physical environments and therefore influences marine organisms. While increasing atmospheric CO2 level and associated ocean acidification has been predicted to stimulate marine primary productivity and may affect community structure, the processes that impact food chain and biological CO2 pump are less documented. We hypothesized that copepods, as the secondary marine producer, may respond to future changes in seawater carbonate chemistry associated with ocean acidification due to increasing atmospheric CO2 concentration. Here, we show that the copepod, Centropages tenuiremis, was able to perceive the chemical changes in seawater induced under elevated CO2 concentration (>1700 µatm, pH < 7.60) with avoidance strategy. The copepod's respiration increased at the elevated CO2 (1000 µatm), associated acidity (pH 7.83) and its feeding rates also increased correspondingly, except for the initial acclimating period, when it fed less. Our results imply that marine secondary producers increase their respiration and feeding rate in response to ocean acidification to balance the energy cost against increased acidity and CO2 concentration.

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Recently, vision-based advanced driver-assistance systems (ADAS) have received a new increased interest to enhance driving safety. In particular, due to its high performance–cost ratio, mono-camera systems are arising as the main focus of this field of work. In this paper we present a novel on-board road modeling and vehicle detection system, which is a part of the result of the European I-WAY project. The system relies on a robust estimation of the perspective of the scene, which adapts to the dynamics of the vehicle and generates a stabilized rectified image of the road plane. This rectified plane is used by a recursive Bayesian classi- fier, which classifies pixels as belonging to different classes corresponding to the elements of interest of the scenario. This stage works as an intermediate layer that isolates subsequent modules since it absorbs the inherent variability of the scene. The system has been tested on-road, in different scenarios, including varied illumination and adverse weather conditions, and the results have been proved to be remarkable even for such complex scenarios.

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Se definen conceptos y se aplica el teorema de Valverde para escribir un algoritmo que computa bases de similaridades. This paper studies sorne theory and methods to build a representation theorem basis of a similarity from the basis of its subsimilarities, providing an alternative recursive method to compute the basis of a similarity.

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This letter presents a novel recursive active filter topology that provides dual-band performance, with independent tuning capability in both bands. The dual-band operation is achieved by using two independent feedback lines. Additionally, linear phase shifters based on left-handed cells are included in these two branches in order to tune the center frequency of both pass bands.

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In this paper, we propose a particle filtering (PF) method for indoor tracking using radio frequency identification (RFID) based on aggregated binary measurements. We use an Ultra High Frequency (UHF) RFID system that is composed of a standard RFID reader, a large set of standard passive tags whose locations are known, and a newly designed, special semi-passive tag attached to an object that is tracked. This semi-passive tag has the dual ability to sense the backscatter communication between the reader and other passive tags which are in its proximity and to communicate this sensed information to the reader using backscatter modulation. We refer to this tag as a sense-a-tag (ST). Thus, the ST can provide the reader with information that can be used to determine the kinematic parameters of the object on which the ST is attached. We demonstrate the performance of the method with data obtained in a laboratory environment.