959 resultados para White noise


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The Rapid Oscillations in the Solar Atmosphere instrument reveals solar atmospheric fluctuations at high frequencies. Spectra of variations of the G-band intensity (IG ) and Ca II K-line intensity (IK ) show correlated fluctuations above white noise to frequencies beyond 300 mHz and 50 mHz, respectively. The noise-corrected G-band spectrum for f = 28-326 mHz shows a power law with exponent -1.21 ± 0.02, consistent with the presence of turbulent motions. G-band spectral power in the 25-100 mHz ("UHF") range is concentrated at the locations of magnetic bright points in the intergranular lanes and is highly intermittent in time. The intermittence of the UHF G-band fluctuations, shown by a positive kurtosis ?, also suggests turbulence. Combining values of IG , IK , UHF power, and ? reveals two distinct states of the solar atmosphere. State 1, including almost all the data, is characterized by low IG , IK , and UHF power and ? ˜ 6. State 2, including only a very small fraction of the data, is characterized by high IG , IK , and UHF power and ? ˜ 3. Superposed epoch analysis shows that the UHF power peaks simultaneously with spatio-temporal IG maxima in either state. For State 1, IK shows 3.5 minute chromospheric oscillations with maxima occurring 21 s after IG maxima implying a 150-210 km effective height difference. However, for State 2 the IK and IG maxima are simultaneous; in this highly magnetized environment sites of G-band and K-line emission may be spatially close together.

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The Next Generation Transit Survey (NGTS) is a new ground-based sky survey designed to find transiting Neptunes and super-Earths. By covering at least sixteen times the sky area of Kepler we will find small planets around stars that are sufficiently bright for radial velocity confirmation, mass determination and atmospheric characterisation. The NGTS instrument will consist of an array of twelve independently pointed 20cm telescopes fitted with red-sensitive CCD cameras. It will be constructed at the ESO Paranal Observatory, thereby benefiting from the very best photometric conditions as well as follow up synergy with the VLT and E-ELT. Our design has been verified through the operation of two prototype instruments, demonstrating white noise characteristics to sub-mmag photometric precision. Detailed simulations show that about thirty bright super-Earths and up to two hundred Neptunes could be discovered. Our science operations are due to begin in 2014.

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A novel method for the detection of linear decalibration of sensors is proposed. The presence of a fault is indicated as a change in the mean of a white noise sequence. A simulation example is described which shows the success of the technique.

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We investigate intensity variations and energy deposition in five coronal loops in active region cores. These were selected for their strong variability in the AIA/SDO 94 Å intensity channel. We isolate the hot Fe XVIII and Fe XXI components of the 94 Å and 131 Å by modeling and subtracting the "warm" contributions to the emission. HMI/SDO data allow us to focus on "inter-moss" regions in the loops. The detailed evolution of the inter-moss intensity time series reveals loops that are impulsively heated in a mode compatible with a nanoflare storm, with a spike in the hot 131 Å signals leading and the other five EUV emission channels following in progressive cooling order. A sharp increase in electron temperature tends to follow closely after the hot 131 Å signal confirming the impulsive nature of the process. A cooler process of growing emission measure follows more slowly. The Fourier power spectra of the hot 131 Å signals, when averaged over the five loops, present three scaling regimes with break frequencies near 0.1 min–1 and 0.7 min–1. The low frequency regime corresponds to 1/f noise; the intermediate indicates a persistent scaling process and the high frequencies show white noise. Very similar results are found for the energy dissipation in a 2D "hybrid" shell model of loop magneto-turbulence, based on reduced magnetohydrodynamics, that is compatible with nanoflare statistics. We suggest that such turbulent dissipation is the energy source for our loops

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Using the Rapid Oscillation in the Solar Atmosphere (ROSA) instrument at the Dunn Solar Telescope we have found that the spectra of fluctuations of the G-band (cadence 1.05 s) and Ca II K-line (cadence 4.2 s) intensities show correlated fluctuations above white noise out to frequencies beyond 300 mHz and up to 70 mHz, respectively. The noise-corrected G-band spectrum presents a scaling range (Ultra High Frequency “UHF”) for f = 25-100 mHz, with an exponent consistent with the presence of turbulent motions. The UHF power, is concentrated at the locations of magnetic bright points in the intergranular lanes, it is highly intermittent in time and characterized by a positive kurtosis κ. Combining values of G-band and K-line intensities, the UHF power, and κ, reveals two distinct “states” of the internetwork solar atmosphere. State 1, with κ ≍ 6, which includes almost all the data, is characterized by low intensities and low UHF power. State 2, with κ ≍ 3, including a very small fraction of the data, is characterized by high intensities and high UHF power. Superposed epoch analysis shows that for State 1, the K-line intensity presents 3.5 min chromospheric oscillations with maxima occurring 21 s after G-band intensity maxima implying a 150-210 km effective height difference. For State 2, the G-band and K-line intensity maxima are simultaneous, suggesting that in the highly magnetized environment sites of G-band and K-line emission may be spatially close together. Analysis of observations obtained with Hinode/SOT confirm a scaling range in the G-band spectrum up to 53 mHz also consistent with turbulent motions as well as the identification of two distinct states in terms of the H-line intensity and G-band power as functions of G-band intensity.

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While current speech recognisers give acceptable performance in carefully controlled environments, their performance degrades rapidly when they are applied in more realistic situations. Generally, the environmental noise may be classified into two classes: the wide-band noise and narrow band noise. While the multi-band model has been shown to be capable of dealing with speech corrupted by narrow-band noise, it is ineffective for wide-band noise. In this paper, we suggest a combination of the frequency-filtering technique with the probabilistic union model in the multi-band approach. The new system has been tested on the TIDIGITS database, corrupted by white noise, noise collected from a railway station, and narrow-band noise, respectively. The results have shown that this approach is capable of dealing with noise of narrow-band or wide-band characteristics, assuming no knowledge about the noisy environment.

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Trabalho de Dissertação de Natureza Científica para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Estruturas

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Sleep spindles are synchronized 11-15 Hz electroencephalographic (EEG) oscillations predominant during nonrapid-eye-movement sleep (NREMS). Rhythmic bursting in the reticular thalamic nucleus (nRt), arising from interplay between Ca(v)3.3-type Ca(2+) channels and Ca(2+)-dependent small-conductance-type 2 (SK2) K(+) channels, underlies spindle generation. Correlative evidence indicates that spindles contribute to memory consolidation and protection against environmental noise in human NREMS. Here, we describe a molecular mechanism through which spindle power is selectively extended and we probed the actions of intensified spindling in the naturally sleeping mouse. Using electrophysiological recordings in acute brain slices from SK2 channel-overexpressing (SK2-OE) mice, we found that nRt bursting was potentiated and thalamic circuit oscillations were prolonged. Moreover, nRt cells showed greater resilience to transit from burst to tonic discharge in response to gradual depolarization, mimicking transitions out of NREMS. Compared with wild-type littermates, chronic EEG recordings of SK2-OE mice contained less fragmented NREMS, while the NREMS EEG power spectrum was conserved. Furthermore, EEG spindle activity was prolonged at NREMS exit. Finally, when exposed to white noise, SK2-OE mice needed stronger stimuli to arouse. Increased nRt bursting thus strengthens spindles and improves sleep quality through mechanisms independent of EEG slow waves (<4 Hz), suggesting SK2 signaling as a new potential therapeutic target for sleep disorders and for neuropsychiatric diseases accompanied by weakened sleep spindles.

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Dans ce mémoire, nous avons utilisé le logiciel R pour la programmation.

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Le prix efficient est latent, il est contaminé par les frictions microstructurelles ou bruit. On explore la mesure et la prévision de la volatilité fondamentale en utilisant les données à haute fréquence. Dans le premier papier, en maintenant le cadre standard du modèle additif du bruit et le prix efficient, on montre qu’en utilisant le volume de transaction, les volumes d’achat et de vente, l’indicateur de la direction de transaction et la différence entre prix d’achat et prix de vente pour absorber le bruit, on améliore la précision des estimateurs de volatilité. Si le bruit n’est que partiellement absorbé, le bruit résiduel est plus proche d’un bruit blanc que le bruit original, ce qui diminue la misspécification des caractéristiques du bruit. Dans le deuxième papier, on part d’un fait empirique qu’on modélise par une forme linéaire de la variance du bruit microstructure en la volatilité fondamentale. Grâce à la représentation de la classe générale des modèles de volatilité stochastique, on explore la performance de prévision de différentes mesures de volatilité sous les hypothèses de notre modèle. Dans le troisième papier, on dérive de nouvelles mesures réalizées en utilisant les prix et les volumes d’achat et de vente. Comme alternative au modèle additif standard pour les prix contaminés avec le bruit microstructure, on fait des hypothèses sur la distribution du prix sans frictions qui est supposé borné par les prix de vente et d’achat.

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This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.

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Chaos is a subject oftopical interest and, studied in great detail in relation to its relevance in almost all branches of science, which include physical, chemical, and biological fields. Chaos in the literal sense signifies utter confusion, but the scientific community has differentiated chaos as deterministic chaos and white noise. Deterministic chaos implies the complex behaviour of systems, which are governed by deterministic laws. Behaviour of such systems often become unpredictable in the long run. This unpredictability arises from the sensitivity of the system to its initial conditions. The essential requirement for ‘sensitivity to initial condition’ is nonlinearity of the system. The only method for determining the future of such systems is numerically simulating its final state from a set ofinitial conditions. Synchronisation

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The decadal predictability of three-dimensional Atlantic Ocean anomalies is examined in a coupled global climate model (HadCM3) using a Linear Inverse Modelling (LIM) approach. It is found that the evolution of temperature and salinity in the Atlantic, and the strength of the meridional overturning circulation (MOC), can be effectively described by a linear dynamical system forced by white noise. The forecasts produced using this linear model are more skillful than other reference forecasts for several decades. Furthermore, significant non-normal amplification is found under several different norms. The regions from which this growth occurs are found to be fairly shallow and located in the far North Atlantic. Initially, anomalies in the Nordic Seas impact the MOC, and the anomalies then grow to fill the entire Atlantic basin, especially at depth, over one to three decades. It is found that the structure of the optimal initial condition for amplification is sensitive to the norm employed, but the initial growth seems to be dominated by MOC-related basin scale changes, irrespective of the choice of norm. The consistent identification of the far North Atlantic as the most sensitive region for small perturbations suggests that additional observations in this region would be optimal for constraining decadal climate predictions.

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Diebold and Lamb (1997) argue that since the long-run elasticity of supply derived from the Nerlovian model entails a ratio of random variables, it is without moments. They propose minimum expected loss estimation to correct this problem but in so-doing ignore the fact that a non white-noise-error is implicit in the model. We show that, as a consequence the estimator is biased and demonstrate that Bayesian estimation which fully accounts for the error structure is preferable.

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Cercal hairs represent in cricket a wind sensitive escape system, able to detect the airflow generated from predating species. These sensors have been studied as a biomimetic concept to allow the development of MEMS for biomedical use. In particular, the behaviour of the hairs, including airflow response, resonant frequency and damping, has been investigated up to a frequency of 20 kHz. The microscopic nature of the hairs, the complex vibrations of excited hairs and the high damping of the system suggested that the use of Laser Doppler vibrometry could possibly improve the test performance. Two types of tests were performed: in the first case the hairs were indirectly excited using the signal obtained from a vibrating aluminium plate, whilst in the second case the hairs were directly excited using a white noise chirp. The results from the first experiment indicated that the hairs move in-phase with the exciting signal up to frequencies in the order of 10 kHz, responding to the vibration modes of the plate with a signal attenuation of 12 to 20 dB. The chirp experiment revealed the presence of rotational resonant modes at 6850 and 11300 Hz. No clear effect of hair length was perceivable on the vibration response of the filiform sensors. The obtained results proved promising to support the mechanical and vibration characterisation of the hairs and suggest that scanning Laser vibrometry can be used extensively on highly dampened biological materials.