899 resultados para Transformada de Wavelet
Resumo:
We study the nature of quiet-Sun oscillations using multi-wavelength observations from TRACE, Hinode, and SOHO. The aim is to investigate the existence of propagating waves in the solar chromosphere and the transition region by analyzing the statistical distribution of power in different locations, e.g. in bright magnetic (network), bright non-magnetic and dark non-magnetic (inter-network) regions, separately. We use Fourier power and phase-difference techniques combined with a wavelet analysis. Two-dimensional Fourier power maps were constructed in the period bands 2 -aEuro parts per thousand 4 minutes, 4 -aEuro parts per thousand 6 minutes, 6 -aEuro parts per thousand 15 minutes, and beyond 15 minutes. We detect the presence of long-period oscillations with periods between 15 and 30 minutes in bright magnetic regions. These oscillations were detected from the chromosphere to the transition region. The Fourier power maps show that short-period powers are mainly concentrated in dark regions whereas long-period powers are concentrated in bright magnetic regions. This is the first report of long-period waves in quiet-Sun network regions. We suggest that the observed propagating oscillations are due to magnetoacoustic waves, which can be important for the heating of the solar atmosphere.
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Compressive Sensing (CS) is a new sensing paradigm which permits sampling of a signal at its intrinsic information rate which could be much lower than Nyquist rate, while guaranteeing good quality reconstruction for signals sparse in a linear transform domain. We explore the application of CS formulation to music signals. Since music signals comprise of both tonal and transient nature, we examine several transforms such as discrete cosine transform (DCT), discrete wavelet transform (DWT), Fourier basis and also non-orthogonal warped transforms to explore the effectiveness of CS theory and the reconstruction algorithms. We show that for a given sparsity level, DCT, overcomplete, and warped Fourier dictionaries result in better reconstruction, and warped Fourier dictionary gives perceptually better reconstruction. “MUSHRA” test results show that a moderate quality reconstruction is possible with about half the Nyquist sampling.
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Automated security is one of the major concerns of modern times. Secure and reliable authentication systems are in great demand. A biometric trait like the finger knuckle print (FKP) of a person is unique and secure. Finger knuckle print is a novel biometric trait and is not explored much for real-time implementation. In this paper, three different algorithms have been proposed based on this trait. The first approach uses Radon transform for feature extraction. Two levels of security are provided here and are based on eigenvalues and the peak points of the Radon graph. In the second approach, Gabor wavelet transform is used for extracting the features. Again, two levels of security are provided based on magnitude values of Gabor wavelet and the peak points of Gabor wavelet graph. The third approach is intended to authenticate a person even if there is a damage in finger knuckle position due to injury. The FKP image is divided into modules and module-wise feature matching is done for authentication. Performance of these algorithms was found to be much better than very few existing works. Moreover, the algorithms are designed so as to implement in real-time system with minimal changes.
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Daily rainfall datasets of 10 years (1998-2007) of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) version 6 and India Meteorological Department (IMD) gridded rain gauge have been compared over the Indian landmass, both in large and small spatial scales. On the larger spatial scale, the pattern correlation between the two datasets on daily scales during individual years of the study period is ranging from 0.4 to 0.7. The correlation improved significantly (similar to 0.9) when the study was confined to specific wet and dry spells each of about 5-8 days. Wavelet analysis of intraseasonal oscillations (ISO) of the southwest monsoon rainfall show the percentage contribution of the major two modes (30-50 days and 10-20 days), to be ranging respectively between similar to 30-40% and 5-10% for the various years. Analysis of inter-annual variability shows the satellite data to be underestimating seasonal rainfall by similar to 110 mm during southwest monsoon and overestimating by similar to 150 mm during northeast monsoon season. At high spatio-temporal scales, viz., 1 degrees x1 degrees grid, TMPA data do not correspond to ground truth. We have proposed here a new analysis procedure to assess the minimum spatial scale at which the two datasets are compatible with each other. This has been done by studying the contribution to total seasonal rainfall from different rainfall rate windows (at 1 mm intervals) on different spatial scales (at daily time scale). The compatibility spatial scale is seen to be beyond 5 degrees x5 degrees average spatial scale over the Indian landmass. This will help to decide the usability of TMPA products, if averaged at appropriate spatial scales, for specific process studies, e.g., cloud scale, meso scale or synoptic scale.
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We present new data on the strength of oceanic lithosphere along the Ninetyeast Ridge (NER) from two independent methods: spectral analysis (Bouguer coherence) using the fan wavelet transform technique, and spatial analysis (flexure inversion) with the convolution method. The two methods provide effective elastic thickness (T-e) patterns that broadly complement each other, and correlate well with known surface structures and regional-scale features. Furthermore, our study presents a new high resolution database on the Moho configuration, which obeys flexural isostasy, and exhibit regional correlations with the T-e variations. A continuous ridge structure with a much lower T-e value than that of normal oceanic lithosphere provides strong support for the hotspot theory. The derived T-e values vary over the northern (higher T-e similar to 10-20 km), central (anomalously low T-e similar to 0-5 km), and southern (low T-e similar to 5 km) segments of the NER. The lack of correlation of the T-e value with the progressive aging of the lithosphere implies differences in thermo-mechanical setting of the crust and underlying mantle in different parts of the NER, again indicating diversity in their evolution. The anomalously low T-e and deeper Moho (similar to 22 km) estimates of the central NER (between 0.5 degrees N and 17 degrees S) are attributed to the interaction of a hotspot with the Wharton spreading ridge that caused significant thermal rejuvenation and hence weakening of the lithosphere. The higher mechanical strength values in the northern NER (north of 0.5 degrees N) may support the idea of off-ridge emplacement and a relatively large plate motion at the time of volcanism. The low T-e and deeper Moho (similar to 22 km) estimates in the southern part (south of 17 degrees S) suggest that the lithosphere was weak and therefore younger at the time of volcanism, and this supports the idea that the southern NER was emplaced on the edge of the Indian plate. (C) 2013 Elsevier B.V. All rights reserved.
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Stiffener is one of the major components of aircraft structures to increase the load carrying capacity. Damage in the stiffener, mostly in the form of crack is an unavoidable problem in aerospace structures. Stiffener is bonded to the inner side of the aircraft panel which is not accessible for immediate inspection. A sensor-actuator network can be placed on the outer side of the panel that is accessible. Ultrasonic lamb waves are transmitted through stiffener using the sensoractuator network for detecting the presence of damages. The sensor-actuator network is placed on both halves of the stiffened section on the accessible surface of the plate. Detecting damage in stiffener by using this technique has significant potential for SHM technology. One of the major objectives of the present work is to determine the smallest detectable crack on the stiffener using the proposed technique. Wavelet based damage parameter correlation studies are carried out. In the proposed scheme, with increase in the damage size along the stiffener, it is found that the amplitude of the received signal decreases monotonically. The advantage of this technique is that the stiffened panels need not be disassembled in a realistic deployment of SHM system.
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A new evaluation of the elastic thickness (Te) structure of the Indian Shield, derived from isotropic fan wavelet methodology, documents spatial variations of lithospheric deformation in different tectonic provinces correlated with episodic tectono-thermal events. The Te variations corroborated by shear velocity, crustal thickness, and seismogenic thickness reveal the heterogeneous rheology of the Indian lithosphere. The thinned, attenuated lithosphere beneath Peninsular India is considered to be the reason for its mechanically weak strength (<30 km), where a decoupled crust-mantle rheology under different surface/subsurface loading structures may explain the prominent low Te patterns. The arcuate Te structure of the Western Dharwar province and a NNE-trending band of low Te anomaly in the Southern Granulite Terrane are intriguing patterns. The average Te values (40-50 km) of the Central Indian Tectonic Zone, the Bastar Craton, and the northern Eastern Ghats Mobile Belt are suggestive of old, stable, Indian lithosphere, which was not affected by any major tectono-thermal events after cratonic stabilization. We propose that the anomalously high Te (60-85 km) and high S-wave velocity zone to the north of the Narmada-Son Lineament, mainly in NW Himalaya, and the northern Aravalli and Bundelkhand Cratons, suggest that Archean lithosphere characterized by a high velocity mantle keel supports the orogenic topographic loads in/near the Himalaya. The Te map clearly segments the volcanic provinces of the Indian Shield, where the signatures of the Reunion, Marion, and Kerguelen hotspots are indicated by significantly low Te patterns that correlate with plume- and rift-related thermal and mechanical rejuvenation, magmatic underplating, and crustal necking. The correlations between Te variations and the occurrence of seismicity over seismically active zones reveal different causal relationships, which led to the current seismogenic zonation of the Indian Shield. (C) 2013 Elsevier B.V. All rights reserved.
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Propagation of convective systems in the meridional direction during boreal summer is responsible for active and break phases of monsoon over south Asia. This region is unique in the world in its characteristics of monsoon variability and is in close proximity of mountains like the Himalayas. Here, using an atmospheric general circulation model, we try to understand the role of orography in determining spatial and temporal scales of these convective systems. Absence of orography (noGlOrog) decreased the simulated seasonal mean precipitation over India by 23 % due to delay in onset by about a month vis-a-vis the full-mountain case. In noGlOrog, poleward propagations were absent during the delayed period prior to onset. Post-onset, both simulations had similar patterns of poleward propagations. The spatial and temporal scales of propagating clouds bands were determined using wavelet analysis. These scales were found to be different in full-mountain and no-mountain experiments in June-July. However, after the onset of monsoon in noGlOrog, these scales become similar to that with orography. Simulations with two different sets of convection schemes confirmed this result. Further analysis shows that the absence (presence) of meridional propagations during early (late) phase of summer monsoon in noGlOrog was associated with weaker (stronger) vertical shear of zonal wind over south Asia. Our study shows that orography plays a major role in determining the time of onset over the Indian region. However, after onset, basic characteristics of propagating convective systems and therefore the monthly precipitation over India, are less sensitive to the presence of orography and are modulated by moist convective processes.
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This study reports characteristics of inertia-gravity waves (IGWs) in the atmospheric boundary layer during the passage of Tropical Cylone-03B, using the Doppler Sound Detection and Ranging (SODAR) observations at the Indian tropical station of Gadanki (13.45 degrees N, 79.2 degrees E; near the east coast of India). Wavelet analysis of horizontal winds indicates significant wave motion (60h) near the characteristic inertial period. The hodograph analysis of the filtered winds shows an anti-cyclonic turning of horizontal wind with height and time, indicating the presence of IGW. This study finds important implications in boundary layer dynamics during the passage of tropical cyclones.
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The effects of evaporation and the presence of agglomerating nanoparticles on the oscillation characteristics of pendant droplets are studied experimentally using ethanol and aqueous nanoalumina suspension, respectively. Axisymmetric oscillations induced by a round air jet are considered. Wavelet transform of the time evolution of the 2nd modal coefficient revealed that while a continuous increase in the natural frequency of the droplet occurs with time due to the diameter regression induced by vaporization in the case of ethanol droplet, no such change in resonant frequency occurs in the case of the agglomerating droplet. However, a gradual reduction in the oscillation amplitude ensues as the agglomeration becomes dominant. (C) 2014 Elsevier Ltd. All rights reserved.
Resumo:
For obtaining dynamic response of structure to high frequency shock excitation spectral elements have several advantages over conventional methods. At higher frequencies transverse shear and rotary inertia have a predominant role. These are represented by the First order Shear Deformation Theory (FSDT). But not much work is reported on spectral elements with FSDT. This work presents a new spectral element based on the FSDT/Mindlin Plate Theory which is essential for wave propagation analysis of sandwich plates. Multi-transformation method is used to solve the coupled partial differential equations, i.e., Laplace transforms for temporal approximation and wavelet transforms for spatial approximation. The formulation takes into account the axial-flexure and shear coupling. The ability of the element to represent different modes of wave motion is demonstrated. Impact on the derived wave motion characteristics in the absence of the developed spectral element is discussed. The transient response using the formulated element is validated by the results obtained using Finite Element Method (FEM) which needs significant computational effort. Experimental results are provided which confirms the need to having the developed spectral element for the high frequency response of structures. (C) 2015 Elsevier Ltd. All rights reserved.
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This paper deals with processing the EEG signals obtained from 16 spatially arranged electrodes to measure coupling or synchrony between the frontal, parietal, occipital and temporal lobes of the cerebrum under the eyes open and eyes closed conditions. This synchrony was measured using magnitude squared coherence, Short Time Fourier Transform and wavelet based coherences. We found a pattern in the time-frequency coherence as we moved from the nasion to the inion of the subject's head. The coherence pattern obtained from the wavelet approach was found to be far more capable of picking up peaks in coherence with respect to frequency when compared to the regular Fourier based coherence. We detected high synchrony between frontal polar electrodes that is missing in coherence plots between other electrode pairs. The study has potential applications in healthcare.
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The effect of multiplicative noise on a signal when compared with that of additive noise is very large. In this paper, we address the problem of suppressing multiplicative noise in one-dimensional signals. To deal with signals that are corrupted with multiplicative noise, we propose a denoising algorithm based on minimization of an unbiased estimator (MURE) of meansquare error (MSE). We derive an expression for an unbiased estimate of the MSE. The proposed denoising is carried out in wavelet domain (soft thresholding) by considering time-domain MURE. The parameters of thresholding function are obtained by minimizing the unbiased estimator MURE. We show that the parameters for optimal MURE are very close to the optimal parameters considering the oracle MSE. Experiments show that the SNR improvement for the proposed denoising algorithm is competitive with a state-of-the-art method.
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We propose optimal bilateral filtering techniques for Gaussian noise suppression in images. To achieve maximum denoising performance via optimal filter parameter selection, we adopt Stein's unbiased risk estimate (SURE)-an unbiased estimate of the mean-squared error (MSE). Unlike MSE, SURE is independent of the ground truth and can be used in practical scenarios where the ground truth is unavailable. In our recent work, we derived SURE expressions in the context of the bilateral filter and proposed SURE-optimal bilateral filter (SOBF). We selected the optimal parameters of SOBF using the SURE criterion. To further improve the denoising performance of SOBF, we propose variants of SOBF, namely, SURE-optimal multiresolution bilateral filter (SMBF), which involves optimal bilateral filtering in a wavelet framework, and SURE-optimal patch-based bilateral filter (SPBF), where the bilateral filter parameters are optimized on small image patches. Using SURE guarantees automated parameter selection. The multiresolution and localized denoising in SMBF and SPBF, respectively, yield superior denoising performance when compared with the globally optimal SOBF. Experimental validations and comparisons show that the proposed denoisers perform on par with some state-of-the-art denoising techniques. (C) 2015 SPIE and IS&T
Resumo:
Selection of relevant features is an open problem in Brain-computer interfacing (BCI) research. Sometimes, features extracted from brain signals are high dimensional which in turn affects the accuracy of the classifier. Selection of the most relevant features improves the performance of the classifier and reduces the computational cost of the system. In this study, we have used a combination of Bacterial Foraging Optimization and Learning Automata to determine the best subset of features from a given motor imagery electroencephalography (EEG) based BCI dataset. Here, we have employed Discrete Wavelet Transform to obtain a high dimensional feature set and classified it by Distance Likelihood Ratio Test. Our proposed feature selector produced an accuracy of 80.291% in 216 seconds.