2D Log-Gabor Wavelet Based Action Recognition
NASA Astrophysics Data System (ADS)
Li, Ning; Xu, De
The frequency response of log-Gabor function matches well the frequency response of primate visual neurons. In this letter, motion-salient regions are extracted based on the 2D log-Gabor wavelet transform of the spatio-temporal form of actions. A supervised classification technique is then used to classify the actions. The proposed method is robust to the irregular segmentation of actors. Moreover, the 2D log-Gabor wavelet permits more compact representation of actions than the recent neurobiological models using Gabor wavelet.
Applications of a fast, continuous wavelet transform
Dress, W.B.
1997-02-01
A fast, continuous, wavelet transform, based on Shannon`s sampling theorem in frequency space, has been developed for use with continuous mother wavelets and sampled data sets. The method differs from the usual discrete-wavelet approach and the continuous-wavelet transform in that, here, the wavelet is sampled in the frequency domain. Since Shannon`s sampling theorem lets us view the Fourier transform of the data set as a continuous function in frequency space, the continuous nature of the functions is kept up to the point of sampling the scale-translation lattice, so the scale-translation grid used to represent the wavelet transform is independent of the time- domain sampling of the signal under analysis. Computational cost and nonorthogonality aside, the inherent flexibility and shift invariance of the frequency-space wavelets has advantages. The method has been applied to forensic audio reconstruction speaker recognition/identification, and the detection of micromotions of heavy vehicles associated with ballistocardiac impulses originating from occupants` heart beats. Audio reconstruction is aided by selection of desired regions in the 2-D representation of the magnitude of the transformed signal. The inverse transform is applied to ridges and selected regions to reconstruct areas of interest, unencumbered by noise interference lying outside these regions. To separate micromotions imparted to a mass-spring system (e.g., a vehicle) by an occupants beating heart from gross mechanical motions due to wind and traffic vibrations, a continuous frequency-space wavelet, modeled on the frequency content of a canonical ballistocardiogram, was used to analyze time series taken from geophone measurements of vehicle micromotions. By using a family of mother wavelets, such as a set of Gaussian derivatives of various orders, features such as the glottal closing rate and word and phrase segmentation may be extracted from voice data.
The Wavelet Element Method. Part 2; Realization and Additional Features in 2D and 3D
NASA Technical Reports Server (NTRS)
Canuto, Claudio; Tabacco, Anita; Urban, Karsten
1998-01-01
The Wavelet Element Method (WEM) provides a construction of multiresolution systems and biorthogonal wavelets on fairly general domains. These are split into subdomains that are mapped to a single reference hypercube. Tensor products of scaling functions and wavelets defined on the unit interval are used on the reference domain. By introducing appropriate matching conditions across the interelement boundaries, a globally continuous biorthogonal wavelet basis on the general domain is obtained. This construction does not uniquely define the basis functions but rather leaves some freedom for fulfilling additional features. In this paper we detail the general construction principle of the WEM to the 1D, 2D and 3D cases. We address additional features such as symmetry, vanishing moments and minimal support of the wavelet functions in each particular dimension. The construction is illustrated by using biorthogonal spline wavelets on the interval.
Applications of a fast continuous wavelet transform
NASA Astrophysics Data System (ADS)
Dress, William B.
1997-04-01
A fast, continuous, wavelet transform, justified by appealing to Shannon's sampling theorem in frequency space, has been developed for use with continuous mother wavelets and sampled data sets. The method differs from the usual discrete-wavelet approach and from the standard treatment of the continuous-wavelet transform in that, here, the wavelet is sampled in the frequency domain. Since Shannon's sampling theorem lets us view the Fourier transform of the data set as representing the continuous function in frequency space, the continuous nature of the functions is kept up to the point of sampling the scale-translation lattice, so the scale-translation grid used to represent the wavelet transform is independent of the time-domain sampling of the signal under analysis. Although more computationally costly and not represented by an orthogonal basis, the inherent flexibility and shift invariance of the frequency-space wavelets are advantageous for certain applications. The method has been applied to forensic audio reconstruction, speaker recognition/identification, and the detection of micromotions of heavy vehicles associated with ballistocardiac impulses originating from occupants' heart beats. Audio reconstruction is aided by selection of desired regions in the 2D representation of the magnitude of the transformed signals. The inverse transform is applied to ridges and selected regions to reconstruct areas of interest, unencumbered by noise interference lying outside these regions. To separate micromotions imparted to a mass- spring system by an occupant's beating heart from gross mechanical motions due to wind and traffic vibrations, a continuous frequency-space wavelet, modeled on the frequency content of a canonical ballistocardiogram, was used to analyze time series taken from geophone measurements of vehicle micromotions. By using a family of mother wavelets, such as a set of Gaussian derivatives of various orders, different features may be extracted from voice
Wavelet transforms with discrete-time continuous-dilation wavelets
NASA Astrophysics Data System (ADS)
Zhao, Wei; Rao, Raghuveer M.
1999-03-01
Wavelet constructions and transforms have been confined principally to the continuous-time domain. Even the discrete wavelet transform implemented through multirate filter banks is based on continuous-time wavelet functions that provide orthogonal or biorthogonal decompositions. This paper provides a novel wavelet transform construction based on the definition of discrete-time wavelets that can undergo continuous parameter dilations. The result is a transformation that has the advantage of discrete-time or digital implementation while circumventing the problem of inadequate scaling resolution seen with conventional dyadic or M-channel constructions. Examples of constructing such wavelets are presented.
Continuous wavelet analysis of coherent structures
NASA Technical Reports Server (NTRS)
Farge, M.; Guezennec, Y.; Ho, C. M.; Meneveau, C.
1990-01-01
We perform an analysis of planar cuts through three dimensional turbulent fields (planar channel flow and mixing layer) using the 2D continuous wavelet transform. We propose two new diagnostics: (1) a measure of intermittency I(r, vector x), which is the ratio of local energy and average energy at a given scale r; and (2) a local Reynolds number, defined on the local velocity contribution at a given scale, computed from the wavelet transform of the three velocity components, the scale of the transform, and molecular viscosity; this gives a representation of the local non-linearity of the flow viewed in both space and scale. We find, for the analyzed flows, strong small-scale intermittency located in the ejection regions for the channel flow and in the vortex core of the mixing layer.
Aircraft target identification based on 2D ISAR images using multiresolution analysis wavelet
NASA Astrophysics Data System (ADS)
Fu, Qiang; Xiao, Huaitie; Hu, Xiangjiang
2001-09-01
The formation of 2D ISAR images for radar target identification hold much promise for additional distinguish- ability between targets. Since an image contains important information is a wide range of scales, and this information is often independent from one scale to another, wavelet analysis provides a method of identifying the spatial frequency content of an image and the local regions within the image where those spatial frequencies exist. In this paper, a multiresolution analysis wavelet method based on 2D ISAR images was proposed for use in aircraft radar target identification under the wide band high range resolution radar background. The proposed method was performed in three steps; first, radar backscatter signals were processed in the form of 2D ISAR images, then, Mallat's wavelet algorithm was used in the decomposition of images, finally, a three layer perceptron neural net was used as classifier. The result of experiments demonstrated that the feasibility of using multiresolution analysis wavelet for target identification.
A 2D wavelet-based spectral finite element method for elastic wave propagation
NASA Astrophysics Data System (ADS)
Pahlavan, L.; Kassapoglou, C.; Suiker, A. S. J.; Gürdal, Z.
2012-10-01
A wavelet-based spectral finite element method (WSFEM) is presented that may be used for an accurate and efficient analysis of elastic wave propagation in two-dimensional (2D) structures. The approach is characterised by a temporal transformation of the governing equations to the wavelet domain using a wavelet-Galerkin approach, and subsequently performing the spatial discretisation in the wavelet domain with the finite element method (FEM). The final solution is obtained by transforming the nodal displacements computed in the wavelet domain back to the time domain. The method straightforwardly eliminates artificial temporal edge effects resulting from the discrete wavelet transform and allows for the modelling of structures with arbitrary geometries and boundary conditions. The accuracy and applicability of the method is demonstrated through (i) the analysis of a benchmark problem on axial and flexural waves (Lamb waves) propagating in an isotropic layer, and (ii) the study of a plate subjected to impact loading. The wave propagation response for the impact problem is compared to the result computed with standard FEM equipped with a direct time-integration scheme. The effect of anisotropy on the response is demonstrated by comparing the numerical result for an isotropic plate to that of an orthotropic plate, and to that of a plate made of two dissimilar materials, with and without a cut-out at one of the plate corners. The decoupling of the time-discretised equations in the wavelet domain makes the method inherently suitable for parallel computation, and thus an appealing candidate for efficiently studying high-frequency wave propagation in engineering structures with a large number of degrees of freedom.
Comparison of 2D and 3D wavelet features for TLE lateralization
NASA Astrophysics Data System (ADS)
Jafari-Khouzani, Kourosh; Soltanian-Zadeh, Hamid; Elisevich, Kost; Patel, Suresh
2004-04-01
Intensity and volume features of the hippocampus from MR images of the brain are known to be useful in detecting the abnormality and consequently candidacy of the hippocampus for temporal lobe epilepsy surgery. However, currently, intracranial EEG exams are required to determine the abnormal hippocampus. These exams are lengthy, painful and costly. The aim of this study is to evaluate texture characteristics of the hippocampi from MR images to help physicians determine the candidate hippocampus for surgery. We studied the MR images of 20 epileptic patients. Intracranial EEG results as well as surgery outcome were used as gold standard. The hippocampi were manually segmented by an expert from T1-weighted MR images. Then the segmented regions were mapped on the corresponding FLAIR images for texture analysis. We calculate the average energy features from 2D wavelet transform of each slice of hippocampus as well as the energy features produced by 3D wavelet transform of the whole hippocampus volume. The 2D wavelet transform is calculated both from the original slices as well as from the slices perpendicular to the principal axis of the hippocampus. In order to calculate the 3D wavelet transform we first rotate each hippocampus to fit it in a rectangular prism and then fill the empty area by extrapolating the intensity values. We combine the resulting features with volume feature and compare their ability to distinguish between normal and abnormal hippocampi using linear classifier and fuzzy c-means clustering algorithm. Experimental results show that the texture features can correctly classify the hippocampi.
A wavelet relational fuzzy C-means algorithm for 2D gel image segmentation.
Rashwan, Shaheera; Faheem, Mohamed Talaat; Sarhan, Amany; Youssef, Bayumy A B
2013-01-01
One of the most famous algorithms that appeared in the area of image segmentation is the Fuzzy C-Means (FCM) algorithm. This algorithm has been used in many applications such as data analysis, pattern recognition, and image segmentation. It has the advantages of producing high quality segmentation compared to the other available algorithms. Many modifications have been made to the algorithm to improve its segmentation quality. The proposed segmentation algorithm in this paper is based on the Fuzzy C-Means algorithm adding the relational fuzzy notion and the wavelet transform to it so as to enhance its performance especially in the area of 2D gel images. Both proposed modifications aim to minimize the oversegmentation error incurred by previous algorithms. The experimental results of comparing both the Fuzzy C-Means (FCM) and the Wavelet Fuzzy C-Means (WFCM) to the proposed algorithm on real 2D gel images acquired from human leukemias, HL-60 cell lines, and fetal alcohol syndrome (FAS) demonstrate the improvement achieved by the proposed algorithm in overcoming the segmentation error. In addition, we investigate the effect of denoising on the three algorithms. This investigation proves that denoising the 2D gel image before segmentation can improve (in most of the cases) the quality of the segmentation.
Laboratory Experiments On Continually Forced 2d Turbulence
NASA Astrophysics Data System (ADS)
Wells, M. G.; Clercx, H. J. H.; Van Heijst, G. J. F.
There has been much recent interest in the advection of tracers by 2D turbulence in geophysical flows. While there is a large body of literature on decaying 2D turbulence or forced 2D turbulence in unbounded domains, there have been very few studies of forced turbulence in bounded domains. In this study we present new experimental results from a continuously forced quasi 2D turbulent field. The experiments are performed in a square Perspex tank filled with water. The flow is made quasi 2D by a steady background rotation. The rotation rate of the tank has a small (<8 %) sinusoidal perturbation which leads to the periodic formation of eddies in the corners of the tank. When the oscillation period of the perturbation is greater than an eddy roll-up time-scale, dipole structures are observed to form. The dipoles can migrate away from the walls, and the interior of the tank is continually filled with vortexs. From experimental visualizations the length scale of the vortexs appears to be largely controlled by the initial formation mechanism and large scale structures are not observed to form at large times. Thus the experiments provide a simple way of cre- ating a continuously forced 2D turbulent field. The resulting structures are in contrast with most previous laboratory experiments on 2D turbulence which have investigated decaying turbulence and have observed the formations of large scale structure. In these experiments, decaying turbulence had been produced by a variety of methods such as the decaying turbulence in the wake of a comb of rods (Massen et al 1999), organiza- tion of vortices in thin conducting liquids (Cardoso et al 1994) or in rotating systems where there are sudden changes in angular rotation rate (Konijnenberg et al 1998). Results of dye visualizations, particle tracking experiments and a direct numerical simulation will be presented and discussed in terms of their oceanographic application. Bibliography Cardoso,O. Marteau, D. &Tabeling, P
An Automatic 3D Facial Landmarking Algorithm Using 2D Gabor Wavelets.
de Jong, Markus A; Wollstein, Andreas; Ruff, Clifford; Dunaway, David; Hysi, Pirro; Spector, Tim; Fan Liu; Niessen, Wiro; Koudstaal, Maarten J; Kayser, Manfred; Wolvius, Eppo B; Bohringer, Stefan
2016-02-01
In this paper, we present a novel approach to automatic 3D facial landmarking using 2D Gabor wavelets. Our algorithm considers the face to be a surface and uses map projections to derive 2D features from raw data. Extracted features include texture, relief map, and transformations thereof. We extend an established 2D landmarking method for simultaneous evaluation of these data. The method is validated by performing landmarking experiments on two data sets using 21 landmarks and compared with an active shape model implementation. On average, landmarking error for our method was 1.9 mm, whereas the active shape model resulted in an average landmarking error of 2.3 mm. A second study investigating facial shape heritability in related individuals concludes that automatic landmarking is on par with manual landmarking for some landmarks. Our algorithm can be trained in 30 min to automatically landmark 3D facial data sets of any size, and allows for fast and robust landmarking of 3D faces.
A new stationary gridline artifact suppression method based on the 2D discrete wavelet transform
Tang, Hui; Tong, Dan; Bao, Xudong; Dillenseger, Jean-Louis
2015-01-01
Purpose In digital X-ray radiography, an anti-scatter grid is inserted between the patient and the image receptor to reduce scattered radiation. If the anti-scatter grid is used in a stationary way, gridline artifacts will appear in the final image. In most of the gridline removal image processing methods, the useful information with spatial frequencies close to that of the gridline is usually lost or degraded. In this study, a new stationary gridline suppression method is designed to preserve more of the useful information. Methods The method is as follows. The input image is first recursively decomposed into several smaller sub-images using a multi-scale 2D discrete wavelet transform (DWT). The decomposition process stops when the gridline signal is found to be greater than a threshold in one or several of these sub-images using a gridline detection module. An automatic Gaussian band-stop filter is then applied to the detected sub-images to remove the gridline signal. Finally, the restored image is achieved using the corresponding 2D inverse discrete wavelet transform (IDWT). Results The processed images show that the proposed method can remove the gridline signal efficiently while maintaining the image details. The spectra of a 1-dimensional Fourier transform of the processed images demonstrate that, compared with some existing gridline removal methods, the proposed method has better information preservation after the removal of the gridline artifacts. Additionally, the performance speed is relatively high. Conclusions The experimental results demonstrate the efficiency of the proposed method. Compared with some existing gridline removal methods, the proposed method can preserve more information within an acceptable execution time. PMID:25832061
A new stationary gridline artifact suppression method based on the 2D discrete wavelet transform
Tang, Hui; Tong, Dan; Dong Bao, Xu; Dillenseger, Jean-Louis
2015-04-15
Purpose: In digital x-ray radiography, an antiscatter grid is inserted between the patient and the image receptor to reduce scattered radiation. If the antiscatter grid is used in a stationary way, gridline artifacts will appear in the final image. In most of the gridline removal image processing methods, the useful information with spatial frequencies close to that of the gridline is usually lost or degraded. In this study, a new stationary gridline suppression method is designed to preserve more of the useful information. Methods: The method is as follows. The input image is first recursively decomposed into several smaller subimages using a multiscale 2D discrete wavelet transform. The decomposition process stops when the gridline signal is found to be greater than a threshold in one or several of these subimages using a gridline detection module. An automatic Gaussian band-stop filter is then applied to the detected subimages to remove the gridline signal. Finally, the restored image is achieved using the corresponding 2D inverse discrete wavelet transform. Results: The processed images show that the proposed method can remove the gridline signal efficiently while maintaining the image details. The spectra of a 1D Fourier transform of the processed images demonstrate that, compared with some existing gridline removal methods, the proposed method has better information preservation after the removal of the gridline artifacts. Additionally, the performance speed is relatively high. Conclusions: The experimental results demonstrate the efficiency of the proposed method. Compared with some existing gridline removal methods, the proposed method can preserve more information within an acceptable execution time.
NASA Astrophysics Data System (ADS)
Sato, Haruo; Fehler, Michael C.
2016-10-01
The envelope broadening and the peak delay of the S-wavelet of a small earthquake with increasing travel distance are results of scattering by random velocity inhomogeneities in the earth medium. As a simple mathematical model, Sato proposed a new stochastic synthesis of the scalar wavelet envelope in 3-D von Kármán type random media when the centre wavenumber of the wavelet is in the power-law spectral range of the random velocity fluctuation. The essential idea is to split the random medium spectrum into two components using the centre wavenumber as a reference: the long-scale (low-wavenumber spectral) component produces the peak delay and the envelope broadening by multiple scattering around the forward direction; the short-scale (high-wavenumber spectral) component attenuates wave amplitude by wide angle scattering. The former is calculated by the Markov approximation based on the parabolic approximation and the latter is calculated by the Born approximation. Here, we extend the theory for the envelope synthesis of a wavelet in 2-D random media, which makes it easy to compare with finite difference (FD) simulation results. The synthetic wavelet envelope is analytically written by using the random medium parameters in the angular frequency domain. For the case that the power spectral density function of the random velocity fluctuation has a steep roll-off at large wavenumbers, the envelope broadening is small and frequency independent, and scattering attenuation is weak. For the case of a small roll-off, however, the envelope broadening is large and increases with frequency, and the scattering attenuation is strong and increases with frequency. As a preliminary study, we compare synthetic wavelet envelopes with the average of FD simulation wavelet envelopes in 50 synthesized random media, which are characterized by the RMS fractional velocity fluctuation ε = 0.05, correlation scale a = 5 km and the background wave velocity V0 = 4 km s-1. We use the radiation
Blocking geophysical borehole log data using the continuous wavelet transform
NASA Astrophysics Data System (ADS)
Cooper, Gordon R. J.; Cowan, Duncan R.
2009-06-01
The interpretation of geophysical log data is frequently difficult due to the noisy downhole environment. Blocking algorithms attempt to smooth the log data while leaving the boundaries between different geological units sharp. This paper introduces a method for the determination of the boundaries based on the zero contour of the continuous wavelet transform (CWT) of the data. The amount of blocking can be controlled by the choice of the scale of the wavelet used. The method is compared with results from the median filter and with discrete wavelet transform (DWT) blocking methods, and is here applied to log data from Australia. The application of the new CWT method overcomes the rounding and shifting of boundaries inherent in median filtering, and provides greater flexibility by overcoming the power of two limitations in the DWT log blocking.
NASA Astrophysics Data System (ADS)
Wang, Chun-Hsiung; Hsu, Kuan-Yu; Lee, Chih-Kung
2016-03-01
A real-time three-dimensional surface profile metrology system was implemented by integrating Fourier Transform (FT) based algorithms to convert interference intensity fringes to wrapped frequency phase maps and then to unwrapped phase maps. The revival of this field can find its roots in recognizing the development of high-resolution high-speed CCD/CMOS over the years. Two-dimensional Continuous Wavelet Transform (2D-CWT), which possesses the ability to construct daughter wavelets of good time and frequency localization according to different fringes conditions from a characteristic mother wavelet, was implemented with an attempt to reduce redundant fitting process of ordinary Short Time Fourier Transform (STFT), also known as Windowed Fourier Transform (WFT), and therefore to accelerate the FT-related algorithms needed. Implemented with the efficient wavelet construction process by using 2D-CWT, Electronic Speckle Pattern Interferometer (ESPI) was adopted to take advantage of this new process. Different from using several phase shifting steps before to solve the direction ambiguity, which takes time to capture multiple intensity maps during measurement, the phase maps needed were retrieved from a single frame interference fringes. It is to be noted that this one-image interference fringe was captured by having a pre-introduced spatial carrier frequency embedded within the experimental setup so as to remove the directional ambiguity. 2D-CWT dealing with different signal-to-noise ratios was also designed by selecting wavelet parameters properly, which is expected to achieve higher accuracy and faster processing speed. For phase unwrapping, Poisson's equation with Neumann boundary condition was solved by using FFT. The benefit of using 2D-CWTs with different wavelets as compared to WFT was demonstrated experimentally.
Mathematics of adaptive wavelet transforms: relating continuous with discrete transforms
NASA Astrophysics Data System (ADS)
Szu, Harold H.; Telfer, Brian A.
1994-07-01
We prove several theorems and construct explicitly the bridge between the continuous and discrete adaptive wavelet transform (AWT). The computational efficiency of the AWT is a result of its compact support closely matching linearly the signal's time-frequency characteristics, and is also a result of a larger redundancy factor of the superposition-mother s(x) (super-mother), created adaptively by a linear superposition of other admissible mother wavelets. The super-mother always forms a complete basis, but is usually associated with a higher redundancy number than its constituent complete orthonormal bases. The robustness of super-mother suffers less noise contamination (since noise is everywhere, and a redundant sampling by bandpassings can suppress the noise and enhance the signal). Since the continuous super-mother has been created off-line by AWT (using least-mean- squares neural nets), we wish to accomplish fast AWT on line. Thus, we formulate AWT in discrete high-pass (H) and low-pass (L) filter bank coefficients via the quadrature mirror filter, (QMF), a digital subband lossless coding. A linear combination of two special cases of complete biorthogonal normalized (Cbi-ON) QMF [L(z), H(z), L+(z), H+(z)], called (alpha) -bank and (Beta) -bank, becomes a hybrid a(alpha) + b(Beta) -bank (for any real positive constants a and b) that is still admissible, meaning Cbi-ON and lossless. Finally, the power of AWT is the implementation by means of wavelet chips and neurochips, in which each node is a daughter wavelet similar to a radial basis function using dyadic affine scaling.
Adaptive 2-D wavelet transform based on the lifting scheme with preserved vanishing moments.
Vrankic, Miroslav; Sersic, Damir; Sucic, Victor
2010-08-01
In this paper, we propose novel adaptive wavelet filter bank structures based on the lifting scheme. The filter banks are nonseparable, based on quincunx sampling, with their properties being pixel-wise adapted according to the local image features. Despite being adaptive, the filter banks retain a desirable number of primal and dual vanishing moments. The adaptation is introduced in the predict stage of the filter bank with an adaptation region chosen independently for each pixel, based on the intersection of confidence intervals (ICI) rule. The image denoising results are presented for both synthetic and real-world images. It is shown that the obtained wavelet decompositions perform well, especially for synthetic images that contain periodic patterns, for which the proposed method outperforms the state of the art in image denoising.
Wavelet neural network employment for continuous orbit construction
NASA Astrophysics Data System (ADS)
Pavlovčič Prešeren, Polona; Stopar, Bojan
2010-05-01
The scope of this paper is to present a comparison between a novel wavelet neural network (WNN) approximation and currently used polynomial and trigonometric interpolations for continuous GNSS (Global Navigation Satellite System) orbit construction. In the first part we propose the wavelet network construction and algorithms for regression estimation. Since the algorithms for non-parametric regression estimation with wavelet networks overcome backpropagation limitations of small input data domain training, this procedure is employed for the GNSS satellite position computations from precise ephemerides. Finally, the performance of WNN and polynomial and trigonometric interpolations is examined and most efficient WNN algorithm is presented. Simulation studies proved that WNN function overcomes traditional interpolation deficiency in better performance near the end of the interval. The method is linked to a single function determination for the entire interval and overcomes the obstacle of several discrete function establishment, which was the basis for the interpolation methods. Furthermore it is shown that WNN approximation offers better solution in storage of data used for GNSS orbit re-construction, but retains the computation efficiency and generalization ability in any function domain.
Ning, Bende; Qu, Xiaobo; Guo, Di; Hu, Changwei; Chen, Zhong
2013-11-01
Reducing scanning time is significantly important for MRI. Compressed sensing has shown promising results by undersampling the k-space data to speed up imaging. Sparsity of an image plays an important role in compressed sensing MRI to reduce the image artifacts. Recently, the method of patch-based directional wavelets (PBDW) which trains geometric directions from undersampled data has been proposed. It has better performance in preserving image edges than conventional sparsifying transforms. However, obvious artifacts are presented in the smooth region when the data are highly undersampled. In addition, the original PBDW-based method does not hold obvious improvement for radial and fully 2D random sampling patterns. In this paper, the PBDW-based MRI reconstruction is improved from two aspects: 1) An efficient non-convex minimization algorithm is modified to enhance image quality; 2) PBDW are extended into shift-invariant discrete wavelet domain to enhance the ability of transform on sparsifying piecewise smooth image features. Numerical simulation results on vivo magnetic resonance images demonstrate that the proposed method outperforms the original PBDW in terms of removing artifacts and preserving edges.
On applying continuous wavelet transform in wheeze analysis.
Taplidou, Styliani A; Hadjileontiadis, Leontios J; Kitsas, Ilias K; Panoulas, Konstantinos I; Penzel, Thomas; Gross, Volker; Panas, Stavros M
2004-01-01
The identification of continuous abnormal lung sounds, like wheezes, in the total breathing cycle is of great importance in the diagnosis of obstructive airways pathologies. To this vein, the current work introduces an efficient method for the detection of wheezes, based on the time-scale representation of breath sound recordings. The employed Continuous Wavelet Transform is proven to be a valuable tool at this direction, when combined with scale-dependent thresholding. Analysis of lung sound recordings from 'wheezing' patients shows promising performance in the detection and extraction of wheezes from the background noise and reveals its potentiality for data-volume reduction in long-term wheezing screening, such as in sleep-laboratories.
NASA Astrophysics Data System (ADS)
Tang, Xiangyang; Ning, Ruola; Yu, Rongfeng; Conover, David L.
1999-05-01
The application of the newly developed flat panel x-ray imaging detector in cone beam volume CT has attracted increasing interest recently. Due to an imperfect solid state array manufacturing process, however, defective elements, gain non-uniformity and offset image unavoidably exist in all kinds of flat panel x-ray imaging detectors, which will cause severe streak and ring artifacts in a cone beam reconstruction image and severely degrade image quality. A calibration technique, in which the artifacts resulting from the defective elements, gain non-uniformity and offset image can be reduced significantly, is presented in this paper. The detection of defective elements is distinctively based upon two-dimensional (2D) wavelet analysis. Because of its inherent localizability in recognizing singularities or discontinuities, wavelet analysis possesses the capability of detecting defective elements over a rather large x-ray exposure range, e.g., 20% to approximately 60% of the dynamic range of the detector used. Three-dimensional (3D) images of a low-contrast CT phantom have been reconstructed from projection images acquired by a flat panel x-ray imaging detector with and without calibration process applied. The artifacts caused individually by defective elements, gain non-uniformity and offset image have been separated and investigated in detail, and the correlation with each other have also been exposed explicitly. The investigation is enforced by quantitative analysis of the signal to noise ratio (SNR) and the image uniformity of the cone beam reconstruction image. It has been demonstrated that the ring and streak artifacts resulting from the imperfect performance of a flat panel x-ray imaging detector can be reduced dramatically, and then the image qualities of a cone beam reconstruction image, such as contrast resolution and image uniformity are improved significantly. Furthermore, with little modification, the calibration technique presented here is also applicable
Applications of continuous and orthogonal wavelet transforms to MHD and plasma turbulence
NASA Astrophysics Data System (ADS)
Farge, Marie; Schneider, Kai
2016-10-01
Wavelet analysis and compression tools are presented and different applications to study MHD and plasma turbulence are illustrated. We use the continuous and the orthogonal wavelet transform to develop several statistical diagnostics based on the wavelet coefficients. We show how to extract coherent structures out of fully developed turbulent flows using wavelet-based denoising and describe multiscale numerical simulation schemes using wavelets. Several examples for analyzing, compressing and computing one, two and three dimensional turbulent MHD or plasma flows are presented. Details can be found in M. Farge and K. Schneider. Wavelet transforms and their applications to MHD and plasma turbulence: A review. Support by the French Research Federation for Fusion Studies within the framework of the European Fusion Development Agreement (EFDA) is thankfully acknowledged.
Continuous wavelet transform analysis of acceleration signals measured from a wave buoy.
Chuang, Laurence Zsu-Hsin; Wu, Li-Chung; Wang, Jong-Hao
2013-08-19
Accelerometers, which can be installed inside a floating platform on the sea, are among the most commonly used sensors for operational ocean wave measurements. To examine the non-stationary features of ocean waves, this study was conducted to derive a wavelet spectrum of ocean waves and to synthesize sea surface elevations from vertical acceleration signals of a wave buoy through the continuous wavelet transform theory. The short-time wave features can be revealed by simultaneously examining the wavelet spectrum and the synthetic sea surface elevations. The in situ wave signals were applied to verify the practicality of the wavelet-based algorithm. We confirm that the spectral leakage and the noise at very-low-frequency bins influenced the accuracies of the estimated wavelet spectrum and the synthetic sea surface elevations. The appropriate thresholds of these two factors were explored. To study the short-time wave features from the wave records, the acceleration signals recorded from an accelerometer inside a discus wave buoy are analysed. The results from the wavelet spectrum show the evidence of short-time nonlinear wave events. Our study also reveals that more surface profiles with higher vertical asymmetry can be found from short-time nonlinear wave with stronger harmonic spectral peak. Finally, we conclude that the algorithms of continuous wavelet transform are practical for revealing the short-time wave features of the buoy acceleration signals.
2016-01-01
A novel method of extracting heart rate and oxygen saturation from a video-based biosignal is described. The method comprises a novel modular continuous wavelet transform approach which includes: performing the transform, undertaking running wavelet archetyping to enhance the pulse information, extraction of the pulse ridge time–frequency information [and thus a heart rate (HRvid) signal], creation of a wavelet ratio surface, projection of the pulse ridge onto the ratio surface to determine the ratio of ratios from which a saturation trending signal is derived, and calibrating this signal to provide an absolute saturation signal (SvidO2). The method is illustrated through its application to a video photoplethysmogram acquired during a porcine model of acute desaturation. The modular continuous wavelet transform-based approach is advocated by the author as a powerful methodology to deal with noisy, non-stationary biosignals in general. PMID:27382479
Addison, Paul S
2016-06-01
A novel method of extracting heart rate and oxygen saturation from a video-based biosignal is described. The method comprises a novel modular continuous wavelet transform approach which includes: performing the transform, undertaking running wavelet archetyping to enhance the pulse information, extraction of the pulse ridge time-frequency information [and thus a heart rate (HRvid) signal], creation of a wavelet ratio surface, projection of the pulse ridge onto the ratio surface to determine the ratio of ratios from which a saturation trending signal is derived, and calibrating this signal to provide an absolute saturation signal (SvidO2). The method is illustrated through its application to a video photoplethysmogram acquired during a porcine model of acute desaturation. The modular continuous wavelet transform-based approach is advocated by the author as a powerful methodology to deal with noisy, non-stationary biosignals in general.
Analysis of Mold Friction in a Continuous Casting Using Wavelet Entropy
NASA Astrophysics Data System (ADS)
Yong, Ma; Fangyin, Wang; Cheng, Peng; Wei, Gui; Bohan, Fang
2016-06-01
By studying mold friction (MDF), we observed that monitoring and controlling of the friction between the strand and the mold is very important for continuous casting to improve lubrication and prevent breakout. However, existing analysis technologies of MDF do not support the continuous casting very well. In addition, we found that the wavelet entropy has multiscale and statistical properties. Informed by these observations, in this article, we use wavelet entropy to judge the lubrication state between the strand and the mold. First, we demonstrate the implementation and superiority of wavelet entropy and how it helps in efficient evaluation of the lubrication state in mold. A study of wavelet entropy of MDF, which is obtained from the abnormal continuous casting production, such as level fluctuation, submerged entry nozzle broken, and breakout, has been performed to achieve relevant conclusions. The results indicate that the information of MDF in time and frequency domains could be obtained simultaneously by the application of wavelet entropy and that the wavelet entropy has a good sensibility for the study of disorder of MDF, which could further reveal the nature of MDF.
NASA Astrophysics Data System (ADS)
DeVore, Ronald A.; Lucier, Bradley J.
The subject of `wavelets' is expanding at such a tremendous rate that it is impossible to give, within these few pages, a complete introduction to all aspects of its theory. We hope, however, to allow the reader to become sufficiently acquainted with the subject to understand, in part, the enthusiasm of its proponents toward its potential application to various numerical problems. Furthermore, we hope that our exposition can guide the reader who wishes to make more serious excursions into the subject. Our viewpoint is biased by our experience in approximation theory and data compression; we warn the reader that there are other viewpoints that are either not represented here or discussed only briefly. For example, orthogonal wavelets were developed primarily in the context of signal processing, an application upon which we touch only indirectly. However, there are several good expositions (e.g. Daubechies (1990) and Rioul and Vetterli (1991)) of this application. A discussion of wavelet decompositions in the context of Littlewood-Paley theory can be found in the monograph of Frazier et al. (1991). We shall also not attempt to give a complete discussion of the history of wavelets. Historical accounts can be found in the book of Meyer (1990) and the introduction of the article of Daubechies (1990). We shall try to give sufficient historical commentary in the course of our presentation to provide some feeling for the subject's development.
NASA Astrophysics Data System (ADS)
Peresunko, A. P.; Zavadovskya, I. G.
2004-06-01
The paper deals with the studying of prognostic possibilities of determining the orientation structure of endometrial strome in the normal state and hiperplasia. The laser diagnostic of endometrial state is based on the principles of optical changes of laser radiation during its passing through the histological sample with the following investigation of its wavelet coefficients.
Nonlinear 2D arm dynamics in response to continuous and pulse-shaped force perturbations.
Happee, Riender; de Vlugt, Erwin; van Vliet, Bart
2015-01-01
Ample evidence exists regarding the nonlinearity of the neuromuscular system but linear models are widely applied to capture postural dynamics. This study quantifies the nonlinearity of human arm postural dynamics applying 2D continuous force perturbations (0.2-40 Hz) inducing three levels of hand displacement (5, 15, 45 mm RMS) followed by force-pulse perturbations inducing large hand displacements (up to 250 mm) in a position task (PT) and a relax task (RT) recording activity of eight shoulder and elbow muscles. The continuous perturbation data were used to analyze the 2D endpoint dynamics in the frequency domain and to identify reflexive and intrinsic parameters of a linear neuromuscular shoulder-elbow model. Subsequently, it was assessed to what extent the large displacements in response to force pulses could be predicted from the 'small amplitude' linear neuromuscular model. Continuous and pulse perturbation responses with varying amplitudes disclosed highly nonlinear effects. In PT, a larger continuous perturbation induced stiffening with a factor of 1.5 attributed to task adaptation evidenced by increased co-contraction and reflexive activity. This task adaptation was even more profound in the pulse responses where reflexes and displacements were strongly affected by the presence and amplitude of preceding continuous perturbations. In RT, a larger continuous perturbation resulted in yielding with a factor of 3.8 attributed to nonlinear mechanical properties as no significant reflexive activity was found. Pulse perturbations always resulted in yielding where a model fitted to the preceding 5-mm continuous perturbations predicted only 37% of the recorded peak displacements in RT and 79% in PT. This demonstrates that linear neuromuscular models, identified using continuous perturbations with small amplitudes, strongly underestimate displacements in pulse-shaped (e.g., impact) loading conditions. The data will be used to validate neuromuscular models including
Detection of pulse-like ground motions based on continues wavelet transform
NASA Astrophysics Data System (ADS)
Yaghmaei-Sabegh, Saman
2010-10-01
This paper implements a quantitative approach to detect pulse-like ground motions based on continues wavelet transform, which is able to clearly identify sudden jumps in time history of earthquake records by considering contribution of different levels of frequency. These analyses were performed on a set of time series records obtained in near-fault regions of Iran. Pulse-like ground motions frequently resulted from directivity effects in near-fault area and are of interest in the field of seismology and also earthquake engineering for seismic performance evaluation of structures. The results of this study basically help us to establish a suitable platform for selecting pulse-like records, while performance evaluation of structure in near-fault area will need to account. The period of velocity pulses as a key parameter that significantly affects structural response is simply determined by using a pseudo-period of the mother wavelets. In addition, the efficiency of different types of mother wavelets on classification performance and the features of detected pulse are investigated by applying seven different kinds of mother wavelets. The analyses indicate that the selection of most appropriate mother wavelet plays a significant role in effective extraction of ground motion features and consequently in estimation of velocity pulse period. As a result, the user should be aware of what is selected as a mother wavelet in the analysis. The comparisons given here among different mother wavelets also show the better performance of BiorSpline (bior1.3) basis from biorthognal wavelet families for the preferred purpose in this paper.
Exploration of EEG features of Alzheimer's disease using continuous wavelet transform.
Ghorbanian, Parham; Devilbiss, David M; Hess, Terry; Bernstein, Allan; Simon, Adam J; Ashrafiuon, Hashem
2015-09-01
We have developed a novel approach to elucidate several discriminating EEG features of Alzheimer's disease. The approach is based on the use of a variety of continuous wavelet transforms, pairwise statistical tests with multiple comparison correction, and several decision tree algorithms, in order to choose the most prominent EEG features from a single sensor. A pilot study was conducted to record EEG signals from Alzheimer's disease (AD) patients and healthy age-matched control (CTL) subjects using a single dry electrode device during several eyes-closed (EC) and eyes-open (EO) resting conditions. We computed the power spectrum distribution properties and wavelet and sample entropy of the wavelet coefficients time series at scale ranges approximately corresponding to the major brain frequency bands. A predictive index was developed using the results from statistical tests and decision tree algorithms to identify the most reliable significant features of the AD patients when compared to healthy controls. The three most dominant features were identified as larger absolute mean power and larger standard deviation of the wavelet scales corresponding to 4-8 Hz (θ) during EO and lower wavelet entropy of the wavelet scales corresponding to 8-12 Hz (α) during EC, respectively. The fourth reliable set of distinguishing features of AD patients was lower relative power of the wavelet scales corresponding to 12-30 Hz (β) followed by lower skewness of the wavelet scales corresponding to 2-4 Hz (upper δ), both during EO. In general, the results indicate slowing and lower complexity of EEG signal in AD patients using a very easy-to-use and convenient single dry electrode device.
NASA Astrophysics Data System (ADS)
Fayadh, Rashid A.; Malek, F.; Fadhil, Hilal A.; Dawood, Sameer A.; Abdullah, Farah Salwani
2015-05-01
In this paper, three levels of analysis and synthesis filter banks were used to create coefficients for a continuous wavelet transform (CWT) and discrete wavelet transform (DWT). The main property of these wavelet transform schemes is their ability to construct the transmitted signal across a log-normal fading channel over additive white Gaussian noise (AWGN). Wireless rake-receiver structure was chosen as a major application to reduce the inter-symbol interference (ISI) and to minimize the noise. In this work, a new scheme of rake receiver is proposed to receive indoor, multi-path components (MPCs) for ultra-wideband (UWB) wireless communication systems. Rake receivers consist of a continuous wavelet rake (CW-rake) and a discrete wavelet rake (DW-rake), and they use huge bandwidth (7.5 GHz), as reported by the Federal Communications Commission (FCC). The indoor channel models chose for analysis in this research were the non line-of-sight (LOS) channel model (CM4 from 4 to 10 meters) to show the behavior of bit error rate (BER) with respect to signal-to noise ratio (SNR). Two types of rake receiver were used in the simulation, i.e., partial-rake and selective-rake receivers with the maximal ratio combining (MRC) technique to capture the energy of the signal from the output of the rake's fingers.
Combining 2D wavelet edge highlighting and 3D thresholding for lung segmentation in thin-slice CT.
Korfiatis, P; Skiadopoulos, S; Sakellaropoulos, P; Kalogeropoulou, C; Costaridou, L
2007-12-01
The first step in lung analysis by CT is the identification of the lung border. To deal with the increased number of sections per scan in thin-slice multidetector CT, it has been crucial to develop accurate and automated lung segmentation algorithms. In this study, an automated method for lung segmentation of thin-slice CT data is presented. The method exploits the advantages of a two-dimensional wavelet edge-highlighting step in lung border delineation. Lung volume segmentation is achieved with three-dimensional (3D) grey level thresholding, using a minimum error technique. 3D thresholding, combined with the wavelet pre-processing step, successfully deals with lung border segmentation challenges, such as anterior or posterior junction lines and juxtapleural nodules. Finally, to deal with mediastinum border under-segmentation, 3D morphological closing with a spherical structural element is applied. The performance of the proposed method is quantitatively assessed on a dataset originating from the Lung Imaging Database Consortium (LIDC) by comparing automatically derived borders with the manually traced ones. Segmentation performance, averaged over left and right lung volumes, for lung volume overlap is 0.983+/-0.008, whereas for shape differentiation in terms of mean distance it is 0.770+/-0.251 mm (root mean square distance is 0.520+/-0.008 mm; maximum distance is 3.327+/-1.637 mm). The effect of the wavelet pre-processing step was assessed by comparing the proposed method with the 3D thresholding technique (applied on original volume data). This yielded statistically significant differences for all segmentation metrics (p<0.01). Results demonstrate an accurate method that could be used as a first step in computer lung analysis by CT.
Chen, Hui; Lin, Zan; Mo, Lin; Wu, Hegang; Wu, Tong; Tan, Chao
2015-01-01
Spectrum is inherently local in nature since it can be thought of as a signal being composed of various frequency components. Wavelet transform (WT) is a powerful tool that partitions a signal into components with different frequency. The property of multi-resolution enables WT a very effective and natural tool for analyzing spectrum-like signal. In this study, a continuous wavelet transform (CWT)-based variable selection procedure was proposed to search for a set of informative wavelet coefficients for constructing a near-infrared (NIR) spectral diagnosis model of cancer. The CWT provided a fine multi-resolution feature space for selecting best predictors. A measure of discriminating power (DP) was defined to evaluate the coefficients. Partial least squares-discriminant analysis (PLS-DA) was used as the classification algorithm. A NIR spectral dataset associated to cancer diagnosis was used for experiment. The optimal results obtained correspond to the wavelet of db2. It revealed that on condition of having better performance on the training set, the optimal PLS-DA model using only 40 wavelet coefficients in 10 scales achieved the same performance as the one using all the variables in the original space on the test set: an overall accuracy of 93.8%, sensitivity of 92.5% and specificity of 96.3%. It confirms that the CWT-based feature selection coupled with PLS-DA is feasible and effective for constructing models of diagnostic cancer by NIR spectroscopy.
Continuous-wavelet-transform analysis of the multifocal ERG waveform in glaucoma diagnosis.
Miguel-Jiménez, J M; Blanco, R; De-Santiago, L; Fernández, A; Rodríguez-Ascariz, J M; Barea, R; Martín-Sánchez, J L; Amo, C; Sánchez-Morla, E; Boquete, L
2015-09-01
The vast majority of multifocal electroretinogram (mfERG) signal analyses to detect glaucoma study the signals' amplitudes and latencies. The purpose of this paper is to investigate application of wavelet analysis of mfERG signals in diagnosis of glaucoma. This analysis method applies the continuous wavelet transform (CWT) to the signals, using the real Morlet wavelet. CWT coefficients resulting from the scale of maximum correlation are used as inputs to a neural network, which acts as a classifier. mfERG recordings are taken from the eyes of 47 subjects diagnosed with chronic open-angle glaucoma and from those of 24 healthy subjects. The high sensitivity in the classification (0.894) provides reliable detection of glaucomatous sectors, while the specificity achieved (0.844) reflects accurate detection of healthy sectors. The results obtained in this paper improve on the previous findings reported by the authors using the same visual stimuli and database.
Ok, Jong G; Panday, Ashwin; Lee, Taehwa; Jay Guo, L
2014-12-21
We present a versatile and simple methodology for continuous and scalable 2D micro/nano-structure fabrication via sequential 1D patterning strokes enabled by dynamic nano-inscribing (DNI) and vibrational indentation patterning (VIP) as well as a 'single-stroke' 2D patterning using a DNI tool in VIP.
NASA Astrophysics Data System (ADS)
Elbarghathi, F.; Wang, T.; Zhen, D.; Gu, F.; Ball, A.
2012-05-01
Vibration signals from a gearbox are usually very noisy which makes it difficult to find reliable symptoms of a fault in a multistage gearbox. This paper explores the use of time synchronous average (TSA) to suppress the noise and Continue Wavelet Transformation (CWT) to enhance the non-stationary nature of fault signal for more accurate fault diagnosis. The results obtained in diagnosis an incipient gear breakage show that fault diagnosis results can be improved by using an appropriate wavelet. Moreover, a new scheme based on the level of wavelet coefficient amplitudes of baseline data alone, without faulty data samples, is suggested to select an optimal wavelet.
NASA Astrophysics Data System (ADS)
Liu, Yao; Wang, Xiufeng; Lin, Jing; Zhao, Wei
2016-11-01
Motor current is an emerging and popular signal which can be used to detect machining chatter with its multiple advantages. To achieve accurate and reliable chatter detection using motor current, it is important to make clear the quantitative relationship between motor current and chatter vibration, which has not yet been studied clearly. In this study, complex continuous wavelet coherence, including cross wavelet transform and wavelet coherence, is applied to the correlation analysis of motor current and chatter vibration in grinding. Experimental results show that complex continuous wavelet coherence performs very well in demonstrating and quantifying the intense correlation between these two signals in frequency, amplitude and phase. When chatter occurs, clear correlations in frequency and amplitude in the chatter frequency band appear and the phase difference of current signal to vibration signal turns from random to stable. The phase lead of the most correlated chatter frequency is the largest. With the further development of chatter, the correlation grows up in intensity and expands to higher order chatter frequency band. The analyzing results confirm that there is a consistent correlation between motor current and vibration signals in the grinding chatter process. However, to achieve accurate and reliable chatter detection using motor current, the frequency response bandwidth of current loop of the feed drive system must be wide enough to response chatter effectively.
Mouse EEG spike detection based on the adapted continuous wavelet transform
NASA Astrophysics Data System (ADS)
Tieng, Quang M.; Kharatishvili, Irina; Chen, Min; Reutens, David C.
2016-04-01
Objective. Electroencephalography (EEG) is an important tool in the diagnosis of epilepsy. Interictal spikes on EEG are used to monitor the development of epilepsy and the effects of drug therapy. EEG recordings are generally long and the data voluminous. Thus developing a sensitive and reliable automated algorithm for analyzing EEG data is necessary. Approach. A new algorithm for detecting and classifying interictal spikes in mouse EEG recordings is proposed, based on the adapted continuous wavelet transform (CWT). The construction of the adapted mother wavelet is founded on a template obtained from a sample comprising the first few minutes of an EEG data set. Main Result. The algorithm was tested with EEG data from a mouse model of epilepsy and experimental results showed that the algorithm could distinguish EEG spikes from other transient waveforms with a high degree of sensitivity and specificity. Significance. Differing from existing approaches, the proposed approach combines wavelet denoising, to isolate transient signals, with adapted CWT-based template matching, to detect true interictal spikes. Using the adapted wavelet constructed from a predefined template, the adapted CWT is calculated on small EEG segments to fit dynamical changes in the EEG recording.
Wavelet-based method for image filtering using scale-space continuity
NASA Astrophysics Data System (ADS)
Jung, Claudio R.; Scharcanski, Jacob
2001-04-01
This paper proposes a novel technique to reduce noise while preserving edge sharpness during image filtering. This method is based on the image multiresolution decomposition by a discrete wavelet transform, given a proper wavelet basis. In the transform spaces, edges are implicitly located and preserved, at the same time that image noise is filtered out. At each resolution level, geometric continuity is used to preserve edges that are not isolated. Finally, we compare consecutive levels to preserve edges having continuity along scales. As a result, the proposed technique produces a filtered version of the original image, where homogeneous regions appear segmented by well-defined edges. Possible applications include image presegmentation and image denoising.
2D CFD Analysis of an Airfoil with Active Continuous Trailing Edge Flap
NASA Astrophysics Data System (ADS)
Jaksich, Dylan; Shen, Jinwei
2014-11-01
Efficient and quieter helicopter rotors can be achieved through on-blade control devices, such as active Continuous Trailing-Edge Flaps driven by embedded piezoelectric material. This project aims to develop a CFD simulation tool to predict the aerodynamic characteristics of an airfoil with CTEF using open source code: OpenFOAM. Airfoil meshes used by OpenFOAM are obtained with MATLAB scripts. Once created it is possible to rotate the airfoil to various angles of attack. When the airfoil is properly set up various OpenFOAM properties, such as kinematic viscosity and flow velocity, are altered to achieve the desired testing conditions. Upon completion of a simulation, the program gives the lift, drag, and moment coefficients as well as the pressure and velocity around the airfoil. The simulation is then repeated across multiple angles of attack to give full lift and drag curves. The results are then compared to previous test data and other CFD predictions. This research will lead to further work involving quasi-steady 2D simulations incorporating NASTRAN to model aeroelastic deformation and eventually to 3D aeroelastic simulations. NSF ECE Grant #1358991 supported the first author as an REU student.
NASA Astrophysics Data System (ADS)
Timoshevskiy, M. V.; Zapryagaev, I. I.; Pervunin, K. S.; Markovich, D. M.
2016-10-01
In the paper, the possibility of active control of a cavitating flow over a 2D hydrofoil that replicates a scaled-down model of high-pressure hydroturbine guide vane (GV) was tested. The flow manipulation was implemented by a continuous tangential liquid injection at different flow rates through a spanwise slot in the foil surface. In experiments, the hydrofoil was placed in the test channel at the attack angle of 9°. Different cavitation conditions were reached by varying the cavitation number and injection velocity. In order to study time dynamics and spatial patterns of partial cavities, high-speed imaging was employed. A PIV method was used to measure the mean and fluctuating velocity fields over the hydrofoil. Hydroacoustic measurements were carried out by means of a pressure transducer to identify spectral characteristics of the cavitating flow. It was found that the present control technique is able to modify the partial cavity pattern (or even totally suppress cavitation) in case of stable sheet cavitation and change the amplitude of pressure pulsations at unsteady regimes. The injection technique makes it also possible to significantly influence the spatial distributions of the mean velocity and its turbulent fluctuations over the GV section for non-cavitating flow and sheet cavitation.
[An automatic peak detection method for LIBS spectrum based on continuous wavelet transform].
Chen, Peng-Fei; Tian, Di; Qiao, Shu-Jun; Yang, Guang
2014-07-01
Spectrum peak detection in the laser-induced breakdown spectroscopy (LIBS) is an essential step, but the presence of background and noise seriously disturb the accuracy of peak position. The present paper proposed a method applied to automatic peak detection for LIBS spectrum in order to enhance the ability of overlapping peaks searching and adaptivity. We introduced the ridge peak detection method based on continuous wavelet transform to LIBS, and discussed the choice of the mother wavelet and optimized the scale factor and the shift factor. This method also improved the ridge peak detection method with a correcting ridge method. The experimental results show that compared with other peak detection methods (the direct comparison method, derivative method and ridge peak search method), our method had a significant advantage on the ability to distinguish overlapping peaks and the precision of peak detection, and could be be applied to data processing in LIBS.
Wavelet-based low-delay ECG compression algorithm for continuous ECG transmission.
Kim, Byung S; Yoo, Sun K; Lee, Moon H
2006-01-01
The delay performance of compression algorithms is particularly important when time-critical data transmission is required. In this paper, we propose a wavelet-based electrocardiogram (ECG) compression algorithm with a low delay property for instantaneous, continuous ECG transmission suitable for telecardiology applications over a wireless network. The proposed algorithm reduces the frame size as much as possible to achieve a low delay, while maintaining reconstructed signal quality. To attain both low delay and high quality, it employs waveform partitioning, adaptive frame size adjustment, wavelet compression, flexible bit allocation, and header compression. The performances of the proposed algorithm in terms of reconstructed signal quality, processing delay, and error resilience were evaluated using the Massachusetts Institute of Technology University and Beth Israel Hospital (MIT-BIH) and Creighton University Ventricular Tachyarrhythmia (CU) databases and a code division multiple access-based simulation model with mobile channel noise.
NASA Astrophysics Data System (ADS)
Gu, Junhua; Xu, Haiguang; Wang, Jingying; An, Tao; Chen, Wen
2013-08-01
We propose a continuous wavelet transform based non-parametric foreground subtraction method for the detection of redshifted 21 cm signal from the epoch of reionization. This method works based on the assumption that the foreground spectra are smooth in frequency domain, while the 21 cm signal spectrum is full of saw-tooth-like structures, thus their characteristic scales are significantly different. We can distinguish them in the wavelet coefficient space easily and perform the foreground subtraction. Compared with the traditional spectral fitting based method, our method is more tolerant to complex foregrounds. Furthermore, we also find that when the instrument has uncorrected response error, our method can also work significantly better than the spectral fitting based method. Our method can obtain similar results with the Wp smoothing method, which is also a non-parametric method, but our method consumes much less computing time.
Heterogeneities Analysis Using the Generalized Fractal Dimension and Continuous Wavelet Transform
NASA Astrophysics Data System (ADS)
Ouadfeul, S.; Aliouane, L.; Boudella, A.
2012-04-01
The main goal of this work is analyze heterogeneities from well-logs data using the wavelet transform modulus maxima lines (WTMM). Firstly, the continuous wavelet transform (CWT) with sliding window is calculated. The next step consists to calculate the maxima of the modulus of the CWT and estimate the spectrum of exponents. The three generalized fractal dimensions D0, D1 and D2 are then estimated. Application of the proposed idea at the synthetic and real well-logs data of a borehole located in the Algerian Sahara shows that the fractal dimensions are very sensitive to lithological variations. The generalized fractal dimensions are a very robust tool than can be used for petroleum reservoir characterization. Keywrods: reservoir, Heterogeneities, WTMM, fractal dimension.
Automatic detection of position and depth of potential UXO using continuous wavelet transforms
NASA Astrophysics Data System (ADS)
Billings, Stephen D.; Herrmann, Felix J.
2003-09-01
Inversion algorithms for UXO discrimination using magnetometery have recently been used to achieve very low False Alarm Rates, with 100% recovery of detected ordnance. When there are many UXO and/or when the UXO are at significantly different depths, manual estimation of the initial position and scale for each item, is a laborious and time-consuming process. In this paper, we utilize the multi-resolution properties of wavelets to automatically estimate both the position and scale of dipole peaks. The Automated Wavelet Detection (AWD) algorithm that we develop consists of four-stages: (i) maxima and minima in the data are followed across multiple scales as we zoom with a continuous wavelet transform; (ii) the decay of the amplitude of each peak with scale is used to estimate the depth to source; (iii) adjacent maxima and minima of comparable depth are joined together to form dipole anomalies; and (iv) the relative positions and amplitudes of the extrema, along with their depths, are used to estimate a dipole model. We demonstrate the application of the AWD algorithm to three datasets with different characteristics. In each case, the method rapidly located the majority of dipole anomalies and produced accurate estimates of dipole parameters.
Dinç, E; Baleanu, D; Ustündağ, O; Aboul-Enein, H Y
2004-08-01
In this paper we developed a graphical method based on Haar (HA) and Mexican (MEX) one-dimensional continuous wavelet transforms and we applied it to a mixture of hydrochlorothiazide (HCT) and spironolactone (SP) in the presence of strongly overlapping signals. Keeping in mind to obtain an appropriately transformed spectrum, we tested several values of the scaling parameter a and the point number of the analysed spectrum in the concentration range of 2-22 microg/ml for both active compounds. The optimal values of the scale parameters and the corresponding frequencies were found to be a = 32 and 0.031 for HA and a = 30 and 0.008 for MEX corresponding to 400 points. HA and MEX methods based on a zero crossing technique were applied to the analysed signal and their regression lines at the selected points were obtained. The validation of the above methods was carried out by analysing different synthetic mixtures containing HCT and SP. MATLAB 6.5 software was used for one-dimensional wavelet analysis and the basic concepts about wavelet method were briefly explained. The method developed in this paper is rapid, easy to apply, inexpensive and is suitable for analysing the overlapping signals of compounds in their mixtures without any chemical pre-treatment.
Yang, W.; Wu, H.; Cao, L.
2012-07-01
More and more MOX fuels are used in all over the world in the past several decades. Compared with UO{sub 2} fuel, it contains some new features. For example, the neutron spectrum is harder and more resonance interference effects within the resonance energy range are introduced because of more resonant nuclides contained in the MOX fuel. In this paper, the wavelets scaling function expansion method is applied to study the resonance behavior of plutonium isotopes within MOX fuel. Wavelets scaling function expansion continuous-energy self-shielding method is developed recently. It has been validated and verified by comparison to Monte Carlo calculations. In this method, the continuous-energy cross-sections are utilized within resonance energy, which means that it's capable to solve problems with serious resonance interference effects without iteration calculations. Therefore, this method adapts to treat the MOX fuel resonance calculation problem natively. Furthermore, plutonium isotopes have fierce oscillations of total cross-section within thermal energy range, especially for {sup 240}Pu and {sup 242}Pu. To take thermal resonance effect of plutonium isotopes into consideration the wavelet scaling function expansion continuous-energy resonance calculation code WAVERESON is enhanced by applying the free gas scattering kernel to obtain the continuous-energy scattering source within thermal energy range (2.1 eV to 4.0 eV) contrasting against the resonance energy range in which the elastic scattering kernel is utilized. Finally, all of the calculation results of WAVERESON are compared with MCNP calculation. (authors)
NASA Astrophysics Data System (ADS)
Qian, Jinfang; Zhang, Changjiang
2014-11-01
An efficient algorithm based on continuous wavelet transform combining with pre-knowledge, which can be used to detect the defect of glass bottle mouth, is proposed. Firstly, under the condition of ball integral light source, a perfect glass bottle mouth image is obtained by Japanese Computar camera through the interface of IEEE-1394b. A single threshold method based on gray level histogram is used to obtain the binary image of the glass bottle mouth. In order to efficiently suppress noise, moving average filter is employed to smooth the histogram of original glass bottle mouth image. And then continuous wavelet transform is done to accurately determine the segmentation threshold. Mathematical morphology operations are used to get normal binary bottle mouth mask. A glass bottle to be detected is moving to the detection zone by conveyor belt. Both bottle mouth image and binary image are obtained by above method. The binary image is multiplied with normal bottle mask and a region of interest is got. Four parameters (number of connected regions, coordinate of centroid position, diameter of inner cycle, and area of annular region) can be computed based on the region of interest. Glass bottle mouth detection rules are designed by above four parameters so as to accurately detect and identify the defect conditions of glass bottle. Finally, the glass bottles of Coca-Cola Company are used to verify the proposed algorithm. The experimental results show that the proposed algorithm can accurately detect the defect conditions of the glass bottles and have 98% detecting accuracy.
NASA Astrophysics Data System (ADS)
Ali, Abebe Mohammed; Skidmore, Andrew K.; Darvishzadeh, Roshanak; van Duren, Iris; Holzwarth, Stefanie; Mueller, Joerg
2016-12-01
Quantification of vegetation properties plays an important role in the assessment of ecosystem functions with leaf dry mater content (LDMC) and specific leaf area (SLA) being two key functional traits. For the first time, these two leaf traits have been estimated from the airborne images (HySpex) using the INFORM radiative transfer model and Continuous Wavelet Analysis (CWA). Ground truth data, were collected for 33 sample plots during a field campaign in July 2013 in the Bavarian Forest National Park, Germany, concurrent with the hyperspectral overflight. The INFORM model was used to simulate the canopy reflectance of the test site and the simulated spectra were transformed to wavelet features by applying CWA. Next, the top 1% strongly correlated wavelet features with the LDMC and SLA were used to develop predictive (regression) models. The two leaf traits were then retrieved using the CWA transformed HySpex imagery and the predictive models. The results were validated using R2 and the RMSE of the estimated and measured variables. Our results revealed strong correlations between six wavelet features and LDMC, as well as between four wavelet features and SLA. The wavelet features at 1741 nm (scale 5) and 2281 nm (scale 4) were the two most strongly correlated with LDMC and SLA respectively. The combination of all the identified wavelet features for LDMC yielded the most accurate prediction (R2 = 0.59 and RMSE = 4.39%). However, for SLA the most accurate prediction was obtained from the single most correlated feature: 2281 nm, scale 4 (R2 = 0.85 and RMSE = 4.90). Our results demonstrate the applicability of Continuous Wavelet Analysis (CWA) when inverting radiative transfer models, for accurate mapping of forest leaf functional traits.
H∞ control of a class of 2-D continuous switched delayed systems via state-dependent switching
NASA Astrophysics Data System (ADS)
Ghous, Imran; Xiang, Zhengrong
2016-01-01
This paper addresses the problem of state feedback H∞ stabilisation of 2-D (two-dimensional) continuous switched state delayed systems represented by the Roesser model using the multiple Lyapunov functional approach. First, an asymptotical stability condition of 2-D continuous switched systems with state-dependent switching is derived. Second, a sufficient condition for H∞ performance of the underlying system is established. Third, a state feedback controller is proposed to ensure that the resulting closed-loop system has a prescribed H∞ performance level under a state-dependent switching signal. All the results are developed in terms of linear matrix inequalities. Finally, three examples are provided to demonstrate the validity and effectiveness of the proposed method.
Surface contouring by optical edge projection based on a continuous wavelet transform.
Quan, Chenggen; Miao, Hong; Fu, Yu
2006-07-10
A novel optical edge projection method for surface contouring of an object with low reflectivity is presented. A structured light edge is projected onto a dark surface, and the image is captured by a CCD camera. The surface profile of the object is then evaluated by an active triangular projection technique, and a whole-field three-dimensional contour of the object is obtained by scanning the optical edge over the entire object surface. An edge detection method based on a continuous wavelet transform (CWT) is employed to determine the location of the optical edge. The method of optical edge detection is described, and characteristic details of gray-level distribution along the edge are analyzed. It is shown that the proposed wavelet edge detection method is not dependent on any threshold values; hence the true edge position can be determined without subjective selection. A black low-reflectivity object surface made from woven carbon fiber is measured, and the experimental results show that the profile of a woven carbon fiber can be obtained by the proposed method.
Lahmiri, Salim; Gargour, Christian S; Gabrea, Marcel
2014-10-01
An automated diagnosis system that uses complex continuous wavelet transform (CWT) to process retina digital images and support vector machines (SVMs) for classification purposes is presented. In particular, each retina image is transformed into two one-dimensional signals by concatenating image rows and columns separately. The mathematical norm of phase angles found in each one-dimensional signal at each level of CWT decomposition are relied on to characterise the texture of normal images against abnormal images affected by exudates, drusen and microaneurysms. The leave-one-out cross-validation method was adopted to conduct experiments and the results from the SVM show that the proposed approach gives better results than those obtained by other methods based on the correct classification rate, sensitivity and specificity.
Sadabadi, Mahdiye Sadat; Shafiee, Masoud; Karrari, Mehdi
2008-07-01
In this paper, parameter identification of two-dimensional continuous-time systems via two-dimensional modulating functions is proposed. In the proposed method, trigonometric functions and sine-cosine wavelets are used as modulating functions. By this, a partial differential equation on the finite-time intervals is converted into an algebraic equation linear in parameters. The parameters of the system can then be estimated using the least square algorithms. The underlying computations utilize a two-dimensional fast Fourier transform algorithm, without the need for estimating the unknown initial or boundary conditions, at the beginning of each finite-time interval. Numerical simulations are presented to show the effectiveness of the proposed algorithm.
NASA Astrophysics Data System (ADS)
Li, M.; Quan, C.; Tay, C. J.
2008-10-01
White-light interferometric techniques have been widely used in three-dimensional (3D) profiling. This paper presents a new method based on vertical scanning interferometry (VSI) for the 3D profile measurement of a micro-component that contains sharp steps. The use of a white-light source in the system overcomes the phase ambiguity problem often encountered in monochromatic interferometry and also reduces speckle noises. A new algorithm based on the continuous wavelet transform (CWT) is used to retrieve the phase of an interferogram. The algorithm accurately determines local fringe peak and improves the vertical resolution of the measurement. The proposed method is highly resistant to noise and is able to achieve high accuracy. A micro-component (lamellar grating) fabricated by sacrificial etching technique is used as a test specimen to verify the proposed method. The measurement uncertainty of the experimental results is discussed.
Estimating 3D movements from 2D observations using a continuous model of helical swimming.
Gurarie, Eliezer; Grünbaum, Daniel; Nishizaki, Michael T
2011-06-01
Helical swimming is among the most common movement behaviors in a wide range of microorganisms, and these movements have direct impacts on distributions, aggregations, encounter rates with prey, and many other fundamental ecological processes. Microscopy and video technology enable the automated acquisition of large amounts of tracking data; however, these data are typically two-dimensional. The difficulty of quantifying the third movement component complicates understanding of the biomechanical causes and ecological consequences of helical swimming. We present a versatile continuous stochastic model-the correlated velocity helical movement (CVHM) model-that characterizes helical swimming with intrinsic randomness and autocorrelation. The model separates an organism's instantaneous velocity into a slowly varying advective component and a perpendicularly oriented rotation, with velocities, magnitude of stochasticity, and autocorrelation scales defined for both components. All but one of the parameters of the 3D model can be estimated directly from a two-dimensional projection of helical movement with no numerical fitting, making it computationally very efficient. As a case study, we estimate swimming parameters from videotaped trajectories of a toxic unicellular alga, Heterosigma akashiwo (Raphidophyceae). The algae were reared from five strains originally collected from locations in the Atlantic and Pacific Oceans, where they have caused Harmful Algal Blooms (HABs). We use the CVHM model to quantify cell-level and strain-level differences in all movement parameters, demonstrating the utility of the model for identifying strains that are difficult to distinguish by other means.
Ullah, Saleem; Skidmore, Andrew K; Naeem, Mohammad; Schlerf, Martin
2012-10-15
Leaf water content determines plant health, vitality, photosynthetic efficiency and is an important indicator of drought assessment. The retrieval of leaf water content from the visible to shortwave infrared spectra is well known. Here for the first time, we estimated leaf water content from the mid to thermal infrared (2.5-14.0 μm) spectra, based on continuous wavelet analysis. The dataset comprised 394 spectra from nine plant species, with different water contents achieved through progressive drying. To identify the spectral feature most sensitive to the variations in leaf water content, first the Directional Hemispherical Reflectance (DHR) spectra were transformed into a wavelet power scalogram, and then linear relations were established between the wavelet power scalogram and leaf water content. The six individual wavelet features identified in the mid infrared yielded high correlations with leaf water content (R(2)=0.86 maximum, 0.83 minimum), as well as low RMSE (minimum 8.56%, maximum 9.27%). The combination of four wavelet features produced the most accurate model (R(2)=0.88, RMSE=8.00%). The models were consistent in terms of accuracy estimation for both calibration and validation datasets, indicating that leaf water content can be accurately retrieved from the mid to thermal infrared domain of the electromagnetic radiation.
NASA Astrophysics Data System (ADS)
Li, Yuanyuan; Braitenberg, Carla; Yang, Yushan
2013-03-01
A slightly bended gravity high along the Chad lineament in Central North Africa is analyzed and interpreted by the continuous wavelet transform (CWT) method. We use scale normalization on the continuous wavelet transform, allowing analysis of the gravity field in order to determine the sources at different depths. By focusing on homogenous standard sources, such as sphere or cube, horizontal cylinder or prism, sheet and infinite step, we derive the relationships between the source depth and pseudo-wavenumber. Then the source depth can be recovered from tracing the maximal values of the modulus of the complex wavelet coefficients in the CWT-based scalograms that are function of the pseudo-wavenumber. The studied area includes a central gravity high up to 75 km wide, and a secondary high that occurs at the southern part of the anomaly. The interpretation of the depth slices and vertical sections of the modulus maxima of the complex wavelet coefficients allows recognition of a relatively dense terrane located at middle crustal levels (10-25 km depth). A reasonable geological model derived from the 2.5D gravity forward modelling indicates the presence of high density bodies, probably linked to a buried suture, which were thrusted up into the mid-crust during the Neo-Proterozoic terrane collisions between the Saharan metacraton and the Arabian-Nubian shield. We conclude that the Chad line delineates a first order geological boundary, missing on the geologic maps.
Ladner, Tobias; Beckers, Mario; Hitzmann, Bernd; Büchs, Jochen
2016-12-01
Small-scale high-throughput screening devices are becoming increasingly important in bioprocess development. Conventional dipping probes for process monitoring are often too large to be used in these devices. Thus, optical measurements are often the method of choice. Even some parameters that cannot directly be measured by fluorescence become accessible via sensitive fluorescence dyes. However, not all compounds of interest are measurable by this technique. Recent studies applying multi-wavelength (2D) fluorescence spectroscopy in combination with chemometrics have shown that information on numerous analytes is obscured by the fluorescence data. Hitherto, this measurement technique has only been available on the scale of stirred tank fermenters. This work introduces a new device for multi-wavelength (2D) fluorescence spectroscopy in each well of a continuously shaken microtiter plate. Using a combination of spectrograph and CCD detector, the required time per measurement cycle in a 48-well microtiter plate was 0.5 h. Cultures of Hansenula polymorpha and Escherichia coli are monitored. The concentrations of glycerol, glucose and acetate as well as pH are determined using partial least square (PLS) models. Because a pH-sensitive fluorescence dye was not required, no dependency of the pKa of a fluorescence dye exists, and measurements in the low pH range can be obtained.
NASA Astrophysics Data System (ADS)
Fedi, M.; Primiceri, R.; Quarta, T.; Villani, A. V.
2004-01-01
The discrete wavelet transform (dwt), using the good property of localization of wavelet bases has been used as a powerful tool in filtering and denoising problems. The continuous wavelet transform (cwt) exploits the upward continuation properties of the field horizontal derivative and allows the location of potential field singularities in a simple geometrical manner. Within the cwt space-scale framework, the lines formed by joining, at different scales, the modulus maxima of the wavelet coefficients (multiscale edge detection method) intersect each other at the position of the point source or along the edges of the causative body. As long as the multiscale edge detection method is applied to experimental data the procedure may, however, fail, since the observed anomalies are the superposition of effects of sources having different density contrast, geometrical size and depths. We show that wavelet transform modulus maxima lines attributed to deep sources do not converge toward the true depths, but yield completely erroneous solutions. On the other hand, use of nth-order derivatives of the potential field allows the enhancement of the shallowest source effects, preventing us from obtaining information on the deeper ones. In this paper we therefore try to overcome this problem by a joint application of cwt and dwt. A localized dwt filter coupled to compactness criterion allows the separation of the effects due to the deeper sources from those of the shallower ones. Hence, the multiscale edge detection method, applied separately to the original and the filtered signals enabled the estimation of the depth of shallower and deeper sources, respectively. This analysis, performed on the gravity anomalies of Sardinia (Italy), has given estimations of the depths to both the Campidano graben and the Moho discontinuity, in good agreement with previous interpretations of gravity and seismic data.
Continuous high-yield production of vertically aligned carbon nanotubes on 2D and 3D substrates.
Guzmán de Villoria, Roberto; Hart, A John; Wardle, Brian L
2011-06-28
Vertically aligned carbon nanotubes (VACNTs) have certain advantages over bulk CNT powders and randomly oriented CNT mats for applications in flexible electronic devices, filtration membranes, biosensors and multifunctional aerospace materials. Here, a machine and a process to synthesize VACNTs in a continuous manner are presented showing uniform growth on 2D and 3D substrates, including alumina fibers, silicon wafer pieces, and stainless steel foils. Aligned multiwalled carbon nanotubes (MWNT) are synthesized at substrate feed rates of up to 6.8 cm/min, and the CNTs reach up to 60 μm in length depending on residence time in the reactor. In addition to the aligned morphology indicative of high yield growth, transmission electron microscopy and Raman spectroscopy reveal that the CNTs are of comparable quality to CNTs grown via a similar batch process. A significant reduction in time, reaction products, gases, and energy is demonstrated relative to batch processing, paving the way for industrial production of VACNTs.
NASA Astrophysics Data System (ADS)
Fefferman, C. L.; Lee-Thorp, J. P.; Weinstein, M. I.
2016-03-01
Edge states are time-harmonic solutions to energy-conserving wave equations, which are propagating parallel to a line-defect or ‘edge’ and are localized transverse to it. This paper summarizes and extends the authors’ work on the bifurcation of topologically protected edge states in continuous two-dimensional (2D) honeycomb structures. We consider a family of Schrödinger Hamiltonians consisting of a bulk honeycomb potential and a perturbing edge potential. The edge potential interpolates between two different periodic structures via a domain wall. We begin by reviewing our recent bifurcation theory of edge states for continuous 2D honeycomb structures (http://arxiv.org/abs/1506.06111). The topologically protected edge state bifurcation is seeded by the zero-energy eigenstate of a one-dimensional Dirac operator. We contrast these protected bifurcations with (more common) non-protected bifurcations from spectral band edges, which are induced by bound states of an effective Schrödinger operator. Numerical simulations for honeycomb structures of varying contrasts and ‘rational edges’ (zigzag, armchair and others), support the following scenario: (a) for low contrast, under a sign condition on a distinguished Fourier coefficient of the bulk honeycomb potential, there exist topologically protected edge states localized transverse to zigzag edges. Otherwise, and for general edges, we expect long lived edge quasi-modes which slowly leak energy into the bulk. (b) For an arbitrary rational edge, there is a threshold in the medium-contrast (depending on the choice of edge) above which there exist topologically protected edge states. In the special case of the armchair edge, there are two families of protected edge states; for each parallel quasimomentum (the quantum number associated with translation invariance) there are edge states which propagate in opposite directions along the armchair edge.
Phase characteristic analysis of continuous depth air-gun source wavelet
NASA Astrophysics Data System (ADS)
Xing, Lei; Liu, Huaishan; Zheng, Xilai; Liu, Xueqin; Zhang, Jin; Wang, Linfei; Zou, Zhihui; Xu, Yiming
2016-10-01
Air guns are important sources for marine seismic exploration. Far-field wavelet of air gun arrays, as a necessary parameter for pre-stack processing and source models, plays an important role during marine seismic data processing and interpretation. When an air gun fires, it generates a series of air bubbles. Similar to onshore seismic exploration, the water forms a plastic fluid near the bubble; the farther the air gun is located from the measurement, the more steady and more accurately represented the wavelet will be. In practice, hydrophones should be placed more than 100 m from the air gun; however, traditional seismic cables cannot meet this requirement. On the other hand, vertical cables provide a viable solution to this problem. This study uses a vertical cable to receive wavelets from 38 air guns and data are collected offshore Southeast Qiong, where the water depth is over 1000 m. In this study, the wavelets measured using this technique coincide very well with the simulated wavelets and can therefore represent the real shape of the wavelets. This experiment fills a technology gap in China.
Optical HAAR Wavelet Transforms using Computer Generated Holography
1992-12-17
This research introduces an optical implementation of the continuous wavelet transform to filter images. The wavelet transform is modeled as a...continuous wavelet transform was performed and that the results compared favorably to digital simulation. Wavelets, Holography, Optical correlators.
NASA Astrophysics Data System (ADS)
Yang, Xi; Yan, Hong
2012-09-01
Based on the anisotropic deformation of DNA structure in nucleosomes, the non-linear dimensionality reduction algorithm Isomap is used to derive a structural signal accounting for most structural variances from the DNA structural data of nucleosome crystals. The analysis of this structural signal by continuous wavelet transform has successfully revealed the common regularity of nucleosome DNA deformation and also the peculiarity of structural configurations in nucleosomes with particular histone or DNA composition, or special ligands. The relationship between the constituent dinucleotides and the signal energy distribution shows that the fluctuation of a structural signal is sensitive to certain dinucleotide types.
Afkhami, Abbas; Abbasi-Tarighat, Maryam
2009-04-30
Wavelet transformation of kinetic profiles as a new and simple method was developed for the simultaneous determination of binary mixtures without prior separation steps. The mathematical explanation of the procedure is illustrated. Daubechies (db), symlet (sym) and discrete meyer wavelet (meyr) from the family of wavelet transforms were selected and applied under the optimal conditions for the resolution of binary mixtures. A model data as well as experimental data were tested. The results from the experimental data relating to the simultaneous spectrophotometric determination of phosphate and silicate based on the formation of phospho- and silico-molybdenum blue complexes in the presence of ascorbic acid, and also simultaneous determination of Co(2+) and Ni(2+) based on their complexation reactions with 1-(2-pyridylazo)-2-naphthol (PAN) in micellar media at pH 6.0 were presented as real models. The proposed method was validated by simultaneous determination of phosphate and silicate in detergent and tap water and also Co(2+) and Ni(2+) in tap water samples.
Continuous digital ECG analysis over accurate R-peak detection using adaptive wavelet technique.
Gopalakrishnan Nair, T R; Geetha, A P; Asharani, M
2013-10-01
Worldwide, health care segment is under a severe challenge to achieve more accurate and intelligent biomedical systems in order to assist healthcare professionals with more accurate and consistent data as well as reliability. The role of ECG in healthcare is one of the paramount importances and it has got a multitude of abnormal relations and anomalies which characterizes intricate cardiovascular performance image. Until the recent past, ECG instruments and analysis played the role of providing the PQRST signal as raw observational output either on paper or on a console or in a file having many diagnostic clues embedded in the signal left to the expert cardiologist to look out for characteristic intervals and to detect the cardiovascular abnormality. Methods and practises are required more and more, to automate this process of cardiac expertise using knowledge engineering and an intelligent systems approach. This paper presents one of the challenging R-peak detections to classify diagnosis and estimate cardio disorders in a fully automated signal processing sequence. This study used an adaptive wavelet approach to generate an appropriate wavelet for R-signal identification under noise, baseband wandering and temporal variations of R-positions. This study designed an adaptive wavelet and successfully detected R- peak variations under various ECG signal conditions. The result and analysis of this method and the ways to use it for further purposes are presented here.
Wavelet Analysis of Bioacoustic Scattering and Marine Mammal Vocalizations
2005-09-01
17 B. DISCRETE WAVELET TRANSFORM .....................................................17 1. Mother Wavelet ...LEFT BLANK 11 III. WAVELET THEORY There are two distinct classes of wavelet transforms : the continuous wavelet transform (CWT) and the discrete ... wavelet transform (DWT). The discrete wavelet transform is a compact representation of the data and is particularly useful for noise reduction and
NASA Astrophysics Data System (ADS)
van den Berg, J. C.
1999-08-01
A guided tour J. C. van den Berg; 1. Wavelet analysis, a new tool in physics J.-P. Antoine; 2. The 2-D wavelet transform, physical applications J.-P. Antoine; 3. Wavelets and astrophysical applications A. Bijaoui; 4. Turbulence analysis, modelling and computing using wavelets M. Farge, N. K.-R. Kevlahan, V. Perrier and K. Schneider; 5. Wavelets and detection of coherent structures in fluid turbulence L. Hudgins and J. H. Kaspersen; 6. Wavelets, non-linearity and turbulence in fusion plasmas B. Ph. van Milligen; 7. Transfers and fluxes of wind kinetic energy between orthogonal wavelet components during atmospheric blocking A. Fournier; 8. Wavelets in atomic physics and in solid state physics J.-P. Antoine, Ph. Antoine and B. Piraux; 9. The thermodynamics of fractals revisited with wavelets A. Arneodo, E. Bacry and J. F. Muzy; 10. Wavelets in medicine and physiology P. Ch. Ivanov, A. L. Goldberger, S. Havlin, C.-K. Peng, M. G. Rosenblum and H. E. Stanley; 11. Wavelet dimension and time evolution Ch.-A. Guérin and M. Holschneider.
NASA Astrophysics Data System (ADS)
van den Berg, J. C.
2004-03-01
A guided tour J. C. van den Berg; 1. Wavelet analysis, a new tool in physics J.-P. Antoine; 2. The 2-D wavelet transform, physical applications J.-P. Antoine; 3. Wavelets and astrophysical applications A. Bijaoui; 4. Turbulence analysis, modelling and computing using wavelets M. Farge, N. K.-R. Kevlahan, V. Perrier and K. Schneider; 5. Wavelets and detection of coherent structures in fluid turbulence L. Hudgins and J. H. Kaspersen; 6. Wavelets, non-linearity and turbulence in fusion plasmas B. Ph. van Milligen; 7. Transfers and fluxes of wind kinetic energy between orthogonal wavelet components during atmospheric blocking A. Fournier; 8. Wavelets in atomic physics and in solid state physics J.-P. Antoine, Ph. Antoine and B. Piraux; 9. The thermodynamics of fractals revisited with wavelets A. Arneodo, E. Bacry and J. F. Muzy; 10. Wavelets in medicine and physiology P. Ch. Ivanov, A. L. Goldberger, S. Havlin, C.-K. Peng, M. G. Rosenblum and H. E. Stanley; 11. Wavelet dimension and time evolution Ch.-A. Guérin and M. Holschneider.
Abid, Abdulbasit
2013-03-01
This paper presents a thorough discussion of the proposed field-programmable gate array (FPGA) implementation for fringe pattern demodulation using the one-dimensional continuous wavelet transform (1D-CWT) algorithm. This algorithm is also known as wavelet transform profilometry. Initially, the 1D-CWT is programmed using the C programming language and compiled into VHDL using the ImpulseC tool. This VHDL code is implemented on the Altera Cyclone IV GX EP4CGX150DF31C7 FPGA. A fringe pattern image with a size of 512×512 pixels is presented to the FPGA, which processes the image using the 1D-CWT algorithm. The FPGA requires approximately 100 ms to process the image and produce a wrapped phase map. For performance comparison purposes, the 1D-CWT algorithm is programmed using the C language. The C code is then compiled using the Intel compiler version 13.0. The compiled code is run on a Dell Precision state-of-the-art workstation. The time required to process the fringe pattern image is approximately 1 s. In order to further reduce the execution time, the 1D-CWT is reprogramed using Intel Integrated Primitive Performance (IPP) Library Version 7.1. The execution time was reduced to approximately 650 ms. This confirms that at least sixfold speedup was gained using FPGA implementation over a state-of-the-art workstation that executes heavily optimized implementation of the 1D-CWT algorithm.
Real, Ruben G L; Kotchoubey, Boris; Kübler, Andrea
2014-01-01
This study aimed at evaluating the performance of the Studentized Continuous Wavelet Transform (t-CWT) as a method for the extraction and assessment of event-related brain potentials (ERP) in data from a single subject. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of the t-CWT were assessed and compared to a variety of competing procedures using simulated EEG data at six low signal-to-noise ratios. Results show that the t-CWT combines high sensitivity and specificity with favorable PPV and NPV. Applying the t-CWT to authentic EEG data obtained from 14 healthy participants confirmed its high sensitivity. The t-CWT may thus be well suited for the assessment of weak ERPs in single-subject settings.
Elzanfaly, Eman S; Hassan, Said A; Salem, Maissa Y; El-Zeany, Badr A
2015-12-05
A comparative study was established between two signal processing techniques showing the theoretical algorithm for each method and making a comparison between them to indicate the advantages and limitations. The methods under study are Numerical Differentiation (ND) and Continuous Wavelet Transform (CWT). These methods were studied as spectrophotometric resolution tools for simultaneous analysis of binary and ternary mixtures. To present the comparison, the two methods were applied for the resolution of Bisoprolol (BIS) and Hydrochlorothiazide (HCT) in their binary mixture and for the analysis of Amlodipine (AML), Aliskiren (ALI) and Hydrochlorothiazide (HCT) as an example for ternary mixtures. By comparing the results in laboratory prepared mixtures, it was proven that CWT technique is more efficient and advantageous in analysis of mixtures with severe overlapped spectra than ND. The CWT was applied for quantitative determination of the drugs in their pharmaceutical formulations and validated according to the ICH guidelines where accuracy, precision, repeatability and robustness were found to be within the acceptable limit.
Real, Ruben G. L.; Kotchoubey, Boris; Kübler, Andrea
2014-01-01
This study aimed at evaluating the performance of the Studentized Continuous Wavelet Transform (t-CWT) as a method for the extraction and assessment of event-related brain potentials (ERP) in data from a single subject. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of the t-CWT were assessed and compared to a variety of competing procedures using simulated EEG data at six low signal-to-noise ratios. Results show that the t-CWT combines high sensitivity and specificity with favorable PPV and NPV. Applying the t-CWT to authentic EEG data obtained from 14 healthy participants confirmed its high sensitivity. The t-CWT may thus be well suited for the assessment of weak ERPs in single-subject settings. PMID:25309308
Fan, Mengli; Cai, Wensheng; Shao, Xueguang
2017-03-01
The circulatory protein, human serum albumin (HSA), is widely used as a model protein for the study of protein structure. In this work, the structures of human serum albumin in aqueous solutions are studied using temperature-dependent near-infrared (NIR) spectroscopy with the aid of continuous wavelet transform (CWT). Near-infrared spectra of human serum albumin solutions with different concentrations were measured over a temperature range of 30-85 ℃. Then, continuous wavelet transform was performed on the spectra to enhance the resolution. As a result of the resolution enhancement, spectral bands around 4361, 4521, 4600 and 4260 cm(-1) were extracted from the overlapping low-resolution signals. The four bands can be assigned to the protein structures of α-helix, β-sheet, an intermediate state and side chains, respectively. The variations in intensity of the bands around 4361 and 4521 cm(-1) with temperature show that the increase of temperature leads to the loss of α-helical structure but the formation of β-sheet, and the denaturation temperature of human serum albumin is about 55 ℃. The variation of the band around 4600 cm(-1) indicates that the temperature-induced unfolding process of human serum albumin occurs through a stable intermediate state, and a significant change in the microenvironment of the side chains about 63 ℃ is observed from the variation of the band around 4260 cm(-1). On the other hand, the transformed spectra in the region of 8000-5600 cm(-1) provide an explicit evidence for the structural changes of water during the process of protein denaturation, and the unfolding process of HSA can be reflected by these changes.
NASA Astrophysics Data System (ADS)
Debenjak, Andrej; Boškoski, Pavle; Musizza, Bojan; Petrovčič, Janko; Juričić, Đani
2014-05-01
This paper proposes an approach to the estimation of PEM fuel cell impedance by utilizing pseudo-random binary sequence as a perturbation signal and continuous wavelet transform with Morlet mother wavelet. With the approach, the impedance characteristic in the frequency band from 0.1 Hz to 500 Hz is identified in 60 seconds, approximately five times faster compared to the conventional single-sine approach. The proposed approach was experimentally evaluated on a single PEM fuel cell of a larger fuel cell stack. The quality of the results remains at the same level compared to the single-sine approach.
Wavelet Transforms using VTK-m
Li, Shaomeng; Sewell, Christopher Meyer
2016-09-27
These are a set of slides that deal with the topics of wavelet transforms using VTK-m. First, wavelets are discussed and detailed, then VTK-m is discussed and detailed, then wavelets and VTK-m are looked at from a performance comparison, then from an accuracy comparison, and finally lessons learned, conclusion, and what is next. Lessons learned are the following: Launching worklets is expensive; Natural logic of performing 2D wavelet transform: Repeat the same 1D wavelet transform on every row, repeat the same 1D wavelet transform on every column, invoke the 1D wavelet worklet every time: num_rows x num_columns; VTK-m approach of performing 2D wavelet transform: Create a worklet for 2D that handles both rows and columns, invoke this new worklet only one time; Fast calculation, but cannot reuse 1D implementations.
Komorowski, Dariusz; Pietraszek, Stanislaw
2016-01-01
This paper presents the analysis of multi-channel electrogastrographic (EGG) signals using the continuous wavelet transform based on the fast Fourier transform (CWTFT). The EGG analysis was based on the determination of the several signal parameters such as dominant frequency (DF), dominant power (DP) and index of normogastria (NI). The use of continuous wavelet transform (CWT) allows for better visible localization of the frequency components in the analyzed signals, than commonly used short-time Fourier transform (STFT). Such an analysis is possible by means of a variable width window, which corresponds to the scale time of observation (analysis). Wavelet analysis allows using long time windows when we need more precise low-frequency information, and shorter when we need high frequency information. Since the classic CWT transform requires considerable computing power and time, especially while applying it to the analysis of long signals, the authors used the CWT analysis based on the fast Fourier transform (FFT). The CWT was obtained using properties of the circular convolution to improve the speed of calculation. This method allows to obtain results for relatively long records of EGG in a fairly short time, much faster than using the classical methods based on running spectrum analysis (RSA). In this study authors indicate the possibility of a parametric analysis of EGG signals using continuous wavelet transform which is the completely new solution. The results obtained with the described method are shown in the example of an analysis of four-channel EGG recordings, performed for a non-caloric meal.
NASA Astrophysics Data System (ADS)
Qiu, Bingwen; Feng, Min; Tang, Zhenghong
2016-05-01
This study proposed a simple Smoother without any local adjustments based on Continuous Wavelet Transform (SCWT). And then it evaluated its performance together with other commonly applied techniques in phenological estimation. These noise reduction methods included Savitzky-Golay filter (SG), Double Logistic function (DL), Asymmetric Gaussian function (AG), Whittaker Smoother (WS) and Harmonic Analysis of Time-Series (HANTS). They were evaluated based on fidelity and smoothness, and their efficiencies in deriving phenological parameters through the inflexion point-based method with the 8-day composite Moderate Resolution Imaging Spectroradiometer (MODIS) 2-band Enhanced Vegetation Index (EVI2) in 2013 in China. The following conclusions were drawn: (1) The SG method exhibited strong fidelity, but weak smoothness and spatial continuity. (2) The HANTS method had very robust smoothness but weak fidelity. (3) The AG and DL methods performed weakly for vegetation with more than one growth cycle (i.e., multiple crops). (4) The WS and SCWT smoothers outperformed others with combined considerations of fidelity and smoothness, and consistent phenological patterns (correlation coefficients greater than 0.8 except evergreen broadleaf forests (0.68)). (5) Compared with WS methods, the SCWT smoother was capable in preservation of real local minima and maxima with fewer inflexions. (6) Large discrepancy was examined from the estimated phenological dates with SG and HANTS methods, particularly in evergreen forests and multiple cropping regions (the absolute mean deviation rates were 6.2-17.5 days and correlation coefficients less than 0.34 for estimated start dates).
2D continuous spectrum of shear Alfvén waves in the presence of a magnetic island
NASA Astrophysics Data System (ADS)
Biancalani, Alessandro; Chen, Liu; Pegoraro, Francesco; Zonca, Fulvio
2011-02-01
The radial structure of the continuous spectrum of shear Alfvén modes is calculated in the presence of a magnetic island in tokamak plasmas. Modes with the same helicity as the magnetic island are considered in a slab model approximation. In this framework, with an appropriate rotation of the coordinates the problem reduces to two dimensions. Geometrical effects due to the shape of the flux surface's cross-section are retained to all orders. On the other hand, we neglect toroidal couplings but fully take into account curvature effects responsible for the beta-induced gap in the low-frequency part of the continuous spectrum. New continuum accumulation points are found at the O-point of the magnetic island. The beta-induced Alfvén eigenmodes (BAE) continuum accumulation point is found to be positioned at the separatrix flux surface. The most remarkable result is the modification of the BAE continuum accumulation point frequency, due to the presence of the magnetic island.
NASA Astrophysics Data System (ADS)
Farhat, Aseel; Lunasin, Evelyn; Titi, Edriss S.
2017-01-01
In this paper we propose a continuous data assimilation (downscaling) algorithm for a two-dimensional Bénard convection problem. Specifically we consider the two-dimensional Boussinesq system of a layer of incompressible fluid between two solid horizontal walls, with no-normal flow and stress-free boundary conditions on the walls, and the fluid is heated from the bottom and cooled from the top. In this algorithm, we incorporate the observables as a feedback (nudging) term in the evolution equation of the horizontal velocity. We show that under an appropriate choice of the nudging parameter and the size of the spatial coarse mesh observables, and under the assumption that the observed data are error free, the solution of the proposed algorithm converges at an exponential rate, asymptotically in time, to the unique exact unknown reference solution of the original system, associated with the observed data on the horizontal component of the velocity.
NASA Astrophysics Data System (ADS)
Esposito, Angelo; Russo, Luigi; Kändler, Christoph; Pianese, Cesare; Ludwig, Bastian; Steiner, Nadia Yousfi
2016-06-01
The on-line diagnostics of Solid Oxide Fuel Cells (SOFCs) is a critical tool to achieve optimal performance and extend the lifetime. The Continuous Wavelet Transform (CWT) methodology was applied to the SOFC voltage signal to detect signatures that reveal the presence of a fault in the cell/stack. The selected fault was anode re-oxidation caused by high Fuel Utilization (FU) (higher then nominal). To experimentally emulate the high FU faults, a standard test procedure was developed, which was used to characterize a μ-CHP system at high FU operation. To complete the analysis, data collected on Single Cells were exploited too. The CWT was applied to the voltage signal for each FU level to verify the qualitative difference (signature) between the signals at different FU's within the same tests as well as the correspondence between the same conditions over different tests. A statistical study was performed to quantify the observed differences and to determine the correspondence between CWT coefficients and operating conditions. The approach proves to be suitable to diagnose high FU in SOFC, showing a successful detection rate above 76%. The results show the good potential of using the CWT methodology as diagnostic tools for SOFCs from cell to stack level.
NASA Astrophysics Data System (ADS)
Singh, Arvind; Singh, Upendra Kumar
2017-02-01
This paper deals with the application of continuous wavelet transform (CWT) and Euler deconvolution methods to estimate the source depth using magnetic anomalies. These methods are utilized mainly to focus on the fundamental issue of mapping the major coal seam and locating tectonic lineaments. The main aim of the study is to locate and characterize the source of the magnetic field by transferring the data into an auxiliary space by CWT. The method has been tested on several synthetic source anomalies and finally applied to magnetic field data from Jharia coalfield, India. Using magnetic field data, the mean depth of causative sources points out the different lithospheric depth over the study region. Also, it is inferred that there are two faults, namely the northern boundary fault and the southern boundary fault, which have an orientation in the northeastern and southeastern direction respectively. Moreover, the central part of the region is more faulted and folded than the other parts and has sediment thickness of about 2.4 km. The methods give mean depth of the causative sources without any a priori information, which can be used as an initial model in any inversion algorithm.
Wavelet Analyses and Applications
ERIC Educational Resources Information Center
Bordeianu, Cristian C.; Landau, Rubin H.; Paez, Manuel J.
2009-01-01
It is shown how a modern extension of Fourier analysis known as wavelet analysis is applied to signals containing multiscale information. First, a continuous wavelet transform is used to analyse the spectrum of a nonstationary signal (one whose form changes in time). The spectral analysis of such a signal gives the strength of the signal in each…
Tsanas, Athanasios; Clifford, Gari D
2015-01-01
Sleep spindles are critical in characterizing sleep and have been associated with cognitive function and pathophysiological assessment. Typically, their detection relies on the subjective and time-consuming visual examination of electroencephalogram (EEG) signal(s) by experts, and has led to large inter-rater variability as a result of poor definition of sleep spindle characteristics. Hitherto, many algorithmic spindle detectors inherently make signal stationarity assumptions (e.g., Fourier transform-based approaches) which are inappropriate for EEG signals, and frequently rely on additional information which may not be readily available in many practical settings (e.g., more than one EEG channels, or prior hypnogram assessment). This study proposes a novel signal processing methodology relying solely on a single EEG channel, and provides objective, accurate means toward probabilistically assessing the presence of sleep spindles in EEG signals. We use the intuitively appealing continuous wavelet transform (CWT) with a Morlet basis function, identifying regions of interest where the power of the CWT coefficients corresponding to the frequencies of spindles (11-16 Hz) is large. The potential for assessing the signal segment as a spindle is refined using local weighted smoothing techniques. We evaluate our findings on two databases: the MASS database comprising 19 healthy controls and the DREAMS sleep spindle database comprising eight participants diagnosed with various sleep pathologies. We demonstrate that we can replicate the experts' sleep spindles assessment accurately in both databases (MASS database: sensitivity: 84%, specificity: 90%, false discovery rate 83%, DREAMS database: sensitivity: 76%, specificity: 92%, false discovery rate: 67%), outperforming six competing automatic sleep spindle detection algorithms in terms of correctly replicating the experts' assessment of detected spindles.
NASA Astrophysics Data System (ADS)
Sánchez-Úbeda, Juan Pedro; Calvache, María Luisa; Duque, Carlos; López-Chicano, Manuel
2016-11-01
A new methodology has been developed to obtain tidal-filtered time series of groundwater levels in coastal aquifers. Two methods used for oceanography processing and forecasting of sea level data were adapted for this purpose and compared: HA (Harmonic Analysis) and CWT (Continuous Wavelet Transform). The filtering process is generally comprised of two main steps: the detection and fitting of the major tide constituents through the decomposition of the original signal and the subsequent extraction of the complete tidal oscillations. The abilities of the optional HA and CWT methods to decompose and extract the tidal oscillations were assessed by applying them to the data from two piezometers at different depths close to the shoreline of a Mediterranean coastal aquifer (Motril-Salobreña, SE Spain). These methods were applied to three time series of different lengths (one month, one year, and 3.7 years of hourly data) to determine the range of detected frequencies. The different lengths of time series were also used to determine the fit accuracies of the tidal constituents for both the sea level and groundwater heads measurements. The detected tidal constituents were better resolved with increasing depth in the aquifer. The application of these methods yielded a detailed resolution of the tidal components, which enabled the extraction of the major tidal constituents of the sea level measurements from the groundwater heads (e.g., semi-diurnal, diurnal, fortnightly, monthly, semi-annual and annual). In the two wells studied, the CWT method was shown to be a more effective method than HA for extracting the tidal constituents of highest and lowest frequencies from groundwater head measurements.
Wavelet analysis in neurodynamics
NASA Astrophysics Data System (ADS)
Pavlov, Aleksei N.; Hramov, Aleksandr E.; Koronovskii, Aleksei A.; Sitnikova, Evgenija Yu; Makarov, Valeri A.; Ovchinnikov, Alexey A.
2012-09-01
Results obtained using continuous and discrete wavelet transforms as applied to problems in neurodynamics are reviewed, with the emphasis on the potential of wavelet analysis for decoding signal information from neural systems and networks. The following areas of application are considered: (1) the microscopic dynamics of single cells and intracellular processes, (2) sensory data processing, (3) the group dynamics of neuronal ensembles, and (4) the macrodynamics of rhythmical brain activity (using multichannel EEG recordings). The detection and classification of various oscillatory patterns of brain electrical activity and the development of continuous wavelet-based brain activity monitoring systems are also discussed as possibilities.
NASA Astrophysics Data System (ADS)
Sohrabi, Mahmoud Reza; Darabi, Golnaz
2016-01-01
Flavonoids are γ-benzopyrone derivatives, which are highly regarded in these researchers for their antioxidant property. In this study, two new signals processing methods been coupled with UV spectroscopy for spectral resolution and simultaneous quantitative determination of Myricetin, Kaempferol and Quercetin as flavonoids in Laurel, St. John's Wort and Green Tea without the need for any previous separation procedure. The developed methods are continuous wavelet transform (CWT) and least squares support vector machine (LS-SVM) methods integrated with UV spectroscopy individually. Different wavelet families were tested by CWT method and finally the Daubechies wavelet family (Db4) for Myricetin and the Gaussian wavelet families for Kaempferol (Gaus3) and Quercetin (Gaus7) were selected and applied for simultaneous analysis under the optimal conditions. The LS-SVM was applied to build the flavonoids prediction model based on absorption spectra. The root mean square errors for prediction (RMSEP) of Myricetin, Kaempferol and Quercetin were 0.0552, 0.0275 and 0.0374, respectively. The developed methods were validated by the analysis of the various synthetic mixtures associated with a well- known flavonoid contents. Mean recovery values of Myricetin, Kaempferol and Quercetin, in CWT method were 100.123, 100.253, 100.439 and in LS-SVM method were 99.94, 99.81 and 99.682, respectively. The results achieved by analyzing the real samples from the CWT and LS-SVM methods were compared to the HPLC reference method and the results were very close to the reference method. Meanwhile, the obtained results of the one-way ANOVA (analysis of variance) test revealed that there was no significant difference between the suggested methods.
Sohrabi, Mahmoud Reza; Darabi, Golnaz
2016-01-05
Flavonoids are γ-benzopyrone derivatives, which are highly regarded in these researchers for their antioxidant property. In this study, two new signals processing methods been coupled with UV spectroscopy for spectral resolution and simultaneous quantitative determination of Myricetin, Kaempferol and Quercetin as flavonoids in Laurel, St. John's Wort and Green Tea without the need for any previous separation procedure. The developed methods are continuous wavelet transform (CWT) and least squares support vector machine (LS-SVM) methods integrated with UV spectroscopy individually. Different wavelet families were tested by CWT method and finally the Daubechies wavelet family (Db4) for Myricetin and the Gaussian wavelet families for Kaempferol (Gaus3) and Quercetin (Gaus7) were selected and applied for simultaneous analysis under the optimal conditions. The LS-SVM was applied to build the flavonoids prediction model based on absorption spectra. The root mean square errors for prediction (RMSEP) of Myricetin, Kaempferol and Quercetin were 0.0552, 0.0275 and 0.0374, respectively. The developed methods were validated by the analysis of the various synthetic mixtures associated with a well- known flavonoid contents. Mean recovery values of Myricetin, Kaempferol and Quercetin, in CWT method were 100.123, 100.253, 100.439 and in LS-SVM method were 99.94, 99.81 and 99.682, respectively. The results achieved by analyzing the real samples from the CWT and LS-SVM methods were compared to the HPLC reference method and the results were very close to the reference method. Meanwhile, the obtained results of the one-way ANOVA (analysis of variance) test revealed that there was no significant difference between the suggested methods.
Wavelet despiking of fractographs
NASA Astrophysics Data System (ADS)
Aubry, Jean-Marie; Saito, Naoki
2000-12-01
Fractographs are elevation maps of the fracture zone of some broken material. The technique employed to create these maps often introduces noise composed of positive or negative 'spikes' that must be removed before further analysis. Since the roughness of these maps contains useful information, it must be preserved. Consequently, conventional denoising techniques cannot be employed. We use continuous and discrete wavelet transforms of these images, and the properties of wavelet coefficients related to pointwise Hoelder regularity, to detect and remove the spikes.
Edge Detection Using a Complex Wavelet
1993-12-01
A complex wavelet of the form Psi(x, y) = C(x jy)exp(-p(x-sq+y-sq))) is used in the continuous wavelet transform to obtain edges from a digital image...and x and y are position variables. The square root of the sum of the squares of the real and imaginary parts of the wavelet transform are used to...radar images and the resulting images are shown. Continuous wavelet transform , Digital image.
Adaptive boxcar/wavelet transform
NASA Astrophysics Data System (ADS)
Sezer, Osman G.; Altunbasak, Yucel
2009-01-01
This paper presents a new adaptive Boxcar/Wavelet transform for image compression. Boxcar/Wavelet decomposition emphasizes the idea of average-interpolation representation which uses dyadic averages and their interpolation to explain a special case of biorthogonal wavelet transforms (BWT). This perspective for image compression together with lifting scheme offers the ability to train an optimum 2-D filter set for nonlinear prediction (interpolation) that will adapt to the context around the low-pass wavelet coefficients for reducing energy in the high-pass bands. Moreover, the filters obtained after training is observed to posses directional information with some textural clues that can provide better prediction performance. This work addresses a firrst step towards obtaining this new set of training-based fillters in the context of Boxcar/Wavelet transform. Initial experimental results show better subjective quality performance compared to popular 9/7-tap and 5/3-tap BWTs with comparable results in objective quality.
Schlossnagle, G.; Restrepo, J.M.; Leaf, G.K.
1993-12-01
The properties of periodized Daubechies wavelets on [0,1] are detailed and contrasted against their counterparts which form a basis for L{sup 2}(R). Numerical examples illustrate the analytical estimates for convergence and demonstrate by comparison with Fourier spectral methods the superiority of wavelet projection methods for approximations. The analytical solution to inner products of periodized wavelets and their derivatives, which are known as connection coefficients, is presented, and several tabulated values are included.
NASA Astrophysics Data System (ADS)
Suvichakorn, A.; Ratiney, H.; Bucur, A.; Cavassila, S.; Antoine, J. P.
2009-10-01
We apply the Morlet wavelet transform (MWT) for quantitatively analyzing proton magnetic resonance spectroscopic (MRS) signals, more precisely signals acquired at short echo time. These signals contain many resonating components whose frequencies are characteristic of the observed metabolites, and amplitudes are directly related to the concentrations of these metabolites. With these powerful properties, in vivo MRS can be considered as a unique non-invasive tool to explore biochemical compounds of living tissues. However, the analysis and quantification of these metabolite contributions are difficult due to the low signal-to-noise ratio, the number of overlapping frequencies and the contamination of the signal of interest with water and a baseline originating from macromolecules and lipids. The baseline is a major obstacle for MRS quantification as its shape and intensity are generally not known a priori. In this paper, we present the methodology to quantify the signals by the MWT. We assess the ability of the proposed method to recover parameters such as metabolite amplitudes, frequencies and damping factors while facing successively quantification challenges arising from the non-Lorentzian lineshapes, overlapping frequencies, and noise or baseline. Tests of the method are performed on simulated signals alone or combined with either in vitro acquisition and/or in vivo macromolecular signal acquired on a horizontal 4.7 T scanner. In presence of the macromolecules, the amplitude parameter is correctly derived by the method, thanks to the time-scale representation of the wavelet which enables us to distinguish the two signals by their time decays and without any additional pre-processing.
Tryptic digests of human serum albumin (HSA) and human lung epithelial cell lysates were used as test samples in a novel proteomics study. Peptides were separated and analyzed using 2D-nano-LC/MSMS with strong cation exchange (SCX) and reverse phase (RP) chromatography and contin...
Magnetic properties of Y0.9Gd0.1Fe2D4.2 compound under continuous magnetic field up to 310 kOe
NASA Astrophysics Data System (ADS)
Paul-Boncour, V.; Guillot, M.; Mazet, T.
2012-04-01
In this work are presented results on the structural, magnetic, and magnetocaloric properties of the Y0.9Gd0.1Fe2D4.2 compound in which TM0 is shifted from 84 K to 110 K because of Gd influence. Magnetization measurements have been performed with a magnetic field up to 310 kOe in the 4.2-300 K temperature range with special attention paid near TM0. The spontaneous magnetization at 4.2 K (3.2 μB/mol) is smaller than for YFe2D4.2 (3.7 μB/mol), showing the contribution of Gd moments. Above 110 K, metamagnetic field-induced transitions are observed: the transition field HTR increases linearly with T. These transitions exist up to 170 K. The influence of both cell volume change and Gd magnetic contribution are finally discussed in comparison with other deuterides.
Mohd, Shukri; Holford, Karen M.; Pullin, Rhys
2014-02-12
Source location is an important feature of acoustic emission (AE) damage monitoring in nuclear piping. The ability to accurately locate sources can assist in source characterisation and early warning of failure. This paper describe the development of a novelAE source location technique termed 'Wavelet Transform analysis and Modal Location (WTML)' based on Lamb wave theory and time-frequency analysis that can be used for global monitoring of plate like steel structures. Source location was performed on a steel pipe of 1500 mm long and 220 mm outer diameter with nominal thickness of 5 mm under a planar location test setup using H-N sources. The accuracy of the new technique was compared with other AE source location methods such as the time of arrival (TOA) techniqueand DeltaTlocation. Theresults of the study show that the WTML method produces more accurate location resultscompared with TOA and triple point filtering location methods. The accuracy of the WTML approach is comparable with the deltaT location method but requires no initial acoustic calibration of the structure.
Ortiz Boyer, F; Fernández Romero, J M; Luque de Castro, M D; Quesada, J M
1999-03-01
A semi-automatic procedure for the continuous clean-up and concentration of several fat-soluble vitamins prior to their separation by HPLC and UV detection is reported. The procedure is based on the use of a minicolumn packed with aminopropylsilica as sorbent located prior to the chromatographic detection system. The overall process was developed and applied to the main liposoluble vitamins (A, D2, D3, E, K1, K3) and several hydroxy metabolites of vitamin D3 [25-(OH)-D3,24,25-(OH)2-D3 and 1,25-(OH)2-D3]. All the analytes were monitored at a compromise wavelength of 270 nm. Calibration graphs were constructed between 0.01 and 100 ng ml-1 for vitamin D2 and D3 and their hydroxy metabolites, between 0.1 and 100 ng ml-1 for vitamin A, K1 and K3 and between 1 and 100 ng ml-1 for vitamin E, with excellent regression coefficients (> or = 0.9901) in all cases. The precision was established at two concentration levels with acceptable RSDs in all instances (between 3.6 and 8.7%). The method was appropriate for the determination of vitamin D2, D3, K1 and K3 and the 24,25-dihydroxy and 25-hydroxy metabolites of vitamin D3 in human plasma. The method was applied to plasma samples spiked with the target analytes and the recoveries ranged between 78 and 109%.
Image denoising with the dual-tree complex wavelet transform
NASA Astrophysics Data System (ADS)
Yaseen, Alauldeen S.; Pavlova, Olga N.; Pavlov, Alexey N.; Hramov, Alexander E.
2016-04-01
The purpose of this study is to compare image denoising techniques based on real and complex wavelet-transforms. Possibilities provided by the classical discrete wavelet transform (DWT) with hard and soft thresholding are considered, and influences of the wavelet basis and image resizing are discussed. The quality of image denoising for the standard 2-D DWT and the dual-tree complex wavelet transform (DT-CWT) is studied. It is shown that DT-CWT outperforms 2-D DWT at the appropriate selection of the threshold level.
Hegazy, Maha A; Lotfy, Hayam M; Mowaka, Shereen; Mohamed, Ekram Hany
2016-07-05
Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.
NASA Astrophysics Data System (ADS)
Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany
2016-07-01
Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.
Wavelet transforms as solutions of partial differential equations
Zweig, G.
1997-10-01
This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). Wavelet transforms are useful in representing transients whose time and frequency structure reflect the dynamics of an underlying physical system. Speech sound, pressure in turbulent fluid flow, or engine sound in automobiles are excellent candidates for wavelet analysis. This project focused on (1) methods for choosing the parent wavelet for a continuous wavelet transform in pattern recognition applications and (2) the more efficient computation of continuous wavelet transforms by understanding the relationship between discrete wavelet transforms and discretized continuous wavelet transforms. The most interesting result of this research is the finding that the generalized wave equation, on which the continuous wavelet transform is based, can be used to understand phenomena that relate to the process of hearing.
NASA Astrophysics Data System (ADS)
Nardi, Fernando; Petroselli, Andrea; Grimaldi, Salvatore
2013-04-01
Ongoing efforts of remote sensing technologies to provide more accurate digital elevation models (DEMs) at the global scale are supporting the use of terrain analysis and hydrologic and hydraulic modelling algorithms for flood mapping in ungauged basins. In this work we implement a fully continuous hydrologic-hydraulic model feeded by a rainfall synthetic time series for providing river hydrographs that are routed along the channel using a bidimensional hydraulic model for the detailed physically-based characterization of the inundation process. In this way the whole physical process is represented, from the net rainfall to the flow time series, avoiding any conceptual sub-method (design hyetograph and hydrograph) commonly needed to apply standard flood modelling and mapping procedures. Nevertheless, the floodplain information is no longer deterministic as the result of the evaluation of the impact on the river valley of a single design hydrologic scenario (event-based approach,EBA), but the final result is composed of a combination of data derived by the application of a fully-continuous approach (FCA). Indeed FCA provides a flow depth time series for each single cell of the inundated domain. The final flood map should be, thus, the result of a proper analysis of this dataset in statistical, qualitative and quantitative terms. Otherwise this would lead to an undefined flooding scenario that could be useless for flood risk management and decision making in urban plans.
Optical wavelet transform for fingerprint identification
NASA Astrophysics Data System (ADS)
MacDonald, Robert P.; Rogers, Steven K.; Burns, Thomas J.; Fielding, Kenneth H.; Warhola, Gregory T.; Ruck, Dennis W.
1994-03-01
The Federal Bureau of Investigation (FBI) has recently sanctioned a wavelet fingerprint image compression algorithm developed for reducing storage requirements of digitized fingerprints. This research implements an optical wavelet transform of a fingerprint image, as the first step in an optical fingerprint identification process. Wavelet filters are created from computer- generated holograms of biorthogonal wavelets, the same wavelets implemented in the FBI algorithm. Using a detour phase holographic technique, a complex binary filter mask is created with both symmetry and linear phase. The wavelet transform is implemented with continuous shift using an optical correlation between binarized fingerprints written on a Magneto-Optic Spatial Light Modulator and the biorthogonal wavelet filters. A telescopic lens combination scales the transformed fingerprint onto the filters, providing a means of adjusting the biorthogonal wavelet filter dilation continuously. The wavelet transformed fingerprint is then applied to an optical fingerprint identification process. Comparison between normal fingerprints and wavelet transformed fingerprints shows improvement in the optical identification process, in terms of rotational invariance.
Wavelet transform of neural spike trains
NASA Astrophysics Data System (ADS)
Kim, Youngtae; Jung, Min Whan; Kim, Yunbok
2000-02-01
Wavelet transform of neural spike trains recorded with a tetrode in the rat primary somatosensory cortex is described. Continuous wavelet transform (CWT) of the spike train clearly shows singularities hidden in the noisy or chaotic spike trains. A multiresolution analysis of the spike train is also carried out using discrete wavelet transform (DWT) for denoising and approximating at different time scales. Results suggest that this multiscale shape analysis can be a useful tool for classifying the spike trains.
Wavelet Analysis of Protein Motion
BENSON, NOAH C.
2014-01-01
As high-throughput molecular dynamics simulations of proteins become more common and the databases housing the results become larger and more prevalent, more sophisticated methods to quickly and accurately mine large numbers of trajectories for relevant information will have to be developed. One such method, which is only recently gaining popularity in molecular biology, is the continuous wavelet transform, which is especially well-suited for time course data such as molecular dynamics simulations. We describe techniques for the calculation and analysis of wavelet transforms of molecular dynamics trajectories in detail and present examples of how these techniques can be useful in data mining. We demonstrate that wavelets are sensitive to structural rearrangements in proteins and that they can be used to quickly detect physically relevant events. Finally, as an example of the use of this approach, we show how wavelet data mining has led to a novel hypothesis related to the mechanism of the protein γδ resolvase. PMID:25484480
Compression of echocardiographic scan line data using wavelet packet transform
NASA Technical Reports Server (NTRS)
Hang, X.; Greenberg, N. L.; Qin, J.; Thomas, J. D.
2001-01-01
An efficient compression strategy is indispensable for digital echocardiography. Previous work has suggested improved results utilizing wavelet transforms in the compression of 2D echocardiographic images. Set partitioning in hierarchical trees (SPIHT) was modified to compress echocardiographic scanline data based on the wavelet packet transform. A compression ratio of at least 94:1 resulted in preserved image quality.
Application of Hermitian wavelet to crack fault detection in gearbox
NASA Astrophysics Data System (ADS)
Li, Hui; Zhang, Yuping; Zheng, Haiqi
2011-05-01
The continuous wavelet transform enables one to look at the evolution in the time scale joint representation plane. This advantage makes it very suitable for the detection of singularity generated by localized defects in the mechanical system. However, most of the applications of the continuous wavelet transform have widely focused on the use of Morlet wavelet transform. The complex Hermitian wavelet is constructed based on the first and the second derivatives of the Gaussian function to detect signal singularities. The Fourier spectrum of Hermitian wavelet is real; therefore, Hermitian wavelet does not affect the phase of a signal in the complex domain. This gives a desirable ability to extract the singularity characteristic of a signal precisely. In this study, Hermitian wavelet is used to diagnose the gear localized crack fault. The simulative and experimental results show that Hermitian wavelet can extract the transients from strong noise signals and can effectively diagnose the localized gear fault.
Wavelet and wavelet packet compression of electrocardiograms.
Hilton, M L
1997-05-01
Wavelets and wavelet packets have recently emerged as powerful tools for signal compression. Wavelet and wavelet packet-based compression algorithms based on embedded zerotree wavelet (EZW) coding are developed for electrocardiogram (ECG) signals, and eight different wavelets are evaluated for their ability to compress Holter ECG data. Pilot data from a blind evaluation of compressed ECG's by cardiologists suggest that the clinically useful information present in original ECG signals is preserved by 8:1 compression, and in most cases 16:1 compressed ECG's are clinically useful.
Optical Wavelet Transform for Fingerprint Identification
1993-12-15
requirements of digitized fingerprints. This research implements an optical wavelet transform of a fingerprint image, as the first step in an optical... wavelet transform is implemented with continuous shift using an optical correlation between binarized fingerprints written on a Magneto-Optic Spatial
Sohrabi, Mahmoud Reza; Tayefeh Zarkesh, Mahshid
2014-05-01
In the present paper, two spectrophotometric methods based on signal processing are proposed for the simultaneous determination of two components of an anti-HIV drug called lamivudine (LMV) and zidovudine (ZDV). The proposed methods are applied to synthetic binary mixtures and commercial pharmaceutical tablets without the need for any chemical separation procedures. The developed methods are based on the application of Continuous Wavelet Transform (CWT) and Derivative Spectrophotometry (DS) combined with the zero cross point technique. The Daubechies (db5) wavelet family (242 nm) and Dmey wavelet family (236 nm) were found to give the best results under optimum conditions for simultaneous analysis of lamivudine and zidovudine, respectively. In addition, the first derivative absorption spectra were selected for the determination of lamivudine and zidovudine at 266 nm and 248 nm, respectively. Assaying various synthetic mixtures of the components validated the presented methods. Mean recovery values were found to be between 100.31% and 100.2% for CWT and 99.42% and 97.37% for DS, respectively for determination of LMV and ZDV. The results obtained from analyzing the real samples by the proposed methods were compared to the HPLC reference method. One-way ANOVA test at 95% confidence level was applied to the results. The statistical data from comparing the proposed methods with the reference method showed no significant differences.
Wavelet frames and admissibility in higher dimensions
NASA Astrophysics Data System (ADS)
Führ, Hartmut
1996-12-01
This paper is concerned with the relations between discrete and continuous wavelet transforms on k-dimensional Euclidean space. We start with the construction of continuous wavelet transforms with the help of square-integrable representations of certain semidirect products, thereby generalizing results of Bernier and Taylor. We then turn to frames of L2(Rk) and to the question, when the functions occurring in a given frame are admissible for a given continuous wavelet transform. For certain frames we give a characterization which generalizes a result of Daubechies to higher dimensions.
Perception-based reversible watermarking for 2D vector maps
NASA Astrophysics Data System (ADS)
Men, Chaoguang; Cao, Liujuan; Li, Xiang
2010-07-01
This paper presents an effective and reversible watermarking approach for digital copyright protection of 2D-vector maps. To ensure that the embedded watermark is insensitive for human perception, we only select the noise non-sensitive regions for watermark embedding by estimating vertex density within each polyline. To ensure the exact recovery of original 2D-vector map after watermark extraction, we introduce a new reversible watermarking scheme based on reversible high-frequency wavelet coefficients modification. Within the former-selected non-sensitive regions, our watermarking operates on the lower-order vertex coordinate decimals with integer wavelet transform. Such operation further reduces the visual distortion caused by watermark embedding. We have validated the effectiveness of our scheme on our real-world city river/building 2D-vector maps. We give extensive experimental comparisons with state-of-the-art methods, including embedding capability, invisibility, and robustness over watermark attacking.
Image encoding with triangulation wavelets
NASA Astrophysics Data System (ADS)
Hebert, D. J.; Kim, HyungJun
1995-09-01
We demonstrate some wavelet-based image processing applications of a class of simplicial grids arising in finite element computations and computer graphics. The cells of a triangular grid form the set of leaves of a binary tree and the nodes of a directed graph consisting of a single cycle. The leaf cycle of a uniform grid forms a pattern for pixel image scanning and for coherent computation of coefficients of splines and wavelets. A simple form of image encoding is accomplished with a 1D quadrature mirror filter whose coefficients represent an expansion of the image in terms of 2D Haar wavelets with triangular support. A combination the leaf cycle and an inherent quadtree structure allow efficient neighbor finding, grid refinement, tree pruning and storage. Pruning of the simplex tree yields a partially compressed image which requires no decoding, but rather may be rendered as a shaded triangulation. This structure and its generalization to n-dimensions form a convenient setting for wavelet analysis and computations based on simplicial grids.
Fingerprint spoof detection using wavelet based local binary pattern
NASA Astrophysics Data System (ADS)
Kumpituck, Supawan; Li, Dongju; Kunieda, Hiroaki; Isshiki, Tsuyoshi
2017-02-01
In this work, a fingerprint spoof detection method using an extended feature, namely Wavelet-based Local Binary Pattern (Wavelet-LBP) is introduced. Conventional wavelet-based methods calculate wavelet energy of sub-band images as the feature for discrimination while we propose to use Local Binary Pattern (LBP) operation to capture the local appearance of the sub-band images instead. The fingerprint image is firstly decomposed by two-dimensional discrete wavelet transform (2D-DWT), and then LBP is applied on the derived wavelet sub-band images. Furthermore, the extracted features are used to train Support Vector Machine (SVM) classifier to create the model for classifying the fingerprint images into genuine and spoof. Experiments that has been done on Fingerprint Liveness Detection Competition (LivDet) datasets show the improvement of the fingerprint spoof detection by using the proposed feature.
NASA Astrophysics Data System (ADS)
Lotsch, Bettina V.
2015-07-01
Graphene's legacy has become an integral part of today's condensed matter science and has equipped a whole generation of scientists with an armory of concepts and techniques that open up new perspectives for the postgraphene area. In particular, the judicious combination of 2D building blocks into vertical heterostructures has recently been identified as a promising route to rationally engineer complex multilayer systems and artificial solids with intriguing properties. The present review highlights recent developments in the rapidly emerging field of 2D nanoarchitectonics from a materials chemistry perspective, with a focus on the types of heterostructures available, their assembly strategies, and their emerging properties. This overview is intended to bridge the gap between two major—yet largely disjunct—developments in 2D heterostructures, which are firmly rooted in solid-state chemistry or physics. Although the underlying types of heterostructures differ with respect to their dimensions, layer alignment, and interfacial quality, there is common ground, and future synergies between the various assembly strategies are to be expected.
[Wavelet entropy analysis of spontaneous EEG signals in Alzheimer's disease].
Zhang, Meiyun; Zhang, Benshu; Chen, Ying
2014-08-01
Wavelet entropy is a quantitative index to describe the complexity of signals. Continuous wavelet transform method was employed to analyze the spontaneous electroencephalogram (EEG) signals of mild, moderate and severe Alzheimer's disease (AD) patients and normal elderly control people in this study. Wavelet power spectrums of EEG signals were calculated based on wavelet coefficients. Wavelet entropies of mild, moderate and severe AD patients were compared with those of normal controls. The correlation analysis between wavelet entropy and MMSE score was carried out. There existed significant difference on wavelet entropy among mild, moderate, severe AD patients and normal controls (P<0.01). Group comparisons showed that wavelet entropy for mild, moderate, severe AD patients was significantly lower than that for normal controls, which was related to the narrow distribution of their wavelet power spectrums. The statistical difference was significant (P<0.05). Further studies showed that the wavelet entropy of EEG and the MMSE score were significantly correlated (r= 0. 601-0. 799, P<0.01). Wavelet entropy is a quantitative indicator describing the complexity of EEG signals. Wavelet entropy is likely to be an electrophysiological index for AD diagnosis and severity assessment.
2D semiconductor optoelectronics
NASA Astrophysics Data System (ADS)
Novoselov, Kostya
The advent of graphene and related 2D materials has recently led to a new technology: heterostructures based on these atomically thin crystals. The paradigm proved itself extremely versatile and led to rapid demonstration of tunnelling diodes with negative differential resistance, tunnelling transistors, photovoltaic devices, etc. By taking the complexity and functionality of such van der Waals heterostructures to the next level we introduce quantum wells engineered with one atomic plane precision. Light emission from such quantum wells, quantum dots and polaritonic effects will be discussed.
NASA Astrophysics Data System (ADS)
Huda, Feblil; Kajiwara, Itsuro; Hosoya, Naoki
2014-08-01
In this paper, a vibration testing and health monitoring system based on an impulse response excited by laser is proposed to detect damage in membrane structures. A high power Nd: YAG pulse laser is used to supply an ideal impulse to a membrane structure by generating shock waves via laser-induced breakdown in air. A health monitoring apparatus is developed with this vibration testing system and a damage detecting algorithm which only requires the vibration mode shape of the damaged membrane. Artificial damage is induced in membrane structure by cutting and tearing the membrane. The vibration mode shapes of the membrane structure extracted from vibration testing by using the laser-induced breakdown and laser Doppler vibrometer are then analyzed by 2-D continuous wavelet transformation. The location of damage is determined by the dominant peak of the wavelet coefficient which can be seen clearly by applying a boundary treatment and the concept of an iso-surface to the 2-D wavelet coefficient. The applicability of the present approach is verified by finite element analysis and experimental results, demonstrating the ability of the method to detect and identify the positions of damage induced on the membrane structure.
NASA Astrophysics Data System (ADS)
Jones, B. J. T.
Wavelet analysis has become a major tool in many aspects of data handling, whether it be statistical analysis, noise removal or image reconstruction. Wavelet analysis has worked its way into fields as diverse as economics, medicine, geophysics, music and cosmology.
Transient Detection Using Wavelets.
1995-03-01
signaL and transients are nonstationary. A new technique for the analysis of this type of signal, called the Wavelet Transform , was applied to artificial...and real signals. A brief theoretical comparison between the Short Time Fourier Transform and the Wavelet Transform is introduced A multisolution...analysis approach for implementing the transform was used. Computer code for the Discrete Wavelet Transform was implemented. Different types of wavelets to use as basis functions were evaluated. (KAR) P. 2
Significance tests for the wavelet cross spectrum and wavelet linear coherence
NASA Astrophysics Data System (ADS)
Ge, Z.
2008-12-01
signals, nearly constant phase angles of the wavelet cross spectrum are found to coincide with large values in the wavelet linear coherence between the winds and the waves. Not limited to geophysics, the significance tests developed in the present work can also be applied to many other quantitative studies using the continuous wavelet transform.
Szu, H.; Hsu, C.
1996-12-31
Human sensors systems (HSS) may be approximately described as an adaptive or self-learning version of the Wavelet Transforms (WT) that are capable to learn from several input-output associative pairs of suitable transform mother wavelets. Such an Adaptive WT (AWT) is a redundant combination of mother wavelets to either represent or classify inputs.
Wavelet Characterizations of Multi-Directional Regularity
NASA Astrophysics Data System (ADS)
Slimane, Mourad Ben
2011-05-01
The study of d dimensional traces of functions of m several variables leads to directional behaviors. The purpose of this paper is two-fold. Firstly, we extend the notion of one direction pointwise Hölder regularity introduced by Jaffard to multi-directions. Secondly, we characterize multi-directional pointwise regularity by Triebel anisotropic wavelet coefficients (resp. leaders), and also by Calderón anisotropic continuous wavelet transform.
2D Seismic Reflection Data across Central Illinois
Smith, Valerie; Leetaru, Hannes
2014-09-30
In a continuing collaboration with the Midwest Geologic Sequestration Consortium (MGSC) on the Evaluation of the Carbon Sequestration Potential of the Cambro-Ordovician Strata of the Illinois and Michigan Basins project, Schlumberger Carbon Services and WesternGeco acquired two-dimensional (2D) seismic data in the Illinois Basin. This work included the design, acquisition and processing of approximately 125 miles of (2D) seismic reflection surveys running west to east in the central Illinois Basin. Schlumberger Carbon Services and WesternGeco oversaw the management of the field operations (including a pre-shoot planning, mobilization, acquisition and de-mobilization of the field personnel and equipment), procurement of the necessary permits to conduct the survey, post-shoot closure, processing of the raw data, and provided expert consultation as needed in the interpretation of the delivered product. Three 2D seismic lines were acquired across central Illinois during November and December 2010 and January 2011. Traversing the Illinois Basin, this 2D seismic survey was designed to image the stratigraphy of the Cambro-Ordovician sections and also to discern the basement topography. Prior to this survey, there were no regionally extensive 2D seismic data spanning this section of the Illinois Basin. Between the NW side of Morgan County and northwestern border of Douglas County, these seismic lines ran through very rural portions of the state. Starting in Morgan County, Line 101 was the longest at 93 miles in length and ended NE of Decatur, Illinois. Line 501 ran W-E from the Illinois Basin – Decatur Project (IBDP) site to northwestern Douglas County and was 25 miles in length. Line 601 was the shortest and ran N-S past the IBDP site and connected lines 101 and 501. All three lines are correlated to well logs at the IBDP site. Originally processed in 2011, the 2D seismic profiles exhibited a degradation of signal quality below ~400 millisecond (ms) which made
Wavelet analysis and scaling properties of time series
NASA Astrophysics Data System (ADS)
Manimaran, P.; Panigrahi, Prasanta K.; Parikh, Jitendra C.
2005-10-01
We propose a wavelet based method for the characterization of the scaling behavior of nonstationary time series. It makes use of the built-in ability of the wavelets for capturing the trends in a data set, in variable window sizes. Discrete wavelets from the Daubechies family are used to illustrate the efficacy of this procedure. After studying binomial multifractal time series with the present and earlier approaches of detrending for comparison, we analyze the time series of averaged spin density in the 2D Ising model at the critical temperature, along with several experimental data sets possessing multifractal behavior.
Discrete multiscale wavelet shrinkage and integrodifferential equations
NASA Astrophysics Data System (ADS)
Didas, S.; Steidl, G.; Weickert, J.
2008-04-01
We investigate the relation between discrete wavelet shrinkage and integrodifferential equations in the context of simplification and denoising of one-dimensional signals. In the continuous setting, strong connections between these two approaches were discovered in 6 (see references). The key observation is that the wavelet transform can be understood as derivative operator after the convolution with a smoothing kernel. In this paper, we extend these ideas to the practically relevant discrete setting with both orthogonal and biorthogonal wavelets. In the discrete case, the behaviour of the smoothing kernels for different scales requires additional investigation. The results of discrete multiscale wavelet shrinkage and related discrete versions of integrodifferential equations are compared with respect to their denoising quality by numerical experiments.
Optical phase distribution evaluation by using zero order Generalized Morse Wavelet
NASA Astrophysics Data System (ADS)
Kocahan, Özlem; Elmas, Merve Naz; Durmuş, ćaǧla; Coşkun, Emre; Tiryaki, Erhan; Özder, Serhat
2017-02-01
When determining the phase from the projected fringes by using continuous wavelet transform (CWT), selection of wavelet is an important step. A new wavelet for phase retrieval from the fringe pattern with the spatial carrier frequency in the x direction is presented. As a mother wavelet, zero order generalized Morse wavelet (GMW) is chosen because of the flexible spatial and frequency localization property, and it is exactly analytic. In this study, GMW method is explained and numerical simulations are carried out to show the validity of this technique for finding the phase distributions. Results for the Morlet and Paul wavelets are compared with the results of GMW analysis.
Biorthogonal wavelet-based method of moments for electromagnetic scattering
NASA Astrophysics Data System (ADS)
Zhang, Qinke
Wavelet analysis is a technique developed in recent years in mathematics and has found usefulness in signal processing and many other engineering areas. The practical use of wavelets for the solution of partial differential and integral equations in computational electromagnetics has been investigated in this dissertation, with the emphasis on development of biorthogonal wavelet based method of moments for the solution of electric and magnetic field integral equations. The fundamentals and numerical analysis aspects of wavelet theory have been studied. In particular, a family of compactly supported biorthogonal spline wavelet bases on the n-cube (0,1) n has been studied in detail. The wavelet bases were used in this work as a building block to construct biorthogonal wavelet bases on general domain geometry. A specific and practical way of adapting the wavelet bases to certain n- dimensional blocks or elements is proposed based on the domain decomposition and local transformation techniques used in traditional finite element methods and computer aided graphics. The element, with the biorthogonal wavelet base embedded in it, is called a wavelet element in this work. The physical domains which can be treated with this method include general curves, surfaces in 2D and 3D, and 3D volume domains. A two-step mapping is proposed for the purpose of taking full advantage of the zero-moments of wavelets. The wavelet element approach appears to offer several important advantages. It avoids the need of generating very complicated meshes required in traditional finite element based methods, and makes the adaptive analysis easy to implement. A specific implementation procedure for performing adaptive analysis is proposed. The proposed biorthogonal wavelet based method of moments (BWMoM) has been implemented by using object-oriented programming techniques. The main computational issues have been detailed, discussed, and implemented in the whole package. Numerical examples show
Wavelet transform: fundamentals, applications, and implementation using acousto-optic correlators
NASA Astrophysics Data System (ADS)
DeCusatis, Casimer M.; Koay, J.; Litynski, Daniel M.; Das, Pankaj K.
1995-10-01
In recent years there has been a great deal of interest in the use of wavelets to supplement or replace conventional Fourier transform signal processing. This paper provides a review of wavelet transforms for signal processing applications, and discusses several emerging applications which benefit from the advantages of wavelets. The wavelet transform can be implemented as an acousto-optic correlator; perfect reconstruction of digital signals may also be achieved using acousto-optic finite impulse response filter banks. Acousto-optic image correlators are discussed as a potential implementation of the wavelet transform, since a 1D wavelet filter bank may be encoded as a 2D image. We discuss applications of the wavelet transform including nondestructive testing of materials, biomedical applications in the analysis of EEG signals, and interference excision in spread spectrum communication systems. Computer simulations and experimental results for these applications are also provided.
E-2D Advanced Hawkeye Aircraft (E-2D AHE)
2015-12-01
Selected Acquisition Report (SAR) RCS: DD-A&T(Q&A)823-364 E-2D Advanced Hawkeye Aircraft (E-2D AHE) As of FY 2017 President’s Budget Defense...Office Estimate RDT&E - Research, Development, Test, and Evaluation SAR - Selected Acquisition Report SCP - Service Cost Position TBD - To Be Determined
Three-dimensional compression scheme based on wavelet transform
NASA Astrophysics Data System (ADS)
Yang, Wu; Xu, Hui; Liao, Mengyang
1999-03-01
In this paper, a 3D compression method based on separable wavelet transform is discussed in detail. The most commonly used digital modalities generate multiple slices in a single examination, which are normally anatomically or physiologically correlated to each other. 3D wavelet compression methods can achieve more efficient compression by exploring the correlation between slices. The first step is based on a separable 3D wavelet transform. Considering the difference between pixel distances within a slice and those between slices, one biorthogonal Antoninin filter bank is applied within 2D slices and a second biorthogonal Villa4 filter bank on the slice direction. Then, S+P transform is applied in the low-resolution wavelet components and an optimal quantizer is presented after analysis of the quantization noise. We use an optimal bit allocation algorithm, which, instead of eliminating the coefficients of high-resolution components in smooth areas, minimizes the system reconstruction distortion at a given bit-rate. Finally, to remain high coding efficiency and adapt to different properties of each component, a comprehensive entropy coding method is proposed, in which arithmetic coding method is applied in high-resolution components and adaptive Huffman coding method in low-resolution components. Our experimental results are evaluated by several image measures and our 3D wavelet compression scheme is proved to be more efficient than 2D wavelet compression.
Edge-preserving image compression using adaptive lifting wavelet transform
NASA Astrophysics Data System (ADS)
Zhang, Libao; Qiu, Bingchang
2015-07-01
In this paper, a novel 2-D adaptive lifting wavelet transform is presented. The proposed algorithm is designed to further reduce the high-frequency energy of wavelet transform, improve the image compression efficiency and preserve the edge or texture of original images more effectively. In this paper, a new optional direction set, covering the surrounding integer pixels and sub-pixels, is designed. Hence, our algorithm adapts far better to the image orientation features in local image blocks. To obtain the computationally efficient and coding performance, the complete processes of 2-D adaptive lifting wavelet transform is introduced and implemented. Compared with the traditional lifting-based wavelet transform, the adaptive directional lifting and the direction-adaptive discrete wavelet transform, the new structure reduces the high-frequency wavelet coefficients more effectively, and the texture structures of the reconstructed images are more refined and clear than that of the other methods. The peak signal-to-noise ratio and the subjective quality of the reconstructed images are significantly improved.
Reversible wavelet filter banks with side informationless spatially adaptive low-pass filters
NASA Astrophysics Data System (ADS)
Abhayaratne, Charith
2011-07-01
Wavelet transforms that have an adaptive low-pass filter are useful in applications that require the signal singularities, sharp transitions, and image edges to be left intact in the low-pass signal. In scalable image coding, the spatial resolution scalability is achieved by reconstructing the low-pass signal subband, which corresponds to the desired resolution level, and discarding other high-frequency wavelet subbands. In such applications, it is vital to have low-pass subbands that are not affected by smoothing artifacts associated with low-pass filtering. We present the mathematical framework for achieving 1-D wavelet transforms that have a spatially adaptive low-pass filter (SALP) using the prediction-first lifting scheme. The adaptivity decisions are computed using the wavelet coefficients, and no bookkeeping is required for the perfect reconstruction. Then, 2-D wavelet transforms that have a spatially adaptive low-pass filter are designed by extending the 1-D SALP framework. Because the 2-D polyphase decompositions are used in this case, the 2-D adaptivity decisions are made nonseparable as opposed to the separable 2-D realization using 1-D transforms. We present examples using the 2-D 5/3 wavelet transform and their lossless image coding and scalable decoding performances in terms of quality and resolution scalability. The proposed 2-D-SALP scheme results in better performance compared to the existing adaptive update lifting schemes.
1994-07-29
Douglas (MDA). This has been extended to the use of local SVD methods and the use of wavelet packets to provide a controlled sparsening. The goal is to be...possibilities for segmenting, compression and denoising signals and one of us (GVW) is using these wavelets to study edge sets with Prof. B. Jawerth. The
NASA Astrophysics Data System (ADS)
Abbasi Tarighat, Maryam; Nabavi, Masoume; Mohammadizadeh, Mohammad Reza
2015-06-01
A new multi-component analysis method based on zero-crossing point-continuous wavelet transformation (CWT) was developed for simultaneous spectrophotometric determination of Cu2+ and Pb2+ ions based on the complex formation with 2-benzyl espiro[isoindoline-1,5oxasolidine]-2,3,4 trione (BSIIOT). The absorption spectra were evaluated with respect to synthetic ligand concentration, time of complexation and pH. Therefore according the absorbance values, 0.015 mmol L-1 BSIIOT, 10 min after mixing and pH 8.0 were used as optimum values. The complex formation between BSIIOT ligand and the cations Cu2+ and Pb2+ by application of rank annihilation factor analysis (RAFA) were investigated. Daubechies-4 (db4), discrete Meyer (dmey), Morlet (morl) and Symlet-8 (sym8) continuous wavelet transforms for signal treatments were found to be suitable among the wavelet families. The applicability of new synthetic ligand and selected mother wavelets were used for the simultaneous determination of strongly overlapped spectra of species without using any pre-chemical treatment. Therefore, CWT signals together with zero crossing technique were directly applied to the overlapping absorption spectra of Cu2+ and Pb2+. The calibration graphs for estimation of Pb2+ and Cu 2+were obtained by measuring the CWT amplitudes at zero crossing points for Cu2+ and Pb2+ at the wavelet domain, respectively. The proposed method was validated by simultaneous determination of Cu2+ and Pb2+ ions in red beans, walnut, rice, tea and soil samples. The obtained results of samples with proposed method have been compared with those predicted by partial least squares (PLS) and flame atomic absorption spectrophotometry (FAAS).
NASA Astrophysics Data System (ADS)
Cai, De; Tan, Qiaofeng; Yan, Yingbai; Jin, Guofan; He, Qingsheng
2005-01-01
Iris, one important biometric feature, has unique advantages: it has complex texture and is almost unchanged for the lifespan. So iris recognition has been widely studied for intelligent personal identification. Most of researchers use wavelets as iris feature extractor. And their systems obtain high accuracy. But wavelet transform is time consuming, so the problem is to enhance the useful information but still keep high processing speed. This is the reason we propose an opto-electronic system for iris recognition because of high parallelism of optics. In this system, we use eigen-images generated corresponding to optimally chosen wavelet packets to compress the iris image bank. After optical correlation between eigen-images and input, the statistic features are extracted. Simulation shows that wavelet packets preprocessing of the input images results in higher identification rate. And this preprocessing can be fulfilled by optical wavelet packet transform (OWPT), a new optical transform introduced by us. To generate the approximations of 2-D wavelet packet basis functions for implementing OWPT, mother wavelet, which has scaling functions, is utilized. Using the cascade algorithm and 2-D separable wavelet transform scheme, an optical wavelet packet filter is constructed based on the selected best bases. Inserting this filter makes the recognition performance better.
3D Wavelet-Based Filter and Method
Moss, William C.; Haase, Sebastian; Sedat, John W.
2008-08-12
A 3D wavelet-based filter for visualizing and locating structural features of a user-specified linear size in 2D or 3D image data. The only input parameter is a characteristic linear size of the feature of interest, and the filter output contains only those regions that are correlated with the characteristic size, thus denoising the image.
Signal extrapolation based on wavelet representation
NASA Astrophysics Data System (ADS)
Xia, Xiang-Gen; Kuo, C.-C. Jay; Zhang, Zhen
1993-11-01
The Papoulis-Gerchberg (PG) algorithm is well known for band-limited signal extrapolation. We consider the generalization of the PG algorithm to signals in the wavelet subspaces in this research. The uniqueness of the extrapolation for continuous-time signals is examined, and sufficient conditions on signals and wavelet bases for the generalized PG (GPG) algorithm to converge are given. We also propose a discrete GPG algorithm for discrete-time signal extrapolation, and investigate its convergence. Numerical examples are given to illustrate the performance of the discrete GPG algorithm.
3D profile measurements of objects by using zero order Generalized Morse Wavelet
NASA Astrophysics Data System (ADS)
Kocahan, Özlem; Durmuş, ćaǧla; Elmas, Merve Naz; Coşkun, Emre; Tiryaki, Erhan; Özder, Serhat
2017-02-01
Generalized Morse wavelets are proposed to evaluate the phase information from projected fringe pattern with the spatial carrier frequency in the x direction. The height profile of the object is determined through the phase change distribution by using the phase of the continuous wavelet transform. The phase distribution is extracted from the optical fringe pattern choosing zero order Generalized Morse Wavelet (GMW) as a mother wavelet. In this study, standard fringe projection technique is used for obtaining images. Experimental results for the GMW phase method are compared with the results of Morlet and Paul wavelet transform.
Analysis of acceleration signals using wavelet transform.
Sekine, M; Tamura, T; Akay, M; Togawa, T; Fukui, Y
2000-06-01
In this study, we attempted to discriminate the acceleration signal for horizontal level and stairway walking using wavelet-based fractal analysis method. The acceleration signal was measured close to the center of gravity of the body, while the subjects walked continuously in the corridor and up and down the stairs. We used the wavelet-based fractal analysis method to discriminate walking pattern. The parameter H which is related directly to the fractal dimension was estimated by the wavelet coefficient and was changed into low value during walking upstairs. By manually setting the threshold level for individual, it was possible to discriminate walking upstairs from the other walking type. However, the common feature among subjects was not shown between level walking and walking downstairs.
The Discrete Wavelet Transform
1991-06-01
Split- Band Coding," Proc. ICASSP, May 1977, pp 191-195. 12. Vetterli, M. "A Theory of Multirate Filter Banks ," IEEE Trans. ASSP, 35, March 1987, pp 356...both special cases of a single filter bank structure, the discrete wavelet transform, the behavior of which is governed by one’s choice of filters . In...B-1 ,.iii FIGURES 1.1 A wavelet filter bank structure ..................................... 2 2.1 Diagram illustrating the dialation and
Wavelets and Multifractal Analysis
2004-07-01
distribution unlimited 13. SUPPLEMENTARY NOTES See also ADM001750, Wavelets and Multifractal Analysis (WAMA) Workshop held on 19-31 July 2004., The original...f)] . . . 16 2.5.4 Detrended Fluctuation Analysis [DFA(m)] . . . . . . . . . . . . . . . 17 2.6 Scale-Independent Measures...18 2.6.1 Detrended -Fluctuation- Analysis Power-Law Exponent (αD) . . . . . . 18 2.6.2 Wavelet-Transform Power-Law Exponent
Optoelectronics with 2D semiconductors
NASA Astrophysics Data System (ADS)
Mueller, Thomas
2015-03-01
Two-dimensional (2D) atomic crystals, such as graphene and layered transition-metal dichalcogenides, are currently receiving a lot of attention for applications in electronics and optoelectronics. In this talk, I will review our research activities on electrically driven light emission, photovoltaic energy conversion and photodetection in 2D semiconductors. In particular, WSe2 monolayer p-n junctions formed by electrostatic doping using a pair of split gate electrodes, type-II heterojunctions based on MoS2/WSe2 and MoS2/phosphorene van der Waals stacks, 2D multi-junction solar cells, and 3D/2D semiconductor interfaces will be presented. Upon optical illumination, conversion of light into electrical energy occurs in these devices. If an electrical current is driven, efficient electroluminescence is obtained. I will present measurements of the electrical characteristics, the optical properties, and the gate voltage dependence of the device response. In the second part of my talk, I will discuss photoconductivity studies of MoS2 field-effect transistors. We identify photovoltaic and photoconductive effects, which both show strong photoconductive gain. A model will be presented that reproduces our experimental findings, such as the dependence on optical power and gate voltage. We envision that the efficient photon conversion and light emission, combined with the advantages of 2D semiconductors, such as flexibility, high mechanical stability and low costs of production, could lead to new optoelectronic technologies.
Random seismic noise attenuation using the Wavelet Transform
NASA Astrophysics Data System (ADS)
Aliouane, L.; Ouadfeul, S.; Boudella, A.; Eladj, S.
2012-04-01
In this paper we propose a technique of random noises attenuation from seismic data using the discrete and continuous wavelet transforms. Firstly the discrete wavelet transform (DWT) is applied to denoise seismic data. This last is based on the threshold method applied at the modulus of the DWT. After we calculate the continuous wavelet transform of the denoised seismic seismogram, the final denoised seismic seismogram is the continuous wavelet transform coefficients at the low scale. Application at a synthetic seismic seismogram shows the robustness of the proposed tool for random noises attenuation. We have applied this idea at a real seismic data of a vertical seismic profile realized in Algeria. Keywords: Seismic data, denoising, DWT, CWT, random noise.
Riesz wavelets and multiresolution structures
NASA Astrophysics Data System (ADS)
Larson, David R.; Tang, Wai-Shing; Weber, Eric
2001-12-01
Multiresolution structures are important in applications, but they are also useful for analyzing properties of associated wavelets. Given a nonorthogonal (multi-) wavelet in a Hilbert space, we construct a core subspace. Subsequently, the dilates of the core subspace defines a ladder of nested subspaces. Of fundamental importance are two questions: 1) when is the core subspace shift invariant; and if yes, then 2) when is the core subspace generated by shifts of a single vector, i.e. there exists a scaling vector. If the wavelet generates a Riesz basis then the answer to question 1) is yes if and only if the wavelet is a biorthogonal wavelet. Additionally, if the wavelet generates a tight frame of arbitrary frame constant, then the core subspace is shift invariant. Question 1) is still open in case the wavelet generates a non-tight frame. We also present some known results to question 2) and provide some preliminary improvements. Our analysis here arises from investigating the dimension function and the multiplicity function of a wavelet. These two functions agree if the wavelet is orthogonal. Finally, we discuss how these questions are important for considering linear perturbation of wavelets. Utilizing the idea of the local commutant of a unitary system developed by Dai and Larson, we show that nearly all linear perturbations of two orthonormal wavelets form a Riesz wavelet. If in fact these wavelets correspond to a von Neumann algebra in the local commutant of a base wavelet, then the interpolated wavelet is biorthogonal. Moreover, we demonstrate that in this case the interpolated wavelets have a scaling vector if the base wavelet has a scaling vector.
Motion-compensated wavelet video coding using adaptive mode selection
NASA Astrophysics Data System (ADS)
Zhai, Fan; Pappas, Thrasyvoulos N.
2004-01-01
A motion-compensated wavelet video coder is presented that uses adaptive mode selection (AMS) for each macroblock (MB). The block-based motion estimation is performed in the spatial domain, and an embedded zerotree wavelet coder (EZW) is employed to encode the residue frame. In contrast to other motion-compensated wavelet video coders, where all the MBs are forced to be in INTER mode, we construct the residue frame by combining the prediction residual of the INTER MBs with the coding residual of the INTRA and INTER_ENCODE MBs. Different from INTER MBs that are not coded, the INTRA and INTER_ENCODE MBs are encoded separately by a DCT coder. By adaptively selecting the quantizers of the INTRA and INTER_ENCODE coded MBs, our goal is to equalize the characteristics of the residue frame in order to improve the overall coding efficiency of the wavelet coder. The mode selection is based on the variance of the MB, the variance of the prediction error, and the variance of the neighboring MBs' residual. Simulations show that the proposed motion-compensated wavelet video coder achieves a gain of around 0.7-0.8dB PSNR over MPEG-2 TM5, and a comparable PSNR to other 2D motion-compensated wavelet-based video codecs. It also provides potential visual quality improvement.
Highly crystalline 2D superconductors
NASA Astrophysics Data System (ADS)
Saito, Yu; Nojima, Tsutomu; Iwasa, Yoshihiro
2016-12-01
Recent advances in materials fabrication have enabled the manufacturing of ordered 2D electron systems, such as heterogeneous interfaces, atomic layers grown by molecular beam epitaxy, exfoliated thin flakes and field-effect devices. These 2D electron systems are highly crystalline, and some of them, despite their single-layer thickness, exhibit a sheet resistance more than an order of magnitude lower than that of conventional amorphous or granular thin films. In this Review, we explore recent developments in the field of highly crystalline 2D superconductors and highlight the unprecedented physical properties of these systems. In particular, we explore the quantum metallic state (or possible metallic ground state), the quantum Griffiths phase observed in out-of-plane magnetic fields and the superconducting state maintained in anomalously large in-plane magnetic fields. These phenomena are examined in the context of weakened disorder and/or broken spatial inversion symmetry. We conclude with a discussion of how these unconventional properties make highly crystalline 2D systems promising platforms for the exploration of new quantum physics and high-temperature superconductors.
Sevrin, A.
1993-06-01
After reviewing some aspects of gravity in two dimensions, I show that non-trivial embeddings of sl(2) in a semi-simple (super) Lie algebra give rise to a very large class of extensions of 2D gravity. The induced action is constructed as a gauged WZW model and an exact expression for the effective action is given.
Dependence and risk assessment for oil prices and exchange rate portfolios: A wavelet based approach
NASA Astrophysics Data System (ADS)
Aloui, Chaker; Jammazi, Rania
2015-10-01
In this article, we propose a wavelet-based approach to accommodate the stylized facts and complex structure of financial data, caused by frequent and abrupt changes of markets and noises. Specifically, we show how the combination of both continuous and discrete wavelet transforms with traditional financial models helps improve portfolio's market risk assessment. In the empirical stage, three wavelet-based models (wavelet-EGARCH with dynamic conditional correlations, wavelet-copula, and wavelet-extreme value) are considered and applied to crude oil price and US dollar exchange rate data. Our findings show that the wavelet-based approach provides an effective and powerful tool for detecting extreme moments and improving the accuracy of VaR and Expected Shortfall estimates of oil-exchange rate portfolios after noise is removed from the original data.
Steerable pyramids and tight wavelet frames in L2(R(d)).
Unser, Michael; Chenouard, Nicolas; Van de Ville, Dimitri
2011-10-01
We present a functional framework for the design of tight steerable wavelet frames in any number of dimensions. The 2-D version of the method can be viewed as a generalization of Simoncelli's steerable pyramid that gives access to a larger palette of steerable wavelets via a suitable parametrization. The backbone of our construction is a primal isotropic wavelet frame that provides the multiresolution decomposition of the signal. The steerable wavelets are obtained by applying a one-to-many mapping (Nth-order generalized Riesz transform) to the primal ones. The shaping of the steerable wavelets is controlled by an M×M unitary matrix (where M is the number of wavelet channels) that can be selected arbitrarily; this allows for a much wider range of solutions than the traditional equiangular configuration (steerable pyramid). We give a complete functional description of these generalized wavelet transforms and derive their steering equations. We describe some concrete examples of transforms, including some built around a Mallat-type multiresolution analysis of L(2)(R(d)), and provide a fast Fourier transform-based decomposition algorithm. We also propose a principal-component-based method for signal-adapted wavelet design. Finally, we present some illustrative examples together with a comparison of the denoising performance of various brands of steerable transforms. The results are in favor of an optimized wavelet design (equalized principal component analysis), which consistently performs best.
a Wavelet Model for Vocalic Speech Coarticulation
NASA Astrophysics Data System (ADS)
Lange, Robert Charles
A known aspect of human speech is that a vowel produced in isolation (for example, "ee") is acoustically different from a production of the same vowel in the company of two consonants ("deed"). This phenomenon, natural to the speech of any language, is known as consonant-vowel -consonant coarticulation. The effect of coarticulation results when a speech segment ("d") dynamically influences the articulation of an adjacent segment ("ee" within "deed"). A recent development in the theory of wavelet signal processing is wavelet system characterization. In wavelet system theory, the wavelet transform is used to describe the time-frequency behavior of a transmission channel, by virtue of its ability to describe the time -frequency content of the system's input and output signals. The present research proposes a wavelet-system model for speech coarticulation; wherein, the system is the process of transformation from a control speech state (input) to an effected speech state (output). Specifically, a vowel produced in isolation is transformed into an effected version of the same vowel produced in consonant-vowel-consonant, via the "coarticulation channel". Quantitatively, the channel is determined by the wavelet transform of the effected vowel's signal, using the control vowel's signal as the mother wavelet. A practical experiment is conducted to evaluate the coarticulation channel using samples of real speech. The results show that the model is capable of depicting coarticulation effects associated with certain vowel-consonant combinations. They suggest that elements of the vowel's acoustic composition are continuously present, in a modified form, throughout the consonant-vowel transition. For other phonetic combinations, however, the model does not respond to instances of segmental transition in a characteristic way. The conclusions drawn from the study are that the wavelet techniques employed here are effective tools for the general analysis of speech sounds, and can
Higher-order wavelet reconstruction/differentiation filters and Gibbs phenomena
NASA Astrophysics Data System (ADS)
Lombardini, Richard; Acevedo, Ramiro; Kuczala, Alexander; Keys, Kerry P.; Goodrich, Carl P.; Johnson, Bruce R.
2016-01-01
An orthogonal wavelet basis is characterized by its approximation order, which relates to the ability of the basis to represent general smooth functions on a given scale. It is known, though perhaps not widely known, that there are ways of exceeding the approximation order, i.e., achieving higher-order error in the discretized wavelet transform and its inverse. The focus here is on the development of a practical formulation to accomplish this first for 1D smooth functions, then for 1D functions with discontinuities and then for multidimensional (here 2D) functions with discontinuities. It is shown how to transcend both the wavelet approximation order and the 2D Gibbs phenomenon in representing electromagnetic fields at discontinuous dielectric interfaces that do not simply follow the wavelet-basis grid.
Wavelets on Planar Tesselations
Bertram, M.; Duchaineau, M.A.; Hamann, B.; Joy, K.I.
2000-02-25
We present a new technique for progressive approximation and compression of polygonal objects in images. Our technique uses local parameterizations defined by meshes of convex polygons in the plane. We generalize a tensor product wavelet transform to polygonal domains to perform multiresolution analysis and compression of image regions. The advantage of our technique over conventional wavelet methods is that the domain is an arbitrary tessellation rather than, for example, a uniform rectilinear grid. We expect that this technique has many applications image compression, progressive transmission, radiosity, virtual reality, and image morphing.
Dual tree fractional quaternion wavelet transform for disparity estimation.
Kumar, Sanoj; Kumar, Sanjeev; Sukavanam, Nagarajan; Raman, Balasubramanian
2014-03-01
This paper proposes a novel phase based approach for computing disparity as the optical flow from the given pair of consecutive images. A new dual tree fractional quaternion wavelet transform (FrQWT) is proposed by defining the 2D Fourier spectrum upto a single quadrant. In the proposed FrQWT, each quaternion wavelet consists of a real part (a real DWT wavelet) and three imaginary parts that are organized according to the quaternion algebra. First two FrQWT phases encode the shifts of image features in the absolute horizontal and vertical coordinate system, while the third phase has the texture information. The FrQWT allowed a multi-scale framework for calculating and adjusting local disparities and executing phase unwrapping from coarse to fine scales with linear computational efficiency.
Davis, A. B.; Petrov, N. P.; Clothiaux, E. E.; Marshak, A.
2002-01-01
Spatial and/or temporal variabilities of clouds is of paramount importance for at least two in tensely researched sub-problems in global and regional climate modeling: (1) cloud-radiation interaction where correlations can trigger 3D radiative transfer effects; and (2) dynamical cloud modeling where the goal is to realistically reproduce the said correlations. We propose wavelets as a simple yet powerful way of quantifying cloud variability. More precisely, we use 'semi-discrete' wavelet transforms which, at least in the present statistical applications, have advantages over both its continuous and discrete counterparts found in the bulk of the wavelet literature. With the particular choice of normalization we adopt, the scale-dependence of the variance of the wavelet coefficients (i.e,, the wavelet energy spectrum) is always a better discriminator of transition from 'stationary' to 'nonstationary' behavior than conventional methods based on auto-correlation analysis, second-order structure function (a.k.a. the semi-variogram), or Fourier analysis. Indeed, the classic statistics go at best from monotonically scale- or wavenumber-dependent to flat at such a transition; by contrast, the wavelet spectrum changes the sign of its derivative with respect to scale. We apply 1D and 2D semi-discrete wavelet transforms to remote sensing data on cloud structure from two sources: (1) an upward-looking milli-meter cloud radar (MMCR) at DOE's climate observation site in Oklahoma deployed as part of the Atmospheric Radiation Measurement (ARM) Progrm; and (2) DOE's Multispectral Thermal Imager (MTI), a high-resolution space-borne instrument in sunsynchronous orbit that is described in sufficient detail for our present purposes by Weber et al. (1999). For each type of data, we have at least one theoretical prediction - with empirical validation already in existence - for a power-law relation for wavelet statistics with respect to scale. This is what is expected in physical (i
Detection of microcalcifications in mammograms using wavelets
NASA Astrophysics Data System (ADS)
Strickland, Robin N.; Hahn, Hee I.
1994-10-01
Clusters of fine, granular microcalcifications in mammograms may be an early sign of disease. Individual grains are difficult to detect and segment due to size and shape variability and because the background mammogram texture is typically inhomogeneous. We present a two- stage method based on wavelet transforms for detecting and segmenting calcifications. The first stage consists of a full resolution wavelet transform, which is simply the conventional filter bank implementation without downsampling, so that all sub-bands remain at full size. Four octaves are computed with two inter-octave voices for finer scale resolution. By appropriate selection of the wavelet basis the detection of microcalcifications in the relevant size range can be nearly optimized in the details sub-bands. In fact, the separable 2D filters which transform the input image into the HH details sub-bands are closely related to pre- whitening matched filters for detecting Gaussian objects (idealized microcalcifications) in Markov noise (background noise). The second stage is designed to overcome the limitations of the simplistic Gaussian assumption and provides a useful segmentation of calcifications boundaries. Detected pixel sites in the LH, HL, and HH sub-bands are heavily weighted before computing the inverse wavelet transform. The LL component is omitted since gross spatial variations are of little interest. Individual microcalcifications are often greatly enhanced in the output image, to the point where straightforward thresholding can be applied to segment them. FROC curves are computed from tests using a well-known database of digitized mammograms. A true positive fraction of 85% is achieved at 0.5 false positives per image.
Mathematical theorems of adaptive wavelet transform
NASA Astrophysics Data System (ADS)
Szu, Harold H.; Telfer, Brian A.
1994-03-01
The computational efficiency of the adaptive wavelet transform (AWT) is due both to the compact support closely matching with signal characteristics, and to a larger redundancy factor of the superposition-mother (s(x), or in short super-mother, created adaptively by a linear superposition of other admissible mother wavelets. We prove that the super-mother always forms a complete basis, but usually associated with a higher redundancy number than its constituent C.O.N. bases. Then, in terms of Daubechies frame redundancy, we prove that the robustness of super-mother in suffering less noise contamination (since noise is everywhere, and a redundant sampling by band-passings can suppress the noise and enhance the signal). Since the continuous function of super- mother has been created with least-mean-squares (LMS) off-line using neural nets and is formulated in discrete approximation in terms of high-pass and low-pass filter bank coefficients, then such a digital subband coding via QMF saves the in-situ computational time of AWT. Moreover, the power of such an adaptive wavelet transform is due to the potential of massive parallel real-time implementation by means of artificial neural networks, where each node is a daughter wavelet similar to a radial basis function using dyadic affine scaling.
Embedded morphological dilation coding for 2D and 3D images
NASA Astrophysics Data System (ADS)
Lazzaroni, Fabio; Signoroni, Alberto; Leonardi, Riccardo
2002-01-01
Current wavelet-based image coders obtain high performance thanks to the identification and the exploitation of the statistical properties of natural images in the transformed domain. Zerotree-based algorithms, as Embedded Zerotree Wavelets (EZW) and Set Partitioning In Hierarchical Trees (SPIHT), offer high Rate-Distortion (RD) coding performance and low computational complexity by exploiting statistical dependencies among insignificant coefficients on hierarchical subband structures. Another possible approach tries to predict the clusters of significant coefficients by means of some form of morphological dilation. An example of a morphology-based coder is the Significance-Linked Connected Component Analysis (SLCCA) that has shown performance which are comparable to the zerotree-based coders but is not embedded. A new embedded bit-plane coder is proposed here based on morphological dilation of significant coefficients and context based arithmetic coding. The algorithm is able to exploit both intra-band and inter-band statistical dependencies among wavelet significant coefficients. Moreover, the same approach is used both for two and three-dimensional wavelet-based image compression. Finally we the algorithms are tested on some 2D images and on a medical volume, by comparing the RD results to those obtained with the state-of-the-art wavelet-based coders.
2D superconductivity by ionic gating
NASA Astrophysics Data System (ADS)
Iwasa, Yoshi
2D superconductivity is attracting a renewed interest due to the discoveries of new highly crystalline 2D superconductors in the past decade. Superconductivity at the oxide interfaces triggered by LaAlO3/SrTiO3 has become one of the promising routes for creation of new 2D superconductors. Also, the MBE grown metallic monolayers including FeSe are also offering a new platform of 2D superconductors. In the last two years, there appear a variety of monolayer/bilayer superconductors fabricated by CVD or mechanical exfoliation. Among these, electric field induced superconductivity by electric double layer transistor (EDLT) is a unique platform of 2D superconductivity, because of its ability of high density charge accumulation, and also because of the versatility in terms of materials, stemming from oxides to organics and layered chalcogenides. In this presentation, the following issues of electric filed induced superconductivity will be addressed; (1) Tunable carrier density, (2) Weak pinning, (3) Absence of inversion symmetry. (1) Since the sheet carrier density is quasi-continuously tunable from 0 to the order of 1014 cm-2, one is able to establish an electronic phase diagram of superconductivity, which will be compared with that of bulk superconductors. (2) The thickness of superconductivity can be estimated as 2 - 10 nm, dependent on materials, and is much smaller than the in-plane coherence length. Such a thin but low resistance at normal state results in extremely weak pinning beyond the dirty Boson model in the amorphous metallic films. (3) Due to the electric filed, the inversion symmetry is inherently broken in EDLT. This feature appears in the enhancement of Pauli limit of the upper critical field for the in-plane magnetic fields. In transition metal dichalcogenide with a substantial spin-orbit interactions, we were able to confirm the stabilization of Cooper pair due to its spin-valley locking. This work has been supported by Grant-in-Aid for Specially
Foist, Rod B; Schulze, H Georg; Ivanov, Andre; Turner, Robin F B
2011-05-01
Two-dimensional correlation spectroscopy (2D-COS) is a powerful spectral analysis technique widely used in many fields of spectroscopy because it can reveal spectral information in complex systems that is not readily evident in the original spectral data alone. However, noise may severely distort the information and thus limit the technique's usefulness. Consequently, noise reduction is often performed before implementing 2D-COS. In general, this is implemented using one-dimensional (1D) methods applied to the individual input spectra, but, because 2D-COS is based on sets of successive spectra and produces 2D outputs, there is also scope for the utilization of 2D noise-reduction methods. Furthermore, 2D noise reduction can be applied either to the original set of spectra before performing 2D-COS ("pretreatment") or on the 2D-COS output ("post-treatment"). Very little work has been done on post-treatment; hence, the relative advantages of these two approaches are unclear. In this work we compare the noise-reduction performance on 2D-COS of pretreatment and post-treatment using 1D (wavelets) and 2D algorithms (wavelets, matrix maximum entropy). The 2D methods generally outperformed the 1D method in pretreatment noise reduction. 2D post-treatment in some cases was superior to pretreatment and, unexpectedly, also provided correlation coefficient maps that were similar to 2D correlation spectroscopy maps but with apparent better contrast.
Adaptive zero-tree structure for curved wavelet image coding
NASA Astrophysics Data System (ADS)
Zhang, Liang; Wang, Demin; Vincent, André
2006-02-01
We investigate the issue of efficient data organization and representation of the curved wavelet coefficients [curved wavelet transform (WT)]. We present an adaptive zero-tree structure that exploits the cross-subband similarity of the curved wavelet transform. In the embedded zero-tree wavelet (EZW) and the set partitioning in hierarchical trees (SPIHT), the parent-child relationship is defined in such a way that a parent has four children, restricted to a square of 2×2 pixels, the parent-child relationship in the adaptive zero-tree structure varies according to the curves along which the curved WT is performed. Five child patterns were determined based on different combinations of curve orientation. A new image coder was then developed based on this adaptive zero-tree structure and the set-partitioning technique. Experimental results using synthetic and natural images showed the effectiveness of the proposed adaptive zero-tree structure for encoding of the curved wavelet coefficients. The coding gain of the proposed coder can be up to 1.2 dB in terms of peak SNR (PSNR) compared to the SPIHT coder. Subjective evaluation shows that the proposed coder preserves lines and edges better than the SPIHT coder.
NASA Astrophysics Data System (ADS)
Mortarini, Luca; Cava, Daniela; Giostra, Umberto; Anfossi, Domenico
2016-04-01
Meandering is generally defined in terms of large variation of the wind direction due to a complex mix of motions on scales between the main turbulent eddies and the smallest mesoscale motions. There is not a general consensus on the physical causes of the motions responsible of the wind meandering during low-wind speed conditions. They include internal gravity waves, quasi-2D pancake motions, cold air drainage, solitons, vortices with either a horizontal axis or a vertical axis. In this work we present the analysis of wind and temperature data measured with two sonic anemometers in a low-wind stably stratified night observed during the Urban Turbulent Project (Torino, Italy). An original approach to estimate the meandering time scales of the wind velocity and temperature using two complementary methodologies is proposed. In the literature the meandering time-scale is evaluated fitting the Eulerian auto-correlation functions of the wind velocity with an oscillating theoretical behaviour on hourly datasets. First we extend this method considering the dependence of the time-scale on the dataset length considering longer datasets (1, 2, 3, 4 hours) and then we compare these results with a wavelet analysis. The continuous wavelet transform based on the Morlet basis is used to detect and characterize the time-scale of the wavelike oscillations both in the wind velocity and in the temperature signals. Moreover cross-wavelet spectra are used to identify the nature of the wavy patterns in order to discriminate the presence of gravity waves. The wavelet analysis corroborates the results obtained with the auto-correlation functions and opens new promising perspectives for the study of the meandering phenomenon.
Multiresolution image representation using combined 2-D and 1-D directional filter banks.
Tanaka, Yuichi; Ikehara, Masaaki; Nguyen, Truong Q
2009-02-01
In this paper, effective multiresolution image representations using a combination of 2-D filter bank (FB) and directional wavelet transform (WT) are presented. The proposed methods yield simple implementation and low computation costs compared to previous 1-D and 2-D FB combinations or adaptive directional WT methods. Furthermore, they are nonredundant transforms and realize quad-tree like multiresolution representations. In applications on nonlinear approximation, image coding, and denoising, the proposed filter banks show visual quality improvements and have higher PSNR than the conventional separable WT or the contourlet.
2D quasiperiodic plasmonic crystals
Bauer, Christina; Kobiela, Georg; Giessen, Harald
2012-01-01
Nanophotonic structures with irregular symmetry, such as quasiperiodic plasmonic crystals, have gained an increasing amount of attention, in particular as potential candidates to enhance the absorption of solar cells in an angular insensitive fashion. To examine the photonic bandstructure of such systems that determines their optical properties, it is necessary to measure and model normal and oblique light interaction with plasmonic crystals. We determine the different propagation vectors and consider the interaction of all possible waveguide modes and particle plasmons in a 2D metallic photonic quasicrystal, in conjunction with the dispersion relations of a slab waveguide. Using a Fano model, we calculate the optical properties for normal and inclined light incidence. Comparing measurements of a quasiperiodic lattice to the modelled spectra for angle of incidence variation in both azimuthal and polar direction of the sample gives excellent agreement and confirms the predictive power of our model. PMID:23209871
NASA Astrophysics Data System (ADS)
Schaibley, John R.; Yu, Hongyi; Clark, Genevieve; Rivera, Pasqual; Ross, Jason S.; Seyler, Kyle L.; Yao, Wang; Xu, Xiaodong
2016-11-01
Semiconductor technology is currently based on the manipulation of electronic charge; however, electrons have additional degrees of freedom, such as spin and valley, that can be used to encode and process information. Over the past several decades, there has been significant progress in manipulating electron spin for semiconductor spintronic devices, motivated by potential spin-based information processing and storage applications. However, experimental progress towards manipulating the valley degree of freedom for potential valleytronic devices has been limited until very recently. We review the latest advances in valleytronics, which have largely been enabled by the isolation of 2D materials (such as graphene and semiconducting transition metal dichalcogenides) that host an easily accessible electronic valley degree of freedom, allowing for dynamic control.
Georgi, Howard; Kats, Yevgeny
2008-09-26
We discuss what can be learned about unparticle physics by studying simple quantum field theories in one space and one time dimension. We argue that the exactly soluble 2D theory of a massless fermion coupled to a massive vector boson, the Sommerfield model, is an interesting analog of a Banks-Zaks model, approaching a free theory at high energies and a scale-invariant theory with nontrivial anomalous dimensions at low energies. We construct a toy standard model coupling to the fermions in the Sommerfield model and study how the transition from unparticle behavior at low energies to free particle behavior at high energies manifests itself in interactions with the toy standard model particles.
NASA Astrophysics Data System (ADS)
Petrov, N. P.; Davis, A. B.
2001-12-01
Semi-discrete wavelet transforms are discrete in scale, as in Mallat's multi-resolution analysis, but continuous in position. The number of coefficients and algorithmic complexity then grows only as NlogN where N is the number of points (pixels) in the time-series (image). The redundancy of this representation at each scale has been exploited in denoising and data compression applications but we see it here as an asset when cumulating spatial statistics. Following Arnéodo, the wavelets are normalized in such a way that the scaling exponents of the moments of the coefficients are the same as for structure functions at all orders, at least in nonstationary/stationary-increment signals. We apply 1D and 2D semi-discrete transforms to remote sensing data on cloud structure from a variety of sources: NASA's MODerate Imaging Spectroradiometer (MODIS) on Terra and Thematic Mapper (TM) on LandSat; high-resolution cloud scenes from DOE's Multispectral Thermal Imager (MTI); and an upward-looking mm-radar at one of DOE's climate observation sites supporting the Atmospheric Radiation Measurement (ARM) Program. We show that the scale-dependence of the variance of the wavelet coefficients is always a better discriminator of transition from stationary to nonstationary behavior than conventional methods based on auto-correlation analysis, 2nd-order structure function (a.k.a. the semi-variogram), or spectral analysis. Examples of stationary behavior are (delta-correlated) instrumental noise and large-scale decorrelation of cloudiness; here wavelet coefficients decrease with increasing scale. Examples of nonstationary behavior are the predominant turbulent structure of cloud layers as well as instrumental or physical smoothing in the data; here wavelet coefficients increase with scale. In all of these regimes, we have theoretical expectations and/or empirical evidence of power-law relations for wavelet statistics with respect to scale as is expected in physical (finite
Quantum coherence selective 2D Raman–2D electronic spectroscopy
Spencer, Austin P.; Hutson, William O.; Harel, Elad
2017-01-01
Electronic and vibrational correlations report on the dynamics and structure of molecular species, yet revealing these correlations experimentally has proved extremely challenging. Here, we demonstrate a method that probes correlations between states within the vibrational and electronic manifold with quantum coherence selectivity. Specifically, we measure a fully coherent four-dimensional spectrum which simultaneously encodes vibrational–vibrational, electronic–vibrational and electronic–electronic interactions. By combining near-impulsive resonant and non-resonant excitation, the desired fifth-order signal of a complex organic molecule in solution is measured free of unwanted lower-order contamination. A critical feature of this method is electronic and vibrational frequency resolution, enabling isolation and assignment of individual quantum coherence pathways. The vibronic structure of the system is then revealed within an otherwise broad and featureless 2D electronic spectrum. This method is suited for studying elusive quantum effects in which electronic transitions strongly couple to phonons and vibrations, such as energy transfer in photosynthetic pigment–protein complexes. PMID:28281541
Quantum coherence selective 2D Raman-2D electronic spectroscopy
NASA Astrophysics Data System (ADS)
Spencer, Austin P.; Hutson, William O.; Harel, Elad
2017-03-01
Electronic and vibrational correlations report on the dynamics and structure of molecular species, yet revealing these correlations experimentally has proved extremely challenging. Here, we demonstrate a method that probes correlations between states within the vibrational and electronic manifold with quantum coherence selectivity. Specifically, we measure a fully coherent four-dimensional spectrum which simultaneously encodes vibrational-vibrational, electronic-vibrational and electronic-electronic interactions. By combining near-impulsive resonant and non-resonant excitation, the desired fifth-order signal of a complex organic molecule in solution is measured free of unwanted lower-order contamination. A critical feature of this method is electronic and vibrational frequency resolution, enabling isolation and assignment of individual quantum coherence pathways. The vibronic structure of the system is then revealed within an otherwise broad and featureless 2D electronic spectrum. This method is suited for studying elusive quantum effects in which electronic transitions strongly couple to phonons and vibrations, such as energy transfer in photosynthetic pigment-protein complexes.
Quantum coherence selective 2D Raman-2D electronic spectroscopy.
Spencer, Austin P; Hutson, William O; Harel, Elad
2017-03-10
Electronic and vibrational correlations report on the dynamics and structure of molecular species, yet revealing these correlations experimentally has proved extremely challenging. Here, we demonstrate a method that probes correlations between states within the vibrational and electronic manifold with quantum coherence selectivity. Specifically, we measure a fully coherent four-dimensional spectrum which simultaneously encodes vibrational-vibrational, electronic-vibrational and electronic-electronic interactions. By combining near-impulsive resonant and non-resonant excitation, the desired fifth-order signal of a complex organic molecule in solution is measured free of unwanted lower-order contamination. A critical feature of this method is electronic and vibrational frequency resolution, enabling isolation and assignment of individual quantum coherence pathways. The vibronic structure of the system is then revealed within an otherwise broad and featureless 2D electronic spectrum. This method is suited for studying elusive quantum effects in which electronic transitions strongly couple to phonons and vibrations, such as energy transfer in photosynthetic pigment-protein complexes.
Wavelet Signal Processing for Transient Feature Extraction
1992-03-15
Research was conducted to evaluate the feasibility of applying Wavelets and Wavelet Transform methods to transient signal feature extraction problems... Wavelet transform techniques were developed to extract low dimensional feature data that allowed a simple classification scheme to easily separate
The generalized Morse wavelet method to determine refractive index dispersion of dielectric films
NASA Astrophysics Data System (ADS)
Kocahan, Özlem; Özcan, Seçkin; Coşkun, Emre; Özder, Serhat
2017-04-01
The continuous wavelet transform (CWT) method is a useful tool for the determination of refractive index dispersion of dielectric films. Mother wavelet selection is an important factor for the accuracy of the results when using CWT. In this study, generalized Morse wavelet (GMW) was proposed as the mother wavelet because of having two degrees of freedom. The simulation studies, based on error calculations and Cauchy Coefficient comparisons, were presented and also the noisy signal was tested by CWT method with GMW. The experimental validity of this method was checked by D263 T schott glass having 100 μm thickness and the results were compared to those from the catalog value.
Giaddui, T; Yu, J; Xiao, Y; Jacobs, P; Manfredi, D; Linnemann, N
2015-06-15
Purpose: 2D-2D kV image guided radiation therapy (IGRT) credentialing evaluation for clinical trial qualification was historically qualitative through submitting screen captures of the fusion process. However, as quantitative DICOM 2D-2D and 2D-3D image registration tools are implemented in clinical practice for better precision, especially in centers that treat patients with protons, better IGRT credentialing techniques are needed. The aim of this work is to establish methodologies for quantitatively reviewing IGRT submissions based on DICOM 2D-2D and 2D-3D image registration and to test the methodologies in reviewing 2D-2D and 2D-3D IGRT submissions for RTOG/NRG Oncology clinical trials qualifications. Methods: DICOM 2D-2D and 2D-3D automated and manual image registration have been tested using the Harmony tool in MIM software. 2D kV orthogonal portal images are fused with the reference digital reconstructed radiographs (DRR) in the 2D-2D registration while the 2D portal images are fused with DICOM planning CT image in the 2D-3D registration. The Harmony tool allows alignment of the two images used in the registration process and also calculates the required shifts. Shifts calculated using MIM are compared with those submitted by institutions for IGRT credentialing. Reported shifts are considered to be acceptable if differences are less than 3mm. Results: Several tests have been performed on the 2D-2D and 2D-3D registration. The results indicated good agreement between submitted and calculated shifts. A workflow for reviewing these IGRT submissions has been developed and will eventually be used to review IGRT submissions. Conclusion: The IROC Philadelphia RTQA center has developed and tested a new workflow for reviewing DICOM 2D-2D and 2D-3D IGRT credentialing submissions made by different cancer clinical centers, especially proton centers. NRG Center for Innovation in Radiation Oncology (CIRO) and IROC RTQA center continue their collaborative efforts to enhance
Wavelet Preprocessing of Acoustic Signals
1991-12-01
wavelet transform to preprocess acoustic broadband signals in a system that discriminates between different classes of acoustic bursts. This is motivated by the similarity between the proportional bandwidth filters provided by the wavelet transform and those found in biological hearing systems. The experiment involves comparing statistical pattern classifier effects of wavelet and FFT preprocessed acoustic signals. The data used was from the DARPA Phase I database, which consists of artificially generated signals with real ocean background. The
2007-11-02
Daubechies-DeVore (Cohen-Daubechies-Gulleryuz-Orchard) This encoder is optimal on all Besov classes compactly embedded into L2 EZW , Said-Pearlman...DeVore (Cohen-Daubechies-Gulleryuz-Orchard) This encoder is optimal on all Besov classes compactly embedded into L2 EZW , Said-Pearlman, Cargese – p.49...Cohen-Daubechies-Gulleryuz-Orchard) This encoder is optimal on all Besov classes compactly embedded into L2 EZW , Said-Pearlman, Cargese – p.49/49 Wavelet
Wavelet phase synchronization and chaoticity.
Postnikov, E B
2009-11-01
It has been shown that the so-called "wavelet phase" (or "time-scale") synchronization of chaotic signals is actually synchronization of smoothed functions with reduced chaotic fluctuations. This fact is based on the representation of the wavelet transform with the Morlet wavelet as a solution of the Cauchy problem for a simple diffusion equation with initial condition in a form of harmonic function modulated by a given signal. The topological background of the resulting effect is discussed. It is argued that the wavelet phase synchronization provides information about the synchronization of an averaged motion described by bounding tori instead of the fine-level classical chaotic phase synchronization.
Synchrosqueezed wavelet transform for damping identification
NASA Astrophysics Data System (ADS)
Mihalec, Marko; Slavič, Janko; Boltežar, Miha
2016-12-01
Synchrosqueezing is a procedure for improving the frequency localization of a continuous wavelet transform. This research focuses on using a synchrosqueezed wavelet transform (SWT) to determine the damping ratios of a vibrating system using a free-response signal. While synchrosqueezing is advantageous due to its localisation in the frequency, damping identification with the original SWT is not sufficiently accurate. Here, the synchrosqueezing was researched in detail, and it was found that an error in the frequency occurs as a result of the numerical calculation of the preliminary frequencies. If this error were to be compensated, a better damping identification would be expected. To minimize the frequency-shift error, three different strategies are investigated: the scale-dependent coefficient method, the shifted-coefficient method and the autocorrelated-frequency method. Furthermore, to improve the SWT, two synchrosqueezing criteria are introduced: the average SWT and the proportional SWT. Finally, the proposed modifications are tested against close modes and the noise in the signals. It was numerically and experimentally confirmed that the SWT with the proportional criterion offers better frequency localization and performs better than the continuous wavelet transform when tested against noisy signals.
Perceptually Lossless Wavelet Compression
NASA Technical Reports Server (NTRS)
Watson, Andrew B.; Yang, Gloria Y.; Solomon, Joshua A.; Villasenor, John
1996-01-01
The Discrete Wavelet Transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter, which we call DWT uniform quantization noise. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2(exp -1), where r is display visual resolution in pixels/degree, and L is the wavelet level. Amplitude thresholds increase rapidly with spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from low-pass to horizontal/vertical to diagonal. We propose a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a 'perceptually lossless' quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.
Zahra, Noor e; Sevindir, Huliya A.; Aslan, Zafar; Siddiqi, A. H.
2012-07-17
The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact on the science of medical imaging and the diagnosis of disease and screening protocols. Based on our initial investigations, future directions include neurosurgical planning and improved assessment of risk for individual patients, improved assessment and strategies for the treatment of chronic pain, improved seizure localization, and improved understanding of the physiology of neurological disorders. We look ahead to these and other emerging applications as the benefits of this technology become incorporated into current and future patient care. In this chapter by applying Fourier transform and wavelet transform, analysis and denoising of one of the important biomedical signals like EEG is carried out. The presence of rhythm, template matching, and correlation is discussed by various method. Energy of EEG signal is used to detect seizure in an epileptic patient. We have also performed denoising of EEG signals by SWT.
NASA Astrophysics Data System (ADS)
Zahra, Noor e.; Sevindir, Hulya Kodal; Aslan, Zafer; Siddiqi, A. H.
2012-07-01
The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact on the science of medical imaging and the diagnosis of disease and screening protocols. Based on our initial investigations, future directions include neurosurgical planning and improved assessment of risk for individual patients, improved assessment and strategies for the treatment of chronic pain, improved seizure localization, and improved understanding of the physiology of neurological disorders. We look ahead to these and other emerging applications as the benefits of this technology become incorporated into current and future patient care. In this chapter by applying Fourier transform and wavelet transform, analysis and denoising of one of the important biomedical signals like EEG is carried out. The presence of rhythm, template matching, and correlation is discussed by various method. Energy of EEG signal is used to detect seizure in an epileptic patient. We have also performed denoising of EEG signals by SWT.
Transition to turbulence: 2D directed percolation
NASA Astrophysics Data System (ADS)
Chantry, Matthew; Tuckerman, Laurette; Barkley, Dwight
2016-11-01
The transition to turbulence in simple shear flows has been studied for well over a century, yet in the last few years has seen major leaps forward. In pipe flow, this transition shows the hallmarks of (1 + 1) D directed percolation, a universality class of continuous phase transitions. In spanwisely confined Taylor-Couette flow the same class is found, suggesting the phenomenon is generic to shear flows. However in plane Couette flow the largest simulations and experiments to-date find evidence for a discrete transition. Here we study a planar shear flow, called Waleffe flow, devoid of walls yet showing the fundamentals of planar transition to turbulence. Working with a quasi-2D yet Navier-Stokes derived model of this flow we are able to attack the (2 + 1) D transition problem. Going beyond the system sizes previously possible we find all of the required scalings of directed percolation and thus establish planar shears flow in this class.
Analyzing Planck-Like Data with Wavelets
NASA Astrophysics Data System (ADS)
Sanz, J. L.; Barreiro, R. B.; Cayón, L.; Martinez-González, E.; Ruiz, G. A.; Diaz, F. J.; Argüeso, F.; Toffolatti, L.
Basics on the continuous and discrete wavelet transform with two scales are outlined. We study maps representing anisotropies in the cosmic microwave background radiation (CMB) and the relation to the standard approach, based on the Cl's, is establised through the introduction of a wavelet spectrum. We apply this technique to small angular scale CMB map simulations of size 12.8 x 12.8 degrees and filtered with a 4'.5 Gaussian beam. This resolution resembles the experimental one expected for future high resolution experiments (e.g. the Planck mission). We consider temperature fluctuations derived from standard, open and flat-Lambda CDM models. We also introduce Gaussian noise (uniform and non-uniform) at different S/N levels and results are given regarding denoising.
Exact reconstruction with directional wavelets on the sphere
NASA Astrophysics Data System (ADS)
Wiaux, Y.; McEwen, J. D.; Vandergheynst, P.; Blanc, O.
2008-08-01
A new formalism is derived for the analysis and exact reconstruction of band-limited signals on the sphere with directional wavelets. It represents an evolution of a previously developed wavelet formalism developed by Antoine & Vandergheynst and Wiaux et al. The translations of the wavelets at any point on the sphere and their proper rotations are still defined through the continuous three-dimensional rotations. The dilations of the wavelets are directly defined in harmonic space through a new kernel dilation, which is a modification of an existing harmonic dilation. A family of factorized steerable functions with compact harmonic support which are suitable for this kernel dilation are first identified. A scale-discretized wavelet formalism is then derived, relying on this dilation. The discrete nature of the analysis scales allows the exact reconstruction of band-limited signals. A corresponding exact multi-resolution algorithm is finally described and an implementation is tested. The formalism is of interest notably for the denoising or the deconvolution of signals on the sphere with a sparse expansion in wavelets. In astrophysics, it finds a particular application for the identification of localized directional features in the cosmic microwave background data, such as the imprint of topological defects, in particular, cosmic strings, and for their reconstruction after separation from the other signal components.
The berkeley wavelet transform: a biologically inspired orthogonal wavelet transform.
Willmore, Ben; Prenger, Ryan J; Wu, Michael C-K; Gallant, Jack L
2008-06-01
We describe the Berkeley wavelet transform (BWT), a two-dimensional triadic wavelet transform. The BWT comprises four pairs of mother wavelets at four orientations. Within each pair, one wavelet has odd symmetry, and the other has even symmetry. By translation and scaling of the whole set (plus a single constant term), the wavelets form a complete, orthonormal basis in two dimensions. The BWT shares many characteristics with the receptive fields of neurons in mammalian primary visual cortex (V1). Like these receptive fields, BWT wavelets are localized in space, tuned in spatial frequency and orientation, and form a set that is approximately scale invariant. The wavelets also have spatial frequency and orientation bandwidths that are comparable with biological values. Although the classical Gabor wavelet model is a more accurate description of the receptive fields of individual V1 neurons, the BWT has some interesting advantages. It is a complete, orthonormal basis and is therefore inexpensive to compute, manipulate, and invert. These properties make the BWT useful in situations where computational power or experimental data are limited, such as estimation of the spatiotemporal receptive fields of neurons.
NASA Astrophysics Data System (ADS)
Yan, Jingwen; Chen, Jiazhen
2007-03-01
A new hyperspectral image compression method of spectral feature classification vector quantization (SFCVQ) and embedded zero-tree of wavelet (EZW) based on Karhunen-Loeve transformation (KLT) and integer wavelet transformation is represented. In comparison with the other methods, this method not only keeps the characteristics of high compression ratio and easy real-time transmission, but also has the advantage of high computation speed. After lifting based integer wavelet and SFCVQ coding are introduced, a system of nearly lossless compression of hyperspectral images is designed. KLT is used to remove the correlation of spectral redundancy as one-dimensional (1D) linear transform, and SFCVQ coding is applied to enhance compression ratio. The two-dimensional (2D) integer wavelet transformation is adopted for the decorrelation of 2D spatial redundancy. EZW coding method is applied to compress data in wavelet domain. Experimental results show that in comparison with the method of wavelet SFCVQ (WSFCVQ), the method of improved BiBlock zero tree coding (IBBZTC) and the method of feature spectral vector quantization (FSVQ), the peak signal-to-noise ratio (PSNR) of this method can enhance over 9 dB, and the total compression performance is improved greatly.
Data compression by wavelet transforms
NASA Technical Reports Server (NTRS)
Shahshahani, M.
1992-01-01
A wavelet transform algorithm is applied to image compression. It is observed that the algorithm does not suffer from the blockiness characteristic of the DCT-based algorithms at compression ratios exceeding 25:1, but the edges do not appear as sharp as they do with the latter method. Some suggestions for the improved performance of the wavelet transform method are presented.
NASA Astrophysics Data System (ADS)
Kasde, Satish Kumar; Gwal, Ashok Kumar; Sondhiya, Deepak Kumar
Abstract: To understand better the variation of solar activity indicators originated at different layers of the solar atmosphere with respect to sunspot cycles, we carried out a study of phase relationship between sunspot number and Sunspot area using cross-correlation analysis. Extended wavelet based approaches such as continuous wavelet transform (CWT), cross wavelet transform (XWT), and wavelet coherence (WTC). It gives better understanding in the physical processes responsible for the solar activity and the solar cycle phenomenon. In this study we found: short term variability for current solar cycle 24 (Jan2008 - May2013). We have observed the mid-term quasi periodicities for this solar cycle and we also investigate the correlation between both parameters and identify the unusual conditions in space weather. Key words: Wavelet analysis, Sunspot Cycle, Solar Activity.
NASA Astrophysics Data System (ADS)
Zielinski, B.; Patorski, K.
2010-06-01
The aim of this paper is to analyze 2D fringe pattern denoising performed by two chosen methods based on quasi-1D two-arm spin filter and 2D discrete wavelet transform (DWT) signal decomposition and thresholding. The ultimate aim of this comparison is to estimate which algorithm is better suited for high-accuracy measurements by phase shifting interferometry (PSI) with the phase step evaluation using the lattice site approach. The spin filtering method proposed by Yu et al. (1994) was designed to minimize possible fringe blur and distortion. The 2D DWT also presents such features due to a lossless nature of the signal wavelet decomposition. To compare both methods, a special 2D histogram introduced by Gutman and Weber (1998) is used to evaluate intensity errors introduced by each of the presented algorithms.
A generalized wavelet extrema representation
Lu, Jian; Lades, M.
1995-10-01
The wavelet extrema representation originated by Stephane Mallat is a unique framework for low-level and intermediate-level (feature) processing. In this paper, we present a new form of wavelet extrema representation generalizing Mallat`s original work. The generalized wavelet extrema representation is a feature-based multiscale representation. For a particular choice of wavelet, our scheme can be interpreted as representing a signal or image by its edges, and peaks and valleys at multiple scales. Such a representation is shown to be stable -- the original signal or image can be reconstructed with very good quality. It is further shown that a signal or image can be modeled as piecewise monotonic, with all turning points between monotonic segments given by the wavelet extrema. A new projection operator is introduced to enforce piecewise inonotonicity of a signal in its reconstruction. This leads to an enhancement to previously developed algorithms in preventing artifacts in reconstructed signal.
NASA Technical Reports Server (NTRS)
Jameson, Leland
1996-01-01
Wavelets can provide a basis set in which the basis functions are constructed by dilating and translating a fixed function known as the mother wavelet. The mother wavelet can be seen as a high pass filter in the frequency domain. The process of dilating and expanding this high-pass filter can be seen as altering the frequency range that is 'passed' or detected. The process of translation moves this high-pass filter throughout the domain, thereby providing a mechanism to detect the frequencies or scales of information at every location. This is exactly the type of information that is needed for effective grid generation. This paper provides motivation to use wavelets for grid generation in addition to providing the final product: source code for wavelet-based grid generation.
Wavelet preprocessing of acoustic signals
NASA Astrophysics Data System (ADS)
Huang, W. Y.; Solorzano, M. R.
1991-12-01
This paper describes results using the wavelet transform to preprocess acoustic broadband signals in a system that discriminates between different classes of acoustic bursts. This is motivated by the similarity between the proportional bandwidth filters provided by the wavelet transform and those found in biological hearing systems. The experiment involves comparing statistical pattern classifier effects of wavelet and FFT preprocessed acoustic signals. The data used was from the DARPA Phase 1 database, which consists of artificially generated signals with real ocean background. The results show that the wavelet transform did provide improved performance when classifying in a frame-by-frame basis. The DARPA Phase 1 database is well matched to proportional bandwidth filtering; i.e., signal classes that contain high frequencies do tend to have shorter duration in this database. It is also noted that the decreasing background levels at high frequencies compensate for the poor match of the wavelet transform for long duration (high frequency) signals.
Classification of FTIR cancer data using wavelets and BPNN
NASA Astrophysics Data System (ADS)
Cheng, Cungui; Tian, Yumei; Zhang, Changjiang
2007-11-01
In this paper, a feature extracting method based on wavelets for horizontal attenuated total reflectance Fourier transform infrared spectroscopy (HATR-FTIR) cancer data analysis and classification using artificial neural network trained with back-propagation algorithm is presented. 168 Spectra were collected from 84 pairs of fresh normal and abnormal lung tissue's samples. After preprocessing, 12 features were extracted with continuous wavelet analysis. Based on BPNN classification, all spectra were classified into two categories : normal or abnormal. The accuracy of identifying normal, early carcinoma, and advanced carcinoma were 100%, 90% and 100% respectively. This result indicated that FTIR with continuous wavelet transform (CWT) and the back-propagation neural network (BPNN) could effectively and easily diagnose lung cancer in its early stages.
NASA Astrophysics Data System (ADS)
Xu, Luopeng; Dan, Youquan; Wang, Qingyuan
2015-10-01
The continuous wavelet transform (CWT) introduces an expandable spatial and frequency window which can overcome the inferiority of localization characteristic in Fourier transform and windowed Fourier transform. The CWT method is widely applied in the non-stationary signal analysis field including optical 3D shape reconstruction with remarkable performance. In optical 3D surface measurement, the performance of CWT for optical fringe pattern phase reconstruction usually depends on the choice of wavelet function. A large kind of wavelet functions of CWT, such as Mexican Hat wavelet, Morlet wavelet, DOG wavelet, Gabor wavelet and so on, can be generated from Gauss wavelet function. However, so far, application of the Gauss wavelet transform (GWT) method (i.e. CWT with Gauss wavelet function) in optical profilometry is few reported. In this paper, the method using GWT for optical fringe pattern phase reconstruction is presented first and the comparisons between real and complex GWT methods are discussed in detail. The examples of numerical simulations are also given and analyzed. The results show that both the real GWT method along with a Hilbert transform and the complex GWT method can realize three-dimensional surface reconstruction; and the performance of reconstruction generally depends on the frequency domain appearance of Gauss wavelet functions. For the case of optical fringe pattern of large phase variation with position, the performance of real GWT is better than that of complex one due to complex Gauss series wavelets existing frequency sidelobes. Finally, the experiments are carried out and the experimental results agree well with our theoretical analysis.
NKG2D ligands as therapeutic targets
Spear, Paul; Wu, Ming-Ru; Sentman, Marie-Louise; Sentman, Charles L.
2013-01-01
The Natural Killer Group 2D (NKG2D) receptor plays an important role in protecting the host from infections and cancer. By recognizing ligands induced on infected or tumor cells, NKG2D modulates lymphocyte activation and promotes immunity to eliminate ligand-expressing cells. Because these ligands are not widely expressed on healthy adult tissue, NKG2D ligands may present a useful target for immunotherapeutic approaches in cancer. Novel therapies targeting NKG2D ligands for the treatment of cancer have shown preclinical success and are poised to enter into clinical trials. In this review, the NKG2D receptor and its ligands are discussed in the context of cancer, infection, and autoimmunity. In addition, therapies targeting NKG2D ligands in cancer are also reviewed. PMID:23833565
Wavelets and spacetime squeeze
NASA Technical Reports Server (NTRS)
Han, D.; Kim, Y. S.; Noz, Marilyn E.
1993-01-01
It is shown that the wavelet is the natural language for the Lorentz covariant description of localized light waves. A model for covariant superposition is constructed for light waves with different frequencies. It is therefore possible to construct a wave function for light waves carrying a covariant probability interpretation. It is shown that the time-energy uncertainty relation (Delta(t))(Delta(w)) is approximately 1 for light waves is a Lorentz-invariant relation. The connection between photons and localized light waves is examined critically.
All-optical image processing and compression based on Haar wavelet transform.
Parca, Giorgia; Teixeira, Pedro; Teixeira, Antonio
2013-04-20
Fast data processing and compression methods based on wavelet transform are fundamental tools in the area of real-time 2D data/image analysis, enabling high definition applications and redundant data reduction. The need for information processing at high data rates motivates the efforts on exploiting the speed and the parallelism of the light for data analysis and compression. Among several schemes for optical wavelet transform implementation, the Haar transform offers simple design and fast computation, plus it can be easily implemented by optical planar interferometry. We present an all optical scheme based on an asymmetric couplers network for achieving fast image processing and compression in the optical domain. The implementation of Haar wavelet transform through a 3D passive structure is supported by theoretical formulation and simulations results. Asymmetrical coupler 3D network design and optimization are reported and Haar wavelet transform, including compression, was achieved, thus demonstrating the feasibility of our approach.
Wavelet Packets in Wideband Multiuser Communications
2004-11-01
developed doubly orthogonal CDMA user spreading waveforms based on wavelet packets. We have also developed and evaluated a wavelet packet based ...inter symbol interferences. Compared with the existing DFT based multicarrier CDMA systems, better performance is achieved with the wavelet packet...23 3.4 Over Loaded Waveform Design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 4. Wavelet Packet Based Time-Varying
High-order wavelet reconstruction/differentiation filters and Gibbs phenomena
NASA Astrophysics Data System (ADS)
Lombardini, Richard; Acevedo, Ramiro; Kuczala, Alexander; Keys, Kerry; Goodrich, Carl; Johnson, Bruce
2016-03-01
We have developed an efficient method to accurately represent 1D or 2D, smooth or discontinuous, solutions to partial differential equations (PDE's), such as Schrodinger or Maxwell's equations, in an orthogonal Daubechies wavelet basis. This is a crucial step in the future development of a wavelet method that solves these PDE's. There are two main developments from this research. First, a reconstruction transform for smooth functions, discovered in previous works [Keinert and Kwon (1997) and Neelov and Goedecker (2006)], is generalized in order to develop a systematic way of tuning its error. This transform converts the wavelet basis representation back to the actual point values of the function. Since this reconstruction can far exceed the wavelet approximation order, it is shown that shorter wavelets can be used while maintaining a high-order accuracy resulting in an increase of computational efficiency. Second, a new ``truncated'' reconstruction transform is developed, using pieces of wavelets, or ``tail functions'', which can be applied to discontinuous functions. Not only does it avoid the wavelet Gibbs phenomenon, but also maintains a tunable accuracy similar to the smooth function case.
An Introduction to Wavelet Theory and Analysis
Miner, N.E.
1998-10-01
This report reviews the history, theory and mathematics of wavelet analysis. Examination of the Fourier Transform and Short-time Fourier Transform methods provides tiormation about the evolution of the wavelet analysis technique. This overview is intended to provide readers with a basic understanding of wavelet analysis, define common wavelet terminology and describe wavelet amdysis algorithms. The most common algorithms for performing efficient, discrete wavelet transforms for signal analysis and inverse discrete wavelet transforms for signal reconstruction are presented. This report is intended to be approachable by non- mathematicians, although a basic understanding of engineering mathematics is necessary.
PSO based Gabor wavelet feature extraction and tracking method
NASA Astrophysics Data System (ADS)
Sun, Hongguang; Bu, Qian; Zhang, Huijie
2008-12-01
The paper is the study of 2D Gabor wavelet and its application in grey image target recognition and tracking. The new optimization algorithms and technologies in the system realization are studied and discussed in theory and practice. Optimization of Gabor wavelet's parameters of translation, orientation, and scale is used to make it approximates a local image contour region. The method of Sobel edge detection is used to get the initial position and orientation value of optimization in order to improve the convergence speed. In the wavelet characteristic space, we adopt PSO (particle swarm optimization) algorithm to identify points on the security border of the system, it can ensure reliable convergence of the target, which can improve convergence speed; the time of feature extraction is shorter. By test in low contrast image, the feasibility and effectiveness of the algorithm are demonstrated by VC++ simulation platform in experiments. Adopting improve Gabor wavelet method in target tracking and making up its frame of tracking, which realize moving target tracking used algorithm, and realize steady target tracking in circumrotate affine distortion.
Wavelet-based coding of ultraspectral sounder data
NASA Astrophysics Data System (ADS)
Garcia-Vilchez, Fernando; Serra-Sagrista, Joan; Auli-Llinas, Francesc
2005-08-01
In this paper we provide a study concerning the suitability of well-known image coding techniques originally devised for lossy compression of still natural images when applied to lossless compression of ultraspectral sounder data. We present here the experimental results of six wavelet-based widespread coding techniques, namely EZW, IC, SPIHT, JPEG2000, SPECK and CCSDS-IDC. Since the considered techniques are 2-dimensional (2D) in nature but the ultraspectral data are 3D, a pre-processing stage is applied to convert the two spatial dimensions into a single spatial dimension. All the wavelet-based techniques are competitive when compared either to the benchmark prediction-based methods for lossless compression, CALIC and JPEG-LS, or to two common compression utilities, GZIP and BZIP2. EZW, SPIHT, SPECK and CCSDS-IDC provide a very similar performance, while IC and JPEG2000 improve the compression factor when compared to the other wavelet-based methods. Nevertheless, they are not competitive when compared to a fast precomputed vector quantizer. The benefits of applying a pre-processing stage, the Bias Adjusted Reordering, prior to the coding process in order to further exploit the spectral and/or spatial correlation when 2D techniques are employed, are also presented.
Wavelet Transform Signal Processing Applied to Ultrasonics.
1995-05-01
THE WAVELET TRANSFORM IS APPLIED TO THE ANALYSIS OF ULTRASONIC WAVES FOR IMPROVED SIGNAL DETECTION AND ANALYSIS OF THE SIGNALS. In instances where...the mother wavelet is well defined, the wavelet transform has relative insensitivity to noise and does not need windowing. Peak detection of...ultrasonic pulses using the wavelet transform is described and results show good detection even when large white noise was added. The use of the wavelet
Spherical 3D isotropic wavelets
NASA Astrophysics Data System (ADS)
Lanusse, F.; Rassat, A.; Starck, J.-L.
2012-04-01
Context. Future cosmological surveys will provide 3D large scale structure maps with large sky coverage, for which a 3D spherical Fourier-Bessel (SFB) analysis in spherical coordinates is natural. Wavelets are particularly well-suited to the analysis and denoising of cosmological data, but a spherical 3D isotropic wavelet transform does not currently exist to analyse spherical 3D data. Aims: The aim of this paper is to present a new formalism for a spherical 3D isotropic wavelet, i.e. one based on the SFB decomposition of a 3D field and accompany the formalism with a public code to perform wavelet transforms. Methods: We describe a new 3D isotropic spherical wavelet decomposition based on the undecimated wavelet transform (UWT) described in Starck et al. (2006). We also present a new fast discrete spherical Fourier-Bessel transform (DSFBT) based on both a discrete Bessel transform and the HEALPIX angular pixelisation scheme. We test the 3D wavelet transform and as a toy-application, apply a denoising algorithm in wavelet space to the Virgo large box cosmological simulations and find we can successfully remove noise without much loss to the large scale structure. Results: We have described a new spherical 3D isotropic wavelet transform, ideally suited to analyse and denoise future 3D spherical cosmological surveys, which uses a novel DSFBT. We illustrate its potential use for denoising using a toy model. All the algorithms presented in this paper are available for download as a public code called MRS3D at http://jstarck.free.fr/mrs3d.html
NASA Astrophysics Data System (ADS)
Le, Minh Hung; Liyana-Pathirana, Ranjith
2003-06-01
The unequal error protection (UEP) codes with wavelet-based algorithm for video compression over wide-band code division multiple access (W-CDMA), additive white Gaussian noise (AWGN) and Rayleigh fading channels are analysed. The utilization of Wavelets has come out to be a powerful method for compress video sequence. The wavelet transform compression technique has shown to be more appropriate to high quality video applications, producing better quality output for the compressed frames of video. A spatially scalable video coding framework of MPEG2 in which motion correspondences between successive video frames are exploited in the wavelet transform domain. The basic motivation for our coder is that motion fields are typically smooth that can be efficiently captured through a multiresolutional framework. Wavelet decomposition is applied to video frames and the coefficients at each level are predicted from the coarser level through backward motion compensation. The proposed algorithms of the embedded zero-tree wavelet (EZW) coder and the 2-D wavelet packet transform (2-D WPT) are investigated.
Tailoring wavelets for chaos control.
Wei, G W; Zhan, Meng; Lai, C-H
2002-12-31
Chaos is a class of ubiquitous phenomena and controlling chaos is of great interest and importance. In this Letter, we introduce wavelet controlled dynamics as a new paradigm of dynamical control. We find that by modifying a tiny fraction of the wavelet subspaces of a coupling matrix, we could dramatically enhance the transverse stability of the synchronous manifold of a chaotic system. Wavelet controlled Hopf bifurcation from chaos is observed. Our approach provides a robust strategy for controlling chaos and other dynamical systems in nature.
Peak finding using biorthogonal wavelets
Tan, C.Y.
2000-02-01
The authors show in this paper how they can find the peaks in the input data if the underlying signal is a sum of Lorentzians. In order to project the data into a space of Lorentzian like functions, they show explicitly the construction of scaling functions which look like Lorentzians. From this construction, they can calculate the biorthogonal filter coefficients for both the analysis and synthesis functions. They then compare their biorthogonal wavelets to the FBI (Federal Bureau of Investigations) wavelets when used for peak finding in noisy data. They will show that in this instance, their filters perform much better than the FBI wavelets.
Quantitative 2D liquid-state NMR.
Giraudeau, Patrick
2014-06-01
Two-dimensional (2D) liquid-state NMR has a very high potential to simultaneously determine the absolute concentration of small molecules in complex mixtures, thanks to its capacity to separate overlapping resonances. However, it suffers from two main drawbacks that probably explain its relatively late development. First, the 2D NMR signal is strongly molecule-dependent and site-dependent; second, the long duration of 2D NMR experiments prevents its general use for high-throughput quantitative applications and affects its quantitative performance. Fortunately, the last 10 years has witnessed an increasing number of contributions where quantitative approaches based on 2D NMR were developed and applied to solve real analytical issues. This review aims at presenting these recent efforts to reach a high trueness and precision in quantitative measurements by 2D NMR. After highlighting the interest of 2D NMR for quantitative analysis, the different strategies to determine the absolute concentrations from 2D NMR spectra are described and illustrated by recent applications. The last part of the manuscript concerns the recent development of fast quantitative 2D NMR approaches, aiming at reducing the experiment duration while preserving - or even increasing - the analytical performance. We hope that this comprehensive review will help readers to apprehend the current landscape of quantitative 2D NMR, as well as the perspectives that may arise from it.
Adaptive wavelet-based recognition of oscillatory patterns on electroencephalograms
NASA Astrophysics Data System (ADS)
Nazimov, Alexey I.; Pavlov, Alexey N.; Hramov, Alexander E.; Grubov, Vadim V.; Koronovskii, Alexey A.; Sitnikova, Evgenija Y.
2013-02-01
The problem of automatic recognition of specific oscillatory patterns on electroencephalograms (EEG) is addressed using the continuous wavelet-transform (CWT). A possibility of improving the quality of recognition by optimizing the choice of CWT parameters is discussed. An adaptive approach is proposed to identify sleep spindles (SS) and spike wave discharges (SWD) that assumes automatic selection of CWT-parameters reflecting the most informative features of the analyzed time-frequency structures. Advantages of the proposed technique over the standard wavelet-based approaches are considered.
Electroencephalography data analysis by using discrete wavelet packet transform
NASA Astrophysics Data System (ADS)
Karim, Samsul Ariffin Abdul; Ismail, Mohd Tahir; Hasan, Mohammad Khatim; Sulaiman, Jumat; Muthuvalu, Mohana Sundaram; Janier Josefina, B.
2015-05-01
Electroencephalography (EEG) is the electrical activity generated by the movement of neurons in the brain. It is categorized into delta waves, theta, alpha, beta and gamma. These waves exist in a different frequency band. This paper is a continuation of our previous research. EEG data will be decomposed using Discrete Wavelet Packet Transform (DWPT). Daubechies wavelets 10 (D10) will be used as the basic functions for research purposes. From the main results, it is clear that the DWPT able to characterize the EEG signal corresponding to each wave at a specific frequency. Furthermore, the numerical results obtained better than the results using DWT. Statistical analysis support our main findings.
Design of Steerable Wavelets to Detect Multifold Junctions.
Püspöki, Zsuzsanna; Uhlmann, Virginie; Vonesch, Cédric; Unser, Michael
2016-02-01
We propose a framework for the detection of junctions in images. Although the detection of edges and key points is a well examined and described area, the multiscale detection of junction centers, especially for odd orders, poses a challenge in pattern analysis. The goal of this paper is to build optimal junction detectors based on 2D steerable wavelets that are polar-separable in the Fourier domain. The approaches we develop are general and can be used for the detection of arbitrary symmetric and asymmetric junctions. The backbone of our construction is a multiscale pyramid with a radial wavelet function where the directional components are represented by circular harmonics and encoded in a shaping matrix. We are able to detect M -fold junctions in different scales and orientations. We provide experimental results on both simulated and real data to demonstrate the effectiveness of the algorithm.
NASA Astrophysics Data System (ADS)
Ren, Zhong; Liu, Guodong; Xiong, Zhihua
2016-10-01
The photoacoustic signals denoising of glucose is one of most important steps in the quality identification of the fruit because the real-time photoacoustic singals of glucose are easily interfered by all kinds of noises. To remove the noises and some useless information, an improved wavelet threshld function were proposed. Compared with the traditional wavelet hard and soft threshold functions, the improved wavelet threshold function can overcome the pseudo-oscillation effect of the denoised photoacoustic signals due to the continuity of the improved wavelet threshold function, and the error between the denoised signals and the original signals can be decreased. To validate the feasibility of the improved wavelet threshold function denoising, the denoising simulation experiments based on MATLAB programmimg were performed. In the simulation experiments, the standard test signal was used, and three different denoising methods were used and compared with the improved wavelet threshold function. The signal-to-noise ratio (SNR) and the root-mean-square error (RMSE) values were used to evaluate the performance of the improved wavelet threshold function denoising. The experimental results demonstrate that the SNR value of the improved wavelet threshold function is largest and the RMSE value is lest, which fully verifies that the improved wavelet threshold function denoising is feasible. Finally, the improved wavelet threshold function denoising was used to remove the noises of the photoacoustic signals of the glucose solutions. The denoising effect is also very good. Therefore, the improved wavelet threshold function denoising proposed by this paper, has a potential value in the field of denoising for the photoacoustic singals.
Beat to beat wavelet variability in atrial fibrillation.
Filos, D; Chouvarda, I; Dakos, G; Vassilikos, V; Maglaveras, N
2011-01-01
Atrial fibrillation (AF) is a complex phenomenon, related with a multitude of factors, including the electrical properties of the atrial substrate. The purpose of this work is to present a method that highlights electrocardiographic differences between normal subjects and patients with paroxysmal AF episodes (PAF), potentially related with substrate differences. Vectorcardiography recordings are considered and, for each lead (X-Y-Z), on a beat by beat basis, a steady window before QRS, corresponding to the atrial activity, is analysed via continuous wavelet transform. Wavelet-based parameters are calculated and compared between the normal and AF group, with the beat to beat variation of wavelet energy as the most important feature showing a significantly higher variability in the AF group.
Birdsong Denoising Using Wavelets
Priyadarshani, Nirosha; Marsland, Stephen; Castro, Isabel; Punchihewa, Amal
2016-01-01
Automatic recording of birdsong is becoming the preferred way to monitor and quantify bird populations worldwide. Programmable recorders allow recordings to be obtained at all times of day and year for extended periods of time. Consequently, there is a critical need for robust automated birdsong recognition. One prominent obstacle to achieving this is low signal to noise ratio in unattended recordings. Field recordings are often very noisy: birdsong is only one component in a recording, which also includes noise from the environment (such as wind and rain), other animals (including insects), and human-related activities, as well as noise from the recorder itself. We describe a method of denoising using a combination of the wavelet packet decomposition and band-pass or low-pass filtering, and present experiments that demonstrate an order of magnitude improvement in noise reduction over natural noisy bird recordings. PMID:26812391
Wavelet theory and its applications
Faber, V.; Bradley, JJ.; Brislawn, C.; Dougherty, R.; Hawrylycz, M.
1996-07-01
This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). We investigated the theory of wavelet transforms and their relation to Laboratory applications. The investigators have had considerable success in the past applying wavelet techniques to the numerical solution of optimal control problems for distributed- parameter systems, nonlinear signal estimation, and compression of digital imagery and multidimensional data. Wavelet theory involves ideas from the fields of harmonic analysis, numerical linear algebra, digital signal processing, approximation theory, and numerical analysis, and the new computational tools arising from wavelet theory are proving to be ideal for many Laboratory applications. 10 refs.
Wavelet entropy of stochastic processes
NASA Astrophysics Data System (ADS)
Zunino, L.; Pérez, D. G.; Garavaglia, M.; Rosso, O. A.
2007-06-01
We compare two different definitions for the wavelet entropy associated to stochastic processes. The first one, the normalized total wavelet entropy (NTWS) family [S. Blanco, A. Figliola, R.Q. Quiroga, O.A. Rosso, E. Serrano, Time-frequency analysis of electroencephalogram series, III. Wavelet packets and information cost function, Phys. Rev. E 57 (1998) 932-940; O.A. Rosso, S. Blanco, J. Yordanova, V. Kolev, A. Figliola, M. Schürmann, E. Başar, Wavelet entropy: a new tool for analysis of short duration brain electrical signals, J. Neurosci. Method 105 (2001) 65-75] and a second introduced by Tavares and Lucena [Physica A 357(1) (2005) 71-78]. In order to understand their advantages and disadvantages, exact results obtained for fractional Gaussian noise ( -1<α< 1) and fractional Brownian motion ( 1<α< 3) are assessed. We find out that the NTWS family performs better as a characterization method for these stochastic processes.
A new fractional wavelet transform
NASA Astrophysics Data System (ADS)
Dai, Hongzhe; Zheng, Zhibao; Wang, Wei
2017-03-01
The fractional Fourier transform (FRFT) is a potent tool to analyze the time-varying signal. However, it fails in locating the fractional Fourier domain (FRFD)-frequency contents which is required in some applications. A novel fractional wavelet transform (FRWT) is proposed to solve this problem. It displays the time and FRFD-frequency information jointly in the time-FRFD-frequency plane. The definition, basic properties, inverse transform and reproducing kernel of the proposed FRWT are considered. It has been shown that an FRWT with proper order corresponds to the classical wavelet transform (WT). The multiresolution analysis (MRA) associated with the developed FRWT, together with the construction of the orthogonal fractional wavelets are also presented. Three applications are discussed: the analysis of signal with time-varying frequency content, the FRFD spectrum estimation of signals that involving noise, and the construction of fractional Harr wavelet. Simulations verify the validity of the proposed FRWT.
A wavelet phase filter for emission tomography
Olsen, E.T.; Lin, B.
1995-07-01
The presence of a high level of noise is a characteristic in some tomographic imaging techniques such as positron emission tomography (PET). Wavelet methods can smooth out noise while preserving significant features of images. Mallat et al. proposed a wavelet based denoising scheme exploiting wavelet modulus maxima, but the scheme is sensitive to noise. In this study, the authors explore the properties of wavelet phase, with a focus on reconstruction of emission tomography images. Specifically, they show that the wavelet phase of regular Poisson noise under a Haar-type wavelet transform converges in distribution to a random variable uniformly distributed on [0, 2{pi}). They then propose three wavelet-phase-based denoising schemes which exploit this property: edge tracking, local phase variance thresholding, and scale phase variation thresholding. Some numerical results are also presented. The numerical experiments indicate that wavelet phase techniques show promise for wavelet based denoising methods.
Gearbox Fault Diagnosis Using Adaptive Wavelet Filter
NASA Astrophysics Data System (ADS)
LIN, J.; ZUO, M. J.
2003-11-01
Vibration signals from a gearbox are usually noisy. As a result, it is difficult to find early symptoms of a potential failure in a gearbox. Wavelet transform is a powerful tool to disclose transient information in signals. An adaptive wavelet filter based on Morlet wavelet is introduced in this paper. The parameters in the Morlet wavelet function are optimised based on the kurtosis maximisation principle. The wavelet used is adaptive because the parameters are not fixed. The adaptive wavelet filter is found to be very effective in detection of symptoms from vibration signals of a gearbox with early fatigue tooth crack. Two types of discrete wavelet transform (DWT), the decimated with DB4 wavelet and the undecimated with harmonic wavelet, are also used to analyse the same signals for comparison. No periodic impulses appear on any scale in either DWT decomposition.
Annotated Bibliography of EDGE2D Use
J.D. Strachan and G. Corrigan
2005-06-24
This annotated bibliography is intended to help EDGE2D users, and particularly new users, find existing published literature that has used EDGE2D. Our idea is that a person can find existing studies which may relate to his intended use, as well as gain ideas about other possible applications by scanning the attached tables.
Staring 2-D hadamard transform spectral imager
Gentry, Stephen M.; Wehlburg, Christine M.; Wehlburg, Joseph C.; Smith, Mark W.; Smith, Jody L.
2006-02-07
A staring imaging system inputs a 2D spatial image containing multi-frequency spectral information. This image is encoded in one dimension of the image with a cyclic Hadamarid S-matrix. The resulting image is detecting with a spatial 2D detector; and a computer applies a Hadamard transform to recover the encoded image.
Heart Disease Detection Using Wavelets
NASA Astrophysics Data System (ADS)
González S., A.; Acosta P., J. L.; Sandoval M., M.
2004-09-01
We develop a wavelet based method to obtain standardized gray-scale chart of both healthy hearts and of hearts suffering left ventricular hypertrophy. The hypothesis that early bad functioning of heart can be detected must be tested by comparing the wavelet analysis of the corresponding ECD with the limit cases. Several important parameters shall be taken into account such as age, sex and electrolytic changes.
NASA Astrophysics Data System (ADS)
Tiryaki, Erhan; Coşkun, Emre; Kocahan, Özlem; Özder, Serhat
2017-02-01
In this work, the Continuous Wavelet Transform (CWT) with Paul wavelet was improved as a tool for determination of refractive index dispersion of dielectric film by using the reflectance spectrum of the film. The reflectance spectrum was generated theoretically in the range of 0.8333 - 3.3333 μm wavenumber and it was analyzed with presented method. Obtained refractive index determined from various resolution of Paul wavelet were compared with the input values, and the importance of the tunable resolution with Paul wavelet was discussed briefly. The noise immunity and uncertainty of the method was also studied.
''Super 2D,'' Innovative seismic reprocessing: A case history
Conne, D.K.M.; Bolander, A.G.; MacDonald, R.J.; Strelioff, D.M.
1988-01-01
The ''Super 2D'' processing sequence involves taking a randomly oriented grid of multivintage two-dimensional seismic data and reprocessing to tie the data where required, then interpolating the data set to a regular grid suitable for three-dimensional processing and interpretation. A data set from Alberta, provided by a Canadian oil company, comprises 15 two-dimensional seismic lines collected and processed over a period of 6 years by various contractors. Field conditions, advances in technology, and changing objectives combined to result in a data set that densely sampled a small area, but did not tie in well enough to be interpreted as a whole. The data mistied in time, phase, and frequency, as well as having a problem with multiples in the zone of interest that had been partly attenuated in varying degrees. Therefore, the first objective of reprocessing was to resolve these problems. The authors' current land data processing sequence, which includes frequency balancing followed by source wavelet designature, F/K multiple attenuation, trim statics, and F-X filtering, as well as close attention to statics and velocity control, resolved all the mistie issues and produced a standardized data volume. This data volume was now suitable for the second stage of this sequence (i.e., interpolating to a regular grid and subsequent three-dimensional processing). The volume was three-dimensionally migrated (finite difference), filtered, and scaled. The full range of three-dimensional display and interpretational options, including loading on an interactive system, are now possible. This, along with standardizing the data set and improving the spatial location of events via three-dimensional migration are the key results of the ''Super 2D'' sequence.
NASA Astrophysics Data System (ADS)
Loussifi, Hichem; Nouri, Khaled; Benhadj Braiek, Naceur
2016-03-01
In this paper a hybrid computational intelligent approach of combining kernel methods with wavelet Multi-resolution Analysis (MRA) is presented for fuzzy wavelet network construction and initialization. Mother wavelets are used as activation functions for the neural network structure, and as kernel functions in the machine learning process. By choosing precise values of scale parameters based on the windowed scalogram representation of the Continuous Wavelet Transform (CWT), a set of kernel parameters is taken to construct the proposed Wavelet Kernel based Fuzzy Neural Network (WK-FNN) with an efficient initialization technique based on the use of wavelet kernels in Support Vector Machine for Regression (SVMR). Simulation examples are given to test usability and effectiveness of the proposed hybrid intelligent method in the system identification of dynamic plants and in the prediction of a chaotic time series. It is seen that the proposed WK-FNN achieves higher accuracy and has good performance as compared to other methods.
Wavelet analysis of Snow course data within the Sierra Nevada Mountains
NASA Astrophysics Data System (ADS)
Rios, T.; Dracup, J. A.
2003-12-01
In recent years, an analytical method known as wavelet analysis has received increasing applications in geophysical fields (Foufoula-Georgiou and Kumar 1994). Wavelet analysis can be used to identify the time and frequency regime in data while still maintaining the time coordinate. By applying the wavelet analysis method to the Mount Shasta snow course for the time period from 1937-1997 using the continuous 1-D wavelet toolbox in MATLAB, we found that several frequency regimes are present within the signal. The inter-annual noise dominates the frequency regime below the seven-year scale, but there is a relatively consistent 9-13 year oscillation that is present within the snow data. This frequency regime is also observed to shift to lower scales as the time series progresses, possibly indicating a shift in the climate variability due to climate change. In addition, analyses of the depth and the water content data exhibit nearly identical wavelet images. We are currently in the process of identifying other climate variables that may exhibit similar periodicity with the continuous 1-D wavelet analysis, such as the PDO and ENSO. Preliminary results show that by analyzing the hydrologic variables of the Sierra Nevada snowpack depth and/or water content using the wavelet method, we may be able to provide useful insights into the synergy and expression of climate change and variability within the California Sierra Nevadas.
Ginsparg, P.
1991-01-01
These are introductory lectures for a general audience that give an overview of the subject of matrix models and their application to random surfaces, 2d gravity, and string theory. They are intentionally 1.5 years out of date.
Ginsparg, P.
1991-12-31
These are introductory lectures for a general audience that give an overview of the subject of matrix models and their application to random surfaces, 2d gravity, and string theory. They are intentionally 1.5 years out of date.
Brittle damage models in DYNA2D
Faux, D.R.
1997-09-01
DYNA2D is an explicit Lagrangian finite element code used to model dynamic events where stress wave interactions influence the overall response of the system. DYNA2D is often used to model penetration problems involving ductile-to-ductile impacts; however, with the advent of the use of ceramics in the armor-anti-armor community and the need to model damage to laser optics components, good brittle damage models are now needed in DYNA2D. This report will detail the implementation of four brittle damage models in DYNA2D, three scalar damage models and one tensor damage model. These new brittle damage models are then used to predict experimental results from three distinctly different glass damage problems.
NASA Astrophysics Data System (ADS)
Dekker, T.; de Zwart, S. T.; Willemsen, O. H.; Hiddink, M. G. H.; IJzerman, W. L.
2006-02-01
A prerequisite for a wide market acceptance of 3D displays is the ability to switch between 3D and full resolution 2D. In this paper we present a robust and cost effective concept for an auto-stereoscopic switchable 2D/3D display. The display is based on an LCD panel, equipped with switchable LC-filled lenticular lenses. We will discuss 3D image quality, with the focus on display uniformity. We show that slanting the lenticulars in combination with a good lens design can minimize non-uniformities in our 20" 2D/3D monitors. Furthermore, we introduce fractional viewing systems as a very robust concept to further improve uniformity in the case slanting the lenticulars and optimizing the lens design are not sufficient. We will discuss measurements and numerical simulations of the key optical characteristics of this display. Finally, we discuss 2D image quality, the switching characteristics and the residual lens effect.
2-d Finite Element Code Postprocessor
Sanford, L. A.; Hallquist, J. O.
1996-07-15
ORION is an interactive program that serves as a postprocessor for the analysis programs NIKE2D, DYNA2D, TOPAZ2D, and CHEMICAL TOPAZ2D. ORION reads binary plot files generated by the two-dimensional finite element codes currently used by the Methods Development Group at LLNL. Contour and color fringe plots of a large number of quantities may be displayed on meshes consisting of triangular and quadrilateral elements. ORION can compute strain measures, interface pressures along slide lines, reaction forces along constrained boundaries, and momentum. ORION has been applied to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.
Chemical Approaches to 2D Materials.
Samorì, Paolo; Palermo, Vincenzo; Feng, Xinliang
2016-08-01
Chemistry plays an ever-increasing role in the production, functionalization, processing and applications of graphene and other 2D materials. This special issue highlights a selection of enlightening chemical approaches to 2D materials, which nicely reflect the breadth of the field and convey the excitement of the individuals involved in it, who are trying to translate graphene and related materials from the laboratory into a real, high-impact technology.
Wavelet-Based Multiresolution Analyses of Signals
1992-06-01
classification. Some signals, notably those of a transient nature, are inherently difficult to analyze with these traditional tools. The Discrete Wavelet Transform has...scales. This thesis investigates dyadic discrete wavelet decompositions of signals. A new multiphase wavelet transform is proposed and investigated. The
Adaptive directional lifting-based wavelet transform for image coding.
Ding, Wenpeng; Wu, Feng; Wu, Xiaolin; Li, Shipeng; Li, Houqiang
2007-02-01
We present a novel 2-D wavelet transform scheme of adaptive directional lifting (ADL) in image coding. Instead of alternately applying horizontal and vertical lifting, as in present practice, ADL performs lifting-based prediction in local windows in the direction of high pixel correlation. Hence, it adapts far better to the image orientation features in local windows. The ADL transform is achieved by existing 1-D wavelets and is seamlessly integrated into the global wavelet transform. The predicting and updating signals of ADL can be derived even at the fractional pixel precision level to achieve high directional resolution, while still maintaining perfect reconstruction. To enhance the ADL performance, a rate-distortion optimized directional segmentation scheme is also proposed to form and code a hierarchical image partition adapting to local features. Experimental results show that the proposed ADL-based image coding technique outperforms JPEG 2000 in both PSNR and visual quality, with the improvement up to 2.0 dB on images with rich orientation features.
VHDL implementation of wavelet packet transforms using SIMULINK tools
NASA Astrophysics Data System (ADS)
Shirvaikar, Mukul; Bushnaq, Tariq
2008-02-01
The wavelet transform is currently being used in many engineering fields. The real-time implementation of the Discrete Wavelet Transform (DWT) is a current area of research as it is one of the most time consuming steps in the JPEG2000 standard. The standard implements two different wavelet transforms: irreversible and reversible Daubechies. The former is a lossy transform, whereas the latter is a lossless transform. Many current JPEG2000 implementations are software-based and not efficient enough to meet real-time deadlines. Field Programmable Gate Arrays (FPGAs) are revolutionizing image and signal processing. Many major FPGA vendors like Altera and Xilinx have recently developed SIMULINK tools to support their FPGAs. These tools are intended to provide a seamless path from system-level algorithm design to FPGA implementation. In this paper, we investigate FPGA implementation of 2-D lifting-based Daubechies 9/7 and Daubechies 5/3 transforms using a Matlab/Simulink tool that generates synthesizable VHSIC Hardware Description Language (VHDL) code. The goal is to study the feasibility of this approach for real time image processing by comparing the performance of the high-level toolbox with a handwritten VHDL implementation. The hardware platform used is an Altera DE2 board with a 50MHz Cyclone II FPGA chip and the Simulink tool chosen is DSPBuilder by Altera.
NKG2D ligands mediate immunosurveillance of senescent cells
Moshayev, Zhana; Vadai, Ezra; Wensveen, Felix; Ben-Dor, Shifra; Golani, Ofra; Polic, Bojan; Krizhanovsky, Valery
2016-01-01
Cellular senescence is a stress response mechanism that limits tumorigenesis and tissue damage. Induction of cellular senescence commonly coincides with an immunogenic phenotype that promotes self-elimination by components of the immune system, thereby facilitating tumor suppression and limiting excess fibrosis during wound repair. The mechanisms by which senescent cells regulate their immune surveillance are not completely understood. Here we show that ligands of an activating Natural Killer (NK) cell receptor (NKG2D), MICA and ULBP2 are consistently up-regulated following induction of replicative senescence, oncogene-induced senescence and DNA damage - induced senescence. MICA and ULBP2 proteins are necessary for efficient NK-mediated cytotoxicity towards senescent fibroblasts. The mechanisms regulating the initial expression of NKG2D ligands in senescent cells are dependent on a DNA damage response, whilst continuous expression of these ligands is regulated by the ERK signaling pathway. In liver fibrosis, the accumulation of senescent activated stellate cells is increased in mice lacking NKG2D receptor leading to increased fibrosis. Overall, our results provide new insights into the mechanisms regulating the expression of immune ligands in senescent cells and reveal the importance of NKG2D receptor-ligand interaction in protecting against liver fibrosis. PMID:26878797
Davis, A.B.; Clothiaux, E.
1999-03-01
Because of Earth`s gravitational field, its atmosphere is strongly anisotropic with respect to the vertical; the effect of the Earth`s rotation on synoptic wind patterns also causes a more subtle form of anisotropy in the horizontal plane. The authors survey various approaches to statistically robust anisotropy from a wavelet perspective and present a new one adapted to strongly non-isotropic fields that are sampled on a rectangular grid with a large aspect ratio. This novel technique uses an anisotropic version of Multi-Resolution Analysis (MRA) in image analysis; the authors form a tensor product of the standard dyadic Haar basis, where the dividing ratio is {lambda}{sub z} = 2, and a nonstandard triadic counterpart, where the dividing ratio is {lambda}{sub x} = 3. The natural support of the field is therefore 2{sup n} pixels (vertically) by 3{sup n} pixels (horizontally) where n is the number of levels in the MRA. The natural triadic basis includes the French top-hat wavelet which resonates with bumps in the field whereas the Haar wavelet responds to ramps or steps. The complete 2D basis has one scaling function and five wavelets. The resulting anisotropic MRA is designed for application to the liquid water content (LWC) field in boundary-layer clouds, as the prevailing wind advects them by a vertically pointing mm-radar system. Spatial correlations are notoriously long-range in cloud structure and the authors use the wavelet coefficients from the new MRA to characterize these correlations in a multifractal analysis scheme. In the present study, the MRA is used (in synthesis mode) to generate fields that mimic cloud structure quite realistically although only a few parameters are used to control the randomness of the LWC`s wavelet coefficients.
Recent advances in wavelet technology
NASA Technical Reports Server (NTRS)
Wells, R. O., Jr.
1994-01-01
Wavelet research has been developing rapidly over the past five years, and in particular in the academic world there has been significant activity at numerous universities. In the industrial world, there has been developments at Aware, Inc., Lockheed, Martin-Marietta, TRW, Kodak, Exxon, and many others. The government agencies supporting wavelet research and development include ARPA, ONR, AFOSR, NASA, and many other agencies. The recent literature in the past five years includes a recent book which is an index of citations in the past decade on this subject, and it contains over 1,000 references and abstracts.
Image Segmentation Using Affine Wavelets
1991-12-12
Fourier Transform [23:677] ........ .. 3-15 3.6. Typical Wavelet Function and its Fourier Transform [23:577] ............ 3-16 3.7. Orientation of...Wavelet Decomposition Filters ii the Fourier Dcmain [14:65] 3-18 4.1. Datafiow- Diagram of the Wa’velet Decompossii ’n Proga, F.r..t cvc.. A -•A 4.2...global spatial relationships, as does a Fourier transforn."[l 1] The main thrust of Daugman’s article [11] was to show the utility of a neural network
Wavelet filtering of chaotic data
NASA Astrophysics Data System (ADS)
Grzesiak, M.
Satisfactory method of removing noise from experimental chaotic data is still an open problem. Normally it is necessary to assume certain properties of the noise and dynamics, which one wants to extract, from time series. The wavelet based method of denoising of time series originating from low-dimensional dynamical systems and polluted by the Gaussian white noise is considered. Its efficiency is investigated by comparing the correlation dimension of clean and noisy data generated for some well-known dynamical systems. The wavelet method is contrasted with the singular value decomposition (SVD) and finite impulse response (FIR) filter methods.
Orthotropic Piezoelectricity in 2D Nanocellulose
NASA Astrophysics Data System (ADS)
García, Y.; Ruiz-Blanco, Yasser B.; Marrero-Ponce, Yovani; Sotomayor-Torres, C. M.
2016-10-01
The control of electromechanical responses within bonding regions is essential to face frontier challenges in nanotechnologies, such as molecular electronics and biotechnology. Here, we present Iβ-nanocellulose as a potentially new orthotropic 2D piezoelectric crystal. The predicted in-layer piezoelectricity is originated on a sui-generis hydrogen bonds pattern. Upon this fact and by using a combination of ab-initio and ad-hoc models, we introduce a description of electrical profiles along chemical bonds. Such developments lead to obtain a rationale for modelling the extended piezoelectric effect originated within bond scales. The order of magnitude estimated for the 2D Iβ-nanocellulose piezoelectric response, ~pm V‑1, ranks this material at the level of currently used piezoelectric energy generators and new artificial 2D designs. Such finding would be crucial for developing alternative materials to drive emerging nanotechnologies.
Orthotropic Piezoelectricity in 2D Nanocellulose
García, Y.; Ruiz-Blanco, Yasser B.; Marrero-Ponce, Yovani; Sotomayor-Torres, C. M.
2016-01-01
The control of electromechanical responses within bonding regions is essential to face frontier challenges in nanotechnologies, such as molecular electronics and biotechnology. Here, we present Iβ-nanocellulose as a potentially new orthotropic 2D piezoelectric crystal. The predicted in-layer piezoelectricity is originated on a sui-generis hydrogen bonds pattern. Upon this fact and by using a combination of ab-initio and ad-hoc models, we introduce a description of electrical profiles along chemical bonds. Such developments lead to obtain a rationale for modelling the extended piezoelectric effect originated within bond scales. The order of magnitude estimated for the 2D Iβ-nanocellulose piezoelectric response, ~pm V−1, ranks this material at the level of currently used piezoelectric energy generators and new artificial 2D designs. Such finding would be crucial for developing alternative materials to drive emerging nanotechnologies. PMID:27708364
Orthotropic Piezoelectricity in 2D Nanocellulose.
García, Y; Ruiz-Blanco, Yasser B; Marrero-Ponce, Yovani; Sotomayor-Torres, C M
2016-10-06
The control of electromechanical responses within bonding regions is essential to face frontier challenges in nanotechnologies, such as molecular electronics and biotechnology. Here, we present Iβ-nanocellulose as a potentially new orthotropic 2D piezoelectric crystal. The predicted in-layer piezoelectricity is originated on a sui-generis hydrogen bonds pattern. Upon this fact and by using a combination of ab-initio and ad-hoc models, we introduce a description of electrical profiles along chemical bonds. Such developments lead to obtain a rationale for modelling the extended piezoelectric effect originated within bond scales. The order of magnitude estimated for the 2D Iβ-nanocellulose piezoelectric response, ~pm V(-1), ranks this material at the level of currently used piezoelectric energy generators and new artificial 2D designs. Such finding would be crucial for developing alternative materials to drive emerging nanotechnologies.
2D microwave imaging reflectometer electronics
Spear, A. G.; Domier, C. W. Hu, X.; Muscatello, C. M.; Ren, X.; Luhmann, N. C.; Tobias, B. J.
2014-11-15
A 2D microwave imaging reflectometer system has been developed to visualize electron density fluctuations on the DIII-D tokamak. Simultaneously illuminated at four probe frequencies, large aperture optics image reflections from four density-dependent cutoff surfaces in the plasma over an extended region of the DIII-D plasma. Localized density fluctuations in the vicinity of the plasma cutoff surfaces modulate the plasma reflections, yielding a 2D image of electron density fluctuations. Details are presented of the receiver down conversion electronics that generate the in-phase (I) and quadrature (Q) reflectometer signals from which 2D density fluctuation data are obtained. Also presented are details on the control system and backplane used to manage the electronics as well as an introduction to the computer based control program.
Large Area Synthesis of 2D Materials
NASA Astrophysics Data System (ADS)
Vogel, Eric
Transition metal dichalcogenides (TMDs) have generated significant interest for numerous applications including sensors, flexible electronics, heterostructures and optoelectronics due to their interesting, thickness-dependent properties. Despite recent progress, the synthesis of high-quality and highly uniform TMDs on a large scale is still a challenge. In this talk, synthesis routes for WSe2 and MoS2 that achieve monolayer thickness uniformity across large area substrates with electrical properties equivalent to geological crystals will be described. Controlled doping of 2D semiconductors is also critically required. However, methods established for conventional semiconductors, such as ion implantation, are not easily applicable to 2D materials because of their atomically thin structure. Redox-active molecular dopants will be demonstrated which provide large changes in carrier density and workfunction through the choice of dopant, treatment time, and the solution concentration. Finally, several applications of these large-area, uniform 2D materials will be described including heterostructures, biosensors and strain sensors.
2D microwave imaging reflectometer electronics.
Spear, A G; Domier, C W; Hu, X; Muscatello, C M; Ren, X; Tobias, B J; Luhmann, N C
2014-11-01
A 2D microwave imaging reflectometer system has been developed to visualize electron density fluctuations on the DIII-D tokamak. Simultaneously illuminated at four probe frequencies, large aperture optics image reflections from four density-dependent cutoff surfaces in the plasma over an extended region of the DIII-D plasma. Localized density fluctuations in the vicinity of the plasma cutoff surfaces modulate the plasma reflections, yielding a 2D image of electron density fluctuations. Details are presented of the receiver down conversion electronics that generate the in-phase (I) and quadrature (Q) reflectometer signals from which 2D density fluctuation data are obtained. Also presented are details on the control system and backplane used to manage the electronics as well as an introduction to the computer based control program.
Assessing 2D electrophoretic mobility spectroscopy (2D MOSY) for analytical applications.
Fang, Yuan; Yushmanov, Pavel V; Furó, István
2016-12-08
Electrophoretic displacement of charged entity phase modulates the spectrum acquired in electrophoretic NMR experiments, and this modulation can be presented via 2D FT as 2D mobility spectroscopy (MOSY) spectra. We compare in various mixed solutions the chemical selectivity provided by 2D MOSY spectra with that provided by 2D diffusion-ordered spectroscopy (DOSY) spectra and demonstrate, under the conditions explored, a superior performance of the former method. 2D MOSY compares also favourably with closely related LC-NMR methods. The shape of 2D MOSY spectra in complex mixtures is strongly modulated by the pH of the sample, a feature that has potential for areas such as in drug discovery and metabolomics. Copyright © 2016 The Authors. Magnetic Resonance in Chemistry published by John Wiley & Sons Ltd. StartCopTextCopyright © 2016 The Authors. Magnetic Resonance in Chemistry published by John Wiley & Sons Ltd.
The EM Method in a Probabilistic Wavelet-Based MRI Denoising
2015-01-01
Human body heat emission and others external causes can interfere in magnetic resonance image acquisition and produce noise. In this kind of images, the noise, when no signal is present, is Rayleigh distributed and its wavelet coefficients can be approximately modeled by a Gaussian distribution. Noiseless magnetic resonance images can be modeled by a Laplacian distribution in the wavelet domain. This paper proposes a new magnetic resonance image denoising method to solve this fact. This method performs shrinkage of wavelet coefficients based on the conditioned probability of being noise or detail. The parameters involved in this filtering approach are calculated by means of the expectation maximization (EM) method, which avoids the need to use an estimator of noise variance. The efficiency of the proposed filter is studied and compared with other important filtering techniques, such as Nowak's, Donoho-Johnstone's, Awate-Whitaker's, and nonlocal means filters, in different 2D and 3D images. PMID:26089959
The EM Method in a Probabilistic Wavelet-Based MRI Denoising.
Martin-Fernandez, Marcos; Villullas, Sergio
2015-01-01
Human body heat emission and others external causes can interfere in magnetic resonance image acquisition and produce noise. In this kind of images, the noise, when no signal is present, is Rayleigh distributed and its wavelet coefficients can be approximately modeled by a Gaussian distribution. Noiseless magnetic resonance images can be modeled by a Laplacian distribution in the wavelet domain. This paper proposes a new magnetic resonance image denoising method to solve this fact. This method performs shrinkage of wavelet coefficients based on the conditioned probability of being noise or detail. The parameters involved in this filtering approach are calculated by means of the expectation maximization (EM) method, which avoids the need to use an estimator of noise variance. The efficiency of the proposed filter is studied and compared with other important filtering techniques, such as Nowak's, Donoho-Johnstone's, Awate-Whitaker's, and nonlocal means filters, in different 2D and 3D images.
2D Distributed Sensing Via TDR
2007-11-02
plate VEGF CompositeSensor Experimental Setup Air 279 mm 61 78 VARTM profile: slope RTM profile: rectangle 22 1 Jul 2003© 2003 University of Delaware...2003 University of Delaware All rights reserved Vision: Non-contact 2D sensing ü VARTM setup constructed within TL can be sensed by its EM field: 2D...300.0 mm/ns. 1 2 1 Jul 2003© 2003 University of Delaware All rights reserved Model Validation “ RTM Flow” TDR Response to 139 mm VEGC
Inkjet printing of 2D layered materials.
Li, Jiantong; Lemme, Max C; Östling, Mikael
2014-11-10
Inkjet printing of 2D layered materials, such as graphene and MoS2, has attracted great interests for emerging electronics. However, incompatible rheology, low concentration, severe aggregation and toxicity of solvents constitute critical challenges which hamper the manufacturing efficiency and product quality. Here, we introduce a simple and general technology concept (distillation-assisted solvent exchange) to efficiently overcome these challenges. By implementing the concept, we have demonstrated excellent jetting performance, ideal printing patterns and a variety of promising applications for inkjet printing of 2D layered materials.
Denoising and robust nonlinear wavelet analysis
NASA Astrophysics Data System (ADS)
Bruce, Andrew G.; Donoho, David L.; Gao, Hong-Ye; Martin, R. D.
1994-03-01
In a series of papers, Donoho and Johnstone develop a powerful theory based on wavelets for extracting non-smooth signals from noisy data. Several nonlinear smoothing algorithms are presented which provide high performance for removing Gaussian noise from a wide range of spatially inhomogeneous signals. However, like other methods based on the linear wavelet transform, these algorithms are very sensitive to certain types of non-Gaussian noise, such as outliers. In this paper, we develop outlier resistant wavelet transforms. In these transforms, outliers and outlier patches are localized to just a few scales. By using the outlier resistant wavelet transform, we improve upon the Donoho and Johnstone nonlinear signal extraction methods. The outlier resistant wavelet algorithms are included with the 'S+WAVELETS' object-oriented toolkit for wavelet analysis.
Wavelets based on Hermite cubic splines
NASA Astrophysics Data System (ADS)
Cvejnová, Daniela; Černá, Dana; Finěk, Václav
2016-06-01
In 2000, W. Dahmen et al. designed biorthogonal multi-wavelets adapted to the interval [0,1] on the basis of Hermite cubic splines. In recent years, several more simple constructions of wavelet bases based on Hermite cubic splines were proposed. We focus here on wavelet bases with respect to which both the mass and stiffness matrices are sparse in the sense that the number of nonzero elements in any column is bounded by a constant. Then, a matrix-vector multiplication in adaptive wavelet methods can be performed exactly with linear complexity for any second order differential equation with constant coefficients. In this contribution, we shortly review these constructions and propose a new wavelet which leads to improved Riesz constants. Wavelets have four vanishing wavelet moments.
A Wavelet Perspective on the Allan Variance.
Percival, Donald B
2016-04-01
The origins of the Allan variance trace back 50 years ago to two seminal papers, one by Allan (1966) and the other by Barnes (1966). Since then, the Allan variance has played a leading role in the characterization of high-performance time and frequency standards. Wavelets first arose in the early 1980s in the geophysical literature, and the discrete wavelet transform (DWT) became prominent in the late 1980s in the signal processing literature. Flandrin (1992) briefly documented a connection between the Allan variance and a wavelet transform based upon the Haar wavelet. Percival and Guttorp (1994) noted that one popular estimator of the Allan variance-the maximal overlap estimator-can be interpreted in terms of a version of the DWT now widely referred to as the maximal overlap DWT (MODWT). In particular, when the MODWT is based on the Haar wavelet, the variance of the resulting wavelet coefficients-the wavelet variance-is identical to the Allan variance when the latter is multiplied by one-half. The theory behind the wavelet variance can thus deepen our understanding of the Allan variance. In this paper, we review basic wavelet variance theory with an emphasis on the Haar-based wavelet variance and its connection to the Allan variance. We then note that estimation theory for the wavelet variance offers a means of constructing asymptotically correct confidence intervals (CIs) for the Allan variance without reverting to the common practice of specifying a power-law noise type a priori. We also review recent work on specialized estimators of the wavelet variance that are of interest when some observations are missing (gappy data) or in the presence of contamination (rogue observations or outliers). It is a simple matter to adapt these estimators to become estimators of the Allan variance. Finally we note that wavelet variances based upon wavelets other than the Haar offer interesting generalizations of the Allan variance.
Enhanced automated platform for 2D characterization of RFID communications
NASA Astrophysics Data System (ADS)
Vuza, Dan Tudor; Vlǎdescu, Marian
2016-12-01
The characterization of the quality of communication between an RFID reader and a transponder at all expected positions of the latter on the reader antenna is of primal importance for the evaluation of performance of an RFID system. Continuing the line of instruments developed for this purpose by the authors, the present work proposes an enhanced version of a previously introduced automated platform for 2D evaluation. By featuring higher performance in terms of mechanical speed, the new version allows to obtain 2D maps of communication with a higher resolution that would have been prohibitive in terms of test duration with the previous version. The list of measurement procedures that can be executed with the platform is now enlarged with additional ones, such as the determination of the variation of the magnetic coupling between transponder and antenna across the antenna surface and the utilization of transponder simulators for evaluation of the quality of communication.
Visibility of wavelet quantization noise
NASA Technical Reports Server (NTRS)
Watson, A. B.; Yang, G. Y.; Solomon, J. A.; Villasenor, J.
1997-01-01
The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2-lambda, where r is display visual resolution in pixels/degree, and lambda is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.
Wavelet Approximation in Data Assimilation
NASA Technical Reports Server (NTRS)
Tangborn, Andrew; Atlas, Robert (Technical Monitor)
2002-01-01
Estimation of the state of the atmosphere with the Kalman filter remains a distant goal because of high computational cost of evolving the error covariance for both linear and nonlinear systems. Wavelet approximation is presented here as a possible solution that efficiently compresses both global and local covariance information. We demonstrate the compression characteristics on the the error correlation field from a global two-dimensional chemical constituent assimilation, and implement an adaptive wavelet approximation scheme on the assimilation of the one-dimensional Burger's equation. In the former problem, we show that 99%, of the error correlation can be represented by just 3% of the wavelet coefficients, with good representation of localized features. In the Burger's equation assimilation, the discrete linearized equations (tangent linear model) and analysis covariance are projected onto a wavelet basis and truncated to just 6%, of the coefficients. A nearly optimal forecast is achieved and we show that errors due to truncation of the dynamics are no greater than the errors due to covariance truncation.
Parallel Stitching of 2D Materials.
Ling, Xi; Lin, Yuxuan; Ma, Qiong; Wang, Ziqiang; Song, Yi; Yu, Lili; Huang, Shengxi; Fang, Wenjing; Zhang, Xu; Hsu, Allen L; Bie, Yaqing; Lee, Yi-Hsien; Zhu, Yimei; Wu, Lijun; Li, Ju; Jarillo-Herrero, Pablo; Dresselhaus, Mildred; Palacios, Tomás; Kong, Jing
2016-03-23
Diverse parallel stitched 2D heterostructures, including metal-semiconductor, semiconductor-semiconductor, and insulator-semiconductor, are synthesized directly through selective "sowing" of aromatic molecules as the seeds in the chemical vapor deposition (CVD) method. The methodology enables the large-scale fabrication of lateral heterostructures, which offers tremendous potential for its application in integrated circuits.
Beckett, Phil
2012-01-01
The technique of two-dimensional (2D) gel electrophoresis is a powerful tool for separating complex mixtures of proteins, but since its inception in the mid 1970s, it acquired the stigma of being a very difficult application to master and was generally used to its best effect by experts. The introduction of commercially available immobilized pH gradients in the early 1990s provided enhanced reproducibility and easier protocols, leading to a pronounced increase in popularity of the technique. However gel-to-gel variation was still difficult to control without the use of technical replicates. In the mid 1990s (at the same time as the birth of "proteomics"), the concept of multiplexing fluorescently labeled proteins for 2D gel separation was realized by Jon Minden's group and has led to the ability to design experiments to virtually eliminate gel-to-gel variation, resulting in biological replicates being used for statistical analysis with the ability to detect very small changes in relative protein abundance. This technology is referred to as 2D difference gel electrophoresis (2D DIGE).
Parallel stitching of 2D materials
Ling, Xi; Wu, Lijun; Lin, Yuxuan; ...
2016-01-27
Diverse parallel stitched 2D heterostructures, including metal–semiconductor, semiconductor–semiconductor, and insulator–semiconductor, are synthesized directly through selective “sowing” of aromatic molecules as the seeds in the chemical vapor deposition (CVD) method. Lastly, the methodology enables the large-scale fabrication of lateral heterostructures, which offers tremendous potential for its application in integrated circuits.
Regulation of Neuronal Survival Factor MEF2D by Chaperone-Mediated Autophagy
Yang, Qian; She, Hua; Gearing, Marla; Colla, Emanuela; Lee, Michael; Shacka, John J.; Mao, Zixu
2009-01-01
Chaperone-mediated autophagy controls the degradation of selective cytosolic proteins and may protect neurons against degeneration. In a neuronal cell line, we found that chaperone-mediated autophagy regulated the activity of myocyte enhancer factor 2D (MEF2D), a transcription factor required for neuronal survival. MEF2D was observed to continuously shuttle to the cytoplasm, interact with the chaperone Hsc70, and undergo degradation. Inhibition of chaperone-mediated autophagy caused accumulation of inactive MEF2D in the cytoplasm. MEF2D levels were increased in the brains of α-synuclein transgenic mice and patients with Parkinson’s disease. Wild-type α-synuclein and a Parkinson’s disease–associated mutant disrupted the MEF2D-Hsc70 binding and led to neuronal death. Thus, chaperone-mediated autophagy modulates the neuronal survival machinery, and dysregulation of this pathway is associated with Parkinson’s disease. PMID:19119233
Non-stationary dynamics in the bouncing ball: A wavelet perspective
Behera, Abhinna K. Panigrahi, Prasanta K.; Sekar Iyengar, A. N.
2014-12-01
The non-stationary dynamics of a bouncing ball, comprising both periodic as well as chaotic behavior, is studied through wavelet transform. The multi-scale characterization of the time series displays clear signatures of self-similarity, complex scaling behavior, and periodicity. Self-similar behavior is quantified by the generalized Hurst exponent, obtained through both wavelet based multi-fractal detrended fluctuation analysis and Fourier methods. The scale dependent variable window size of the wavelets aptly captures both the transients and non-stationary periodic behavior, including the phase synchronization of different modes. The optimal time-frequency localization of the continuous Morlet wavelet is found to delineate the scales corresponding to neutral turbulence, viscous dissipation regions, and different time varying periodic modulations.
Wavelet Analyses of Oil Prices, USD Variations and Impact on Logistics
NASA Astrophysics Data System (ADS)
Melek, M.; Tokgozlu, A.; Aslan, Z.
2009-07-01
This paper is related with temporal variations of historical oil prices and Dollar and Euro in Turkey. Daily data based on OECD and Central Bank of Turkey records beginning from 1946 has been considered. 1D-continuous wavelets and wavelet packets analysis techniques have been applied on data. Wavelet techniques help to detect abrupt changing's, increasing and decreasing trends of data. Estimation of variables has been presented by using linear regression estimation techniques. The results of this study have been compared with the small and large scale effects. Transportation costs of track show a similar variation with fuel prices. The second part of the paper is related with estimation of imports, exports, costs, total number of vehicles and annual variations by considering temporal variation of oil prices and Dollar currency in Turkey. Wavelet techniques offer a user friendly methodology to interpret some local effects on increasing trend of imports and exports data.
Real Clifford Algebra Cl{sub n,0}, n = 2, 3(mod 4) Wavelet Transform
Hitzer, Eckhard
2009-09-09
We show how for n = 2, 3(mod 4) continuous Clifford (geometric) algebra (GA)Cl{sub n}-valued admissible wavelets can be constructed using the similitude group SIM(n). We strictly aim for real geometric interpretation, and replace the imaginary unit i is an element of C therefore with a GA blade squaring to -1. Consequences due to non-commutativity arise. We express the admissibility condition in terms of a Cl{sub n} Clifford Fourier Transform and then derive a set of important properties such as dilation, translation and rotation covariance, a reproducing kernel, and show how to invert the Clifford wavelet transform. As an example, we introduce Clifford Gabor wavelets. We further invent a generalized Clifford wavelet uncertainty principle.
Application of 2D Non-Graphene Materials and 2D Oxide Nanostructures for Biosensing Technology
Shavanova, Kateryna; Bakakina, Yulia; Burkova, Inna; Shtepliuk, Ivan; Viter, Roman; Ubelis, Arnolds; Beni, Valerio; Starodub, Nickolaj; Yakimova, Rositsa; Khranovskyy, Volodymyr
2016-01-01
The discovery of graphene and its unique properties has inspired researchers to try to invent other two-dimensional (2D) materials. After considerable research effort, a distinct “beyond graphene” domain has been established, comprising the library of non-graphene 2D materials. It is significant that some 2D non-graphene materials possess solid advantages over their predecessor, such as having a direct band gap, and therefore are highly promising for a number of applications. These applications are not limited to nano- and opto-electronics, but have a strong potential in biosensing technologies, as one example. However, since most of the 2D non-graphene materials have been newly discovered, most of the research efforts are concentrated on material synthesis and the investigation of the properties of the material. Applications of 2D non-graphene materials are still at the embryonic stage, and the integration of 2D non-graphene materials into devices is scarcely reported. However, in recent years, numerous reports have blossomed about 2D material-based biosensors, evidencing the growing potential of 2D non-graphene materials for biosensing applications. This review highlights the recent progress in research on the potential of using 2D non-graphene materials and similar oxide nanostructures for different types of biosensors (optical and electrochemical). A wide range of biological targets, such as glucose, dopamine, cortisol, DNA, IgG, bisphenol, ascorbic acid, cytochrome and estradiol, has been reported to be successfully detected by biosensors with transducers made of 2D non-graphene materials. PMID:26861346
Application of 2D Non-Graphene Materials and 2D Oxide Nanostructures for Biosensing Technology.
Shavanova, Kateryna; Bakakina, Yulia; Burkova, Inna; Shtepliuk, Ivan; Viter, Roman; Ubelis, Arnolds; Beni, Valerio; Starodub, Nickolaj; Yakimova, Rositsa; Khranovskyy, Volodymyr
2016-02-06
The discovery of graphene and its unique properties has inspired researchers to try to invent other two-dimensional (2D) materials. After considerable research effort, a distinct "beyond graphene" domain has been established, comprising the library of non-graphene 2D materials. It is significant that some 2D non-graphene materials possess solid advantages over their predecessor, such as having a direct band gap, and therefore are highly promising for a number of applications. These applications are not limited to nano- and opto-electronics, but have a strong potential in biosensing technologies, as one example. However, since most of the 2D non-graphene materials have been newly discovered, most of the research efforts are concentrated on material synthesis and the investigation of the properties of the material. Applications of 2D non-graphene materials are still at the embryonic stage, and the integration of 2D non-graphene materials into devices is scarcely reported. However, in recent years, numerous reports have blossomed about 2D material-based biosensors, evidencing the growing potential of 2D non-graphene materials for biosensing applications. This review highlights the recent progress in research on the potential of using 2D non-graphene materials and similar oxide nanostructures for different types of biosensors (optical and electrochemical). A wide range of biological targets, such as glucose, dopamine, cortisol, DNA, IgG, bisphenol, ascorbic acid, cytochrome and estradiol, has been reported to be successfully detected by biosensors with transducers made of 2D non-graphene materials.
A new approach for crop identification with wavelet variance and JM distance.
Qiu, Bingwen; Fan, Zhanling; Zhong, Ming; Tang, Zhenghong; Chen, Chongcheng
2014-11-01
This paper develops a new crop mapping method through combined utilization of both time and frequency information based on wavelet variance and Jeffries-Matusita (JM) distance (CIWJ for short). A two-dimensional wavelet spectrum was obtained from datasets of daily continuous vegetation indices through a continuous wavelet transform using the Mexican hat and the Morlet mother wavelets. The time-average wavelet variance (TAWV) and the scale-average wavelet variance (SAWV) were then calculated based on the wavelet spectrum of the Mexican hat and the Morlet wavelet, respectively. The class separability based on the JM distance was evaluated to discriminate the proper period or scale range applied. Finally, a procedure for criteria quantification was developed using the TAWV and SAWV as the major metrics, and the similarity between unclassified pixels and established land use/cover types was calculated. The proposed CIWJ method was applied to the middle Hexi Corridor in northwest China using 250-m 8-day composite moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI) time series datasets in 2012. The CIWJ method was shown to be efficient in crop field mapping, with an overall accuracy of 83.6 % and kappa coefficient of 0.7009, assessed with 30 m Chinese Environmental Disaster Reduction Satellite (HJ-1)-derived data. Compared with methods utilizing information on either frequency or time, the CIWJ method demonstrates tremendous potential for efficient crop mapping and for further applications. This method could be applied to either coarse or high spatial resolution images for agricultural crop identification, as well as other more general or specific land use classifications.
NASA Astrophysics Data System (ADS)
Ng, J.; Kingsbury, N. G.
2004-02-01
This book provides an overview of the theory and practice of continuous and discrete wavelet transforms. Divided into seven chapters, the first three chapters of the book are introductory, describing the various forms of the wavelet transform and their computation, while the remaining chapters are devoted to applications in fluids, engineering, medicine and miscellaneous areas. Each chapter is well introduced, with suitable examples to demonstrate key concepts. Illustrations are included where appropriate, thus adding a visual dimension to the text. A noteworthy feature is the inclusion, at the end of each chapter, of a list of further resources from the academic literature which the interested reader can consult. The first chapter is purely an introduction to the text. The treatment of wavelet transforms begins in the second chapter, with the definition of what a wavelet is. The chapter continues by defining the continuous wavelet transform and its inverse and a description of how it may be used to interrogate signals. The continuous wavelet transform is then compared to the short-time Fourier transform. Energy and power spectra with respect to scale are also discussed and linked to their frequency counterparts. Towards the end of the chapter, the two-dimensional continuous wavelet transform is introduced. Examples of how the continuous wavelet transform is computed using the Mexican hat and Morlet wavelets are provided throughout. The third chapter introduces the discrete wavelet transform, with its distinction from the discretized continuous wavelet transform having been made clear at the end of the second chapter. In the first half of the chapter, the logarithmic discretization of the wavelet function is described, leading to a discussion of dyadic grid scaling, frames, orthogonal and orthonormal bases, scaling functions and multiresolution representation. The fast wavelet transform is introduced and its computation is illustrated with an example using the Haar
Compatible embedding for 2D shape animation.
Baxter, William V; Barla, Pascal; Anjyo, Ken-Ichi
2009-01-01
We present new algorithms for the compatible embedding of 2D shapes. Such embeddings offer a convenient way to interpolate shapes having complex, detailed features. Compared to existing techniques, our approach requires less user input, and is faster, more robust, and simpler to implement, making it ideal for interactive use in practical applications. Our new approach consists of three parts. First, our boundary matching algorithm locates salient features using the perceptually motivated principles of scale-space and uses these as automatic correspondences to guide an elastic curve matching algorithm. Second, we simplify boundaries while maintaining their parametric correspondence and the embedding of the original shapes. Finally, we extend the mapping to shapes' interiors via a new compatible triangulation algorithm. The combination of our algorithms allows us to demonstrate 2D shape interpolation with instant feedback. The proposed algorithms exhibit a combination of simplicity, speed, and accuracy that has not been achieved in previous work.
Schottky diodes from 2D germanane
NASA Astrophysics Data System (ADS)
Sahoo, Nanda Gopal; Esteves, Richard J.; Punetha, Vinay Deep; Pestov, Dmitry; Arachchige, Indika U.; McLeskey, James T.
2016-07-01
We report on the fabrication and characterization of a Schottky diode made using 2D germanane (hydrogenated germanene). When compared to germanium, the 2D structure has higher electron mobility, an optimal band-gap, and exceptional stability making germanane an outstanding candidate for a variety of opto-electronic devices. One-atom-thick sheets of hydrogenated puckered germanium atoms have been synthesized from a CaGe2 framework via intercalation and characterized by XRD, Raman, and FTIR techniques. The material was then used to fabricate Schottky diodes by suspending the germanane in benzonitrile and drop-casting it onto interdigitated metal electrodes. The devices demonstrate significant rectifying behavior and the outstanding potential of this material.
Extrinsic Cation Selectivity of 2D Membranes
2017-01-01
From a systematic study of the concentration driven diffusion of positive and negative ions across porous 2D membranes of graphene and hexagonal boron nitride (h-BN), we prove their cation selectivity. Using the current–voltage characteristics of graphene and h-BN monolayers separating reservoirs of different salt concentrations, we calculate the reversal potential as a measure of selectivity. We tune the Debye screening length by exchanging the salt concentrations and demonstrate that negative surface charge gives rise to cation selectivity. Surprisingly, h-BN and graphene membranes show similar characteristics, strongly suggesting a common origin of selectivity in aqueous solvents. For the first time, we demonstrate that the cation flux can be increased by using ozone to create additional pores in graphene while maintaining excellent selectivity. We discuss opportunities to exploit our scalable method to use 2D membranes for applications including osmotic power conversion. PMID:28157333
Static & Dynamic Response of 2D Solids
Lin, Jerry
1996-07-15
NIKE2D is an implicit finite-element code for analyzing the finite deformation, static and dynamic response of two-dimensional, axisymmetric, plane strain, and plane stress solids. The code is fully vectorized and available on several computing platforms. A number of material models are incorporated to simulate a wide range of material behavior including elasto-placicity, anisotropy, creep, thermal effects, and rate dependence. Slideline algorithms model gaps and sliding along material interfaces, including interface friction, penetration and single surface contact. Interactive-graphics and rezoning is included for analyses with large mesh distortions. In addition to quasi-Newton and arc-length procedures, adaptive algorithms can be defined to solve the implicit equations using the solution language ISLAND. Each of these capabilities and more make NIKE2D a robust analysis tool.
Explicit 2-D Hydrodynamic FEM Program
Lin, Jerry
1996-08-07
DYNA2D* is a vectorized, explicit, two-dimensional, axisymmetric and plane strain finite element program for analyzing the large deformation dynamic and hydrodynamic response of inelastic solids. DYNA2D* contains 13 material models and 9 equations of state (EOS) to cover a wide range of material behavior. The material models implemented in all machine versions are: elastic, orthotropic elastic, kinematic/isotropic elastic plasticity, thermoelastoplastic, soil and crushable foam, linear viscoelastic, rubber, high explosive burn, isotropic elastic-plastic, temperature-dependent elastic-plastic. The isotropic and temperature-dependent elastic-plastic models determine only the deviatoric stresses. Pressure is determined by one of 9 equations of state including linear polynomial, JWL high explosive, Sack Tuesday high explosive, Gruneisen, ratio of polynomials, linear polynomial with energy deposition, ignition and growth of reaction in HE, tabulated compaction, and tabulated.
Quasiparticle interference in unconventional 2D systems
NASA Astrophysics Data System (ADS)
Chen, Lan; Cheng, Peng; Wu, Kehui
2017-03-01
At present, research of 2D systems mainly focuses on two kinds of materials: graphene-like materials and transition-metal dichalcogenides (TMDs). Both of them host unconventional 2D electronic properties: pseudospin and the associated chirality of electrons in graphene-like materials, and spin-valley-coupled electronic structures in the TMDs. These exotic electronic properties have attracted tremendous interest for possible applications in nanodevices in the future. Investigation on the quasiparticle interference (QPI) in 2D systems is an effective way to uncover these properties. In this review, we will begin with a brief introduction to 2D systems, including their atomic structures and electronic bands. Then, we will discuss the formation of Friedel oscillation due to QPI in constant energy contours of electron bands, and show the basic concept of Fourier-transform scanning tunneling microscopy/spectroscopy (FT-STM/STS), which can resolve Friedel oscillation patterns in real space and consequently obtain the QPI patterns in reciprocal space. In the next two parts, we will summarize some pivotal results in the investigation of QPI in graphene and silicene, in which systems the low-energy quasiparticles are described by the massless Dirac equation. The FT-STM experiments show there are two different interference channels (intervalley and intravalley scattering) and backscattering suppression, which associate with the Dirac cones and the chirality of quasiparticles. The monolayer and bilayer graphene on different substrates (SiC and metal surfaces), and the monolayer and multilayer silicene on a Ag(1 1 1) surface will be addressed. The fifth part will introduce the FT-STM research on QPI in TMDs (monolayer and bilayer of WSe2), which allow us to infer the spin texture of both conduction and valence bands, and present spin-valley coupling by tracking allowed and forbidden scattering channels.
Compact 2-D graphical representation of DNA
NASA Astrophysics Data System (ADS)
Randić, Milan; Vračko, Marjan; Zupan, Jure; Novič, Marjana
2003-05-01
We present a novel 2-D graphical representation for DNA sequences which has an important advantage over the existing graphical representations of DNA in being very compact. It is based on: (1) use of binary labels for the four nucleic acid bases, and (2) use of the 'worm' curve as template on which binary codes are placed. The approach is illustrated on DNA sequences of the first exon of human β-globin and gorilla β-globin.
2D Metals by Repeated Size Reduction.
Liu, Hanwen; Tang, Hao; Fang, Minghao; Si, Wenjie; Zhang, Qinghua; Huang, Zhaohui; Gu, Lin; Pan, Wei; Yao, Jie; Nan, Cewen; Wu, Hui
2016-10-01
A general and convenient strategy for manufacturing freestanding metal nanolayers is developed on large scale. By the simple process of repeatedly folding and calendering stacked metal sheets followed by chemical etching, free-standing 2D metal (e.g., Ag, Au, Fe, Cu, and Ni) nanosheets are obtained with thicknesses as small as 1 nm and with sizes of the order of several micrometers.
Realistic and efficient 2D crack simulation
NASA Astrophysics Data System (ADS)
Yadegar, Jacob; Liu, Xiaoqing; Singh, Abhishek
2010-04-01
Although numerical algorithms for 2D crack simulation have been studied in Modeling and Simulation (M&S) and computer graphics for decades, realism and computational efficiency are still major challenges. In this paper, we introduce a high-fidelity, scalable, adaptive and efficient/runtime 2D crack/fracture simulation system by applying the mathematically elegant Peano-Cesaro triangular meshing/remeshing technique to model the generation of shards/fragments. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level-of-detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanism used for mesh element splitting and merging with minimal memory requirements essential for realistic 2D fragment formation. Upon load impact/contact/penetration, a number of factors including impact angle, impact energy, and material properties are all taken into account to produce the criteria of crack initialization, propagation, and termination leading to realistic fractal-like rubble/fragments formation. The aforementioned parameters are used as variables of probabilistic models of cracks/shards formation, making the proposed solution highly adaptive by allowing machine learning mechanisms learn the optimal values for the variables/parameters based on prior benchmark data generated by off-line physics based simulation solutions that produce accurate fractures/shards though at highly non-real time paste. Crack/fracture simulation has been conducted on various load impacts with different initial locations at various impulse scales. The simulation results demonstrate that the proposed system has the capability to realistically and efficiently simulate 2D crack phenomena (such as window shattering and shards generation) with diverse potentials in military and civil M&S applications such as training and mission planning.
Engineering light outcoupling in 2D materials.
Lien, Der-Hsien; Kang, Jeong Seuk; Amani, Matin; Chen, Kevin; Tosun, Mahmut; Wang, Hsin-Ping; Roy, Tania; Eggleston, Michael S; Wu, Ming C; Dubey, Madan; Lee, Si-Chen; He, Jr-Hau; Javey, Ali
2015-02-11
When light is incident on 2D transition metal dichalcogenides (TMDCs), it engages in multiple reflections within underlying substrates, producing interferences that lead to enhancement or attenuation of the incoming and outgoing strength of light. Here, we report a simple method to engineer the light outcoupling in semiconducting TMDCs by modulating their dielectric surroundings. We show that by modulating the thicknesses of underlying substrates and capping layers, the interference caused by substrate can significantly enhance the light absorption and emission of WSe2, resulting in a ∼11 times increase in Raman signal and a ∼30 times increase in the photoluminescence (PL) intensity of WSe2. On the basis of the interference model, we also propose a strategy to control the photonic and optoelectronic properties of thin-layer WSe2. This work demonstrates the utilization of outcoupling engineering in 2D materials and offers a new route toward the realization of novel optoelectronic devices, such as 2D LEDs and solar cells.
Irreversibility-inversions in 2D turbulence
NASA Astrophysics Data System (ADS)
Bragg, Andrew; de Lillo, Filippo; Boffetta, Guido
2016-11-01
We consider a recent theoretical prediction that for inertial particles in 2D turbulence, the nature of the irreversibility of their pair dispersion inverts when the particle inertia exceeds a certain value. In particular, when the particle Stokes number, St , is below a certain value, the forward-in-time (FIT) dispersion should be faster than the backward-in-time (BIT) dispersion, but for St above this value, this should invert so that BIT becomes faster than FIT dispersion. This non-trivial behavior arises because of the competition between two physically distinct irreversibility mechanisms that operate in different regimes of St . In 3D turbulence, both mechanisms act to produce faster BIT than FIT dispersion, but in 2D, the two mechanisms have opposite effects because of the inverse energy cascade in the turbulent velocity field. We supplement the qualitative argument given by Bragg et al. by deriving quantitative predictions of this effect in the short-time dispersion limit. These predictions are then confirmed by results of inertial particle dispersion in a direct numerical simulation of 2D turbulence.
Optical Wavelet Signals Processing and Multiplexing
NASA Astrophysics Data System (ADS)
Cincotti, Gabriella; Moreolo, Michela Svaluto; Neri, Alessandro
2005-12-01
We present compact integrable architectures to perform the discrete wavelet transform (DWT) and the wavelet packet (WP) decomposition of an optical digital signal, and we show that the combined use of planar lightwave circuits (PLC) technology and multiresolution analysis (MRA) can add flexibility to current multiple access optical networks. We furnish the design guidelines to synthesize wavelet filters as two-port lattice-form planar devices, and we give some examples of optical signal denoising and compression/decompression techniques in the wavelet domain. Finally, we present a fully optical wavelet packet division multiplexing (WPDM) scheme where data signals are waveform-coded onto wavelet atom functions for transmission, and numerically evaluate its performances.
Wavelet analysis of internal gravity waves
NASA Astrophysics Data System (ADS)
Hawkins, J.; Warn-Varnas, A.; Chin-Bing, S.; King, D.; Smolarkiewicsz, P.
2005-05-01
A series of model studies of internal gravity waves (igw) have been conducted for several regions of interest. Dispersion relations from the results have been computed using wavelet analysis as described by Meyers (1993). The wavelet transform is repeatedly applied over time and the components are evaluated with respect to their amplitude and peak position (Torrence and Compo, 1998). In this sense we have been able to compute dispersion relations from model results and from measured data. Qualitative agreement has been obtained in some cases. The results from wavelet analysis must be carefully interpreted because the igw models are fully nonlinear and wavelet analysis is fundamentally a linear technique. Nevertheless, a great deal of information describing igw propagation can be obtained from the wavelet transform. We address the domains over which wavelet analysis techniques can be applied and discuss the limits of their applicability.
NASA Astrophysics Data System (ADS)
Zielinski, B.; Patorski, K.
2008-12-01
The aim of this paper is to analyze the accuracy of 2D fringe pattern denoising performed by two chosen methods using quasi-1D two-arm spin filter and 2D Discrete Wavelet Transform (DWT) signal decomposition and thresholding. The ultimate aim of this comparison is to estimate which algorithm is better suited for high-accuracy interferometric measurements. In spite of the fact that both algorithms are designed to minimize possible fringe blur and distortion, the evaluation of errors introduced by each algorithm is essential for proper estimation of their performance.
NASA Astrophysics Data System (ADS)
Quesada-Barriuso, Pablo; Heras, Dora B.; Argüello, Francisco
2016-10-01
The classification of remote sensing hyperspectral images for land cover applications is a very intensive topic. In the case of supervised classification, Support Vector Machines (SVMs) play a dominant role. Recently, the Extreme Learning Machine algorithm (ELM) has been extensively used. The classification scheme previously published by the authors, and called WT-EMP, introduces spatial information in the classification process by means of an Extended Morphological Profile (EMP) that is created from features extracted by wavelets. In addition, the hyperspectral image is denoised in the 2-D spatial domain, also using wavelets and it is joined to the EMP via a stacked vector. In this paper, the scheme is improved achieving two goals. The first one is to reduce the classification time while preserving the accuracy of the classification by using ELM instead of SVM. The second one is to improve the accuracy results by performing not only a 2-D denoising for every spectral band, but also a previous additional 1-D spectral signature denoising applied to each pixel vector of the image. For each denoising the image is transformed by applying a 1-D or 2-D wavelet transform, and then a NeighShrink thresholding is applied. Improvements in terms of classification accuracy are obtained, especially for images with close regions in the classification reference map, because in these cases the accuracy of the classification in the edges between classes is more relevant.
Improving 3D Wavelet-Based Compression of Hyperspectral Images
NASA Technical Reports Server (NTRS)
Klimesh, Matthew; Kiely, Aaron; Xie, Hua; Aranki, Nazeeh
2009-01-01
Two methods of increasing the effectiveness of three-dimensional (3D) wavelet-based compression of hyperspectral images have been developed. (As used here, images signifies both images and digital data representing images.) The methods are oriented toward reducing or eliminating detrimental effects of a phenomenon, referred to as spectral ringing, that is described below. In 3D wavelet-based compression, an image is represented by a multiresolution wavelet decomposition consisting of several subbands obtained by applying wavelet transforms in the two spatial dimensions corresponding to the two spatial coordinate axes of the image plane, and by applying wavelet transforms in the spectral dimension. Spectral ringing is named after the more familiar spatial ringing (spurious spatial oscillations) that can be seen parallel to and near edges in ordinary images reconstructed from compressed data. These ringing phenomena are attributable to effects of quantization. In hyperspectral data, the individual spectral bands play the role of edges, causing spurious oscillations to occur in the spectral dimension. In the absence of such corrective measures as the present two methods, spectral ringing can manifest itself as systematic biases in some reconstructed spectral bands and can reduce the effectiveness of compression of spatially-low-pass subbands. One of the two methods is denoted mean subtraction. The basic idea of this method is to subtract mean values from spatial planes of spatially low-pass subbands prior to encoding, because (a) such spatial planes often have mean values that are far from zero and (b) zero-mean data are better suited for compression by methods that are effective for subbands of two-dimensional (2D) images. In this method, after the 3D wavelet decomposition is performed, mean values are computed for and subtracted from each spatial plane of each spatially-low-pass subband. The resulting data are converted to sign-magnitude form and compressed in a
2001-10-25
We evaluate a combined discrete wavelet transform (DWT) and wavelet packet algorithm to improve the homogeneity of magnetic resonance imaging when a...image and uses this information to normalize the image intensity variations. Estimation of the coil sensitivity profile based on the wavelet transform of
Wavelet-Based Adaptive Denoising of Phonocardiographic Records
2007-11-02
the approximated signal, and d the signal details at the given scale; h and g are biorthogonal filters, corresponding to the selected mother wavelet ...dyadic scale can be written as: where is the orthogonal mother wavelet , and: The discrete version of the dyadic wavelet transform can be based on... wavelet with 4 moments equal to zero (Coiflet-2) as the mother wavelet . The two channels were wavelet decomposed up to the 9th order (i = 0, 1 ... 8
Application and Development of Wavelet Analysis
1992-08-15
found that optics is quite suitable to generate and display both the direct and the inverse wavelet transforms in parallel. Unlike the digital...toward identifying the suitability of using optics for the multichannel signal analysis. Both the Gabor and the wavelet transforms were studied in terms...inverse wavelet transforms . This is the case for processing both the one and two dimensional signals. A detail comparison of the space-bandwidth
Develop, Apply and Evaluate Wavelet Technology.
1992-10-20
Eddington (1928), A. S . The Nature of the Physical World, Cambridge: Cambridge University Press. [11] Einstein , A. (155), The Meaning of Relativity...Albequerque, NM, 1990. [9] R. A. Gopinath and C. S . Burrus, "Wavelet transforms and filter banks," pp. 603-654 in Wavelets: A Tutorial in Theory and...Resnikoff, "Multidimensional wavelet bases," Aware Technical Report, Aware, Inc., Cambridge, MA 1991. [25] S . G. Mallat, "A Theory for multiresolution
Wavelet analysis in two-dimensional tomography
NASA Astrophysics Data System (ADS)
Burkovets, Dimitry N.
2002-02-01
The diagnostic possibilities of wavelet-analysis of coherent images of connective tissue in its pathological changes diagnostics. The effectiveness of polarization selection in obtaining wavelet-coefficients' images is also shown. The wavelet structures, characterizing the process of skin psoriasis, bone-tissue osteoporosis have been analyzed. The histological sections of physiological normal and pathologically changed samples of connective tissue of human skin and spongy bone tissue have been analyzed.
Wavelet Features Based Fingerprint Verification
NASA Astrophysics Data System (ADS)
Bagadi, Shweta U.; Thalange, Asha V.; Jain, Giridhar P.
2010-11-01
In this work; we present a automatic fingerprint identification system based on Level 3 features. Systems based only on minutiae features do not perform well for poor quality images. In practice, we often encounter extremely dry, wet fingerprint images with cuts, warts, etc. Due to such fingerprints, minutiae based systems show poor performance for real time authentication applications. To alleviate the problem of poor quality fingerprints, and to improve overall performance of the system, this paper proposes fingerprint verification based on wavelet statistical features & co-occurrence matrix features. The features include mean, standard deviation, energy, entropy, contrast, local homogeneity, cluster shade, cluster prominence, Information measure of correlation. In this method, matching can be done between the input image and the stored template without exhaustive search using the extracted feature. The wavelet transform based approach is better than the existing minutiae based method and it takes less response time and hence suitable for on-line verification, with high accuracy.
Multidimensional signaling via wavelet packets
NASA Astrophysics Data System (ADS)
Lindsey, Alan R.
1995-04-01
This work presents a generalized signaling strategy for orthogonally multiplexed communication. Wavelet packet modulation (WPM) employs the basis functions from an arbitrary pruning of a full dyadic tree structured filter bank as orthogonal pulse shapes for conventional QAM symbols. The multi-scale modulation (MSM) and M-band wavelet modulation (MWM) schemes which have been recently introduced are handled as special cases, with the added benefit of an entire library of potentially superior sets of basis functions. The figures of merit are derived and it is shown that the power spectral density is equivalent to that for QAM (in fact, QAM is another special case) and hence directly applicable in existing systems employing this standard modulation. Two key advantages of this method are increased flexibility in time-frequency partitioning and an efficient all-digital filter bank implementation, making the WPM scheme more robust to a larger set of interferences (both temporal and sinusoidal) and computationally attractive as well.
Wavelet methods in data mining
NASA Astrophysics Data System (ADS)
Manchanda, P.
2012-07-01
Data mining (knowledge discovery in data base) is comparatively new interdisciplinary field developed by joint efforts of mathematicians, statisticians, computer scientists and engineers. There are twelve important ingredients of this field along with their applications in real world problems. In this chapter, we have reviewed application of wavelet methods to data mining, particularly denoising, dimension reduction, similarity search, feature extraction and prediction. Meteorological data of Saudi Arabia and Stock market data of India are considered for illustration.
Wavelets, signal processing and matrix computations
NASA Astrophysics Data System (ADS)
Suter, Bruce W.
1994-09-01
Key scientific results were found in the following four areas: (1) multidimensional Malvar wavelets; (2) time/spatial varying filter banks; (3) vector filter banks and vector-valued wavelets; and (4) multirate time-frequency. These results have opened the following new areas of research: nonseparable multidimensional Malvar wavelets, vector-valued wavelets and vector filter banks, and multirate time-frequency analysis. These results also provide fundamental tools in many Air Force and industrial applications, such as modeling of turbulence, compression of images/video images, etc.
Widom, Julia R; Johnson, Neil P; von Hippel, Peter H; Marcus, Andrew H
2013-02-01
We have observed the conformation-dependent electronic coupling between the monomeric subunits of a dinucleotide of 2-aminopurine (2-AP), a fluorescent analog of the nucleic acid base adenine. This was accomplished by extending two-dimensional fluorescence spectroscopy (2D FS) - a fluorescence-detected variation of 2D electronic spectroscopy - to excite molecular transitions in the ultraviolet (UV) regime. A collinear sequence of four ultrafast laser pulses centered at 323 nm was used to resonantly excite the coupled transitions of 2-AP dinucleotide. The phases of the optical pulses were continuously swept at kilohertz frequencies, and the ensuing nonlinear fluorescence was phase-synchronously detected at 370 nm. Upon optimization of a point-dipole coupling model to our data, we found that in aqueous buffer the 2-AP dinucleotide adopts an average conformation in which the purine bases are non-helically stacked (center-to-center distance R12 = 3.5 Å ± 0.5 Å, twist angle θ12 = 5° ± 5°), which differs from the conformation of such adjacent bases in duplex DNA. These experiments establish UV-2D FS as a method for examining the local conformations of an adjacent pair of fluorescent nucleotides substituted into specific DNA or RNA constructs, which will serve as a powerful probe to interpret, in structural terms, biologically significant local conformational changes within the nucleic acid framework of protein-nucleic acid complexes.
Optical Aperture Synthesis Object's Information Extracting Based on Wavelet Denoising
NASA Astrophysics Data System (ADS)
Fan, W. J.; Lu, Y.
2006-10-01
Wavelet denoising is studied to improve OAS(optical aperture synthesis) object's Fourier information extracting. Translation invariance wavelet denoising based on Donoho wavelet soft threshold denoising is researched to remove Pseudo-Gibbs in wavelet soft threshold image. OAS object's information extracting based on translation invariance wavelet denoising is studied. The study shows that wavelet threshold denoising can improve the precision and the repetition of object's information extracting from interferogram, and the translation invariance wavelet denoising information extracting is better than soft threshold wavelet denoising information extracting.
Visibility of Wavelet Quantization Noise
NASA Technical Reports Server (NTRS)
Watson, Andrew B.; Yang, Gloria Y.; Solomon, Joshua A.; Villasenor, John; Null, Cynthia H. (Technical Monitor)
1995-01-01
The Discrete Wavelet Transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter, which we call DWT uniform quantization noise. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2(exp)-L , where r is display visual resolution in pixels/degree, and L is the wavelet level. Amplitude thresholds increase rapidly with spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from low-pass to horizontal/vertical to diagonal. We describe a mathematical model to predict DWT noise detection thresholds as a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.
LIDAR data compression using wavelets
NASA Astrophysics Data System (ADS)
Pradhan, B.; Mansor, Shattri; Ramli, Abdul Rahman; Mohamed Sharif, Abdul Rashid B.; Sandeep, K.
2005-10-01
The lifting scheme has been found to be a flexible method for constructing scalar wavelets with desirable properties. In this paper, it is extended to the LIDAR data compression. A newly developed data compression approach to approximate the LIDAR surface with a series of non-overlapping triangles has been presented. Generally a Triangulated Irregular Networks (TIN) are the most common form of digital surface model that consists of elevation values with x, y coordinates that make up triangles. But over the years the TIN data representation has become a case in point for many researchers due its large data size. Compression of TIN is needed for efficient management of large data and good surface visualization. This approach covers following steps: First, by using a Delaunay triangulation, an efficient algorithm is developed to generate TIN, which forms the terrain from an arbitrary set of data. A new interpolation wavelet filter for TIN has been applied in two steps, namely splitting and elevation. In the splitting step, a triangle has been divided into several sub-triangles and the elevation step has been used to 'modify' the point values (point coordinates for geometry) after the splitting. Then, this data set is compressed at the desired locations by using second generation wavelets. The quality of geographical surface representation after using proposed technique is compared with the original LIDAR data. The results show that this method can be used for significant reduction of data set.
Ground extraction from airborne laser data based on wavelet analysis
NASA Astrophysics Data System (ADS)
Xu, Liang; Yang, Yan; Jiang, Bowen; Li, Jia
2007-11-01
With the advantages of high resolution and accuracy, airborne laser scanning data are widely used in topographic mapping. In order to generate a DTM, measurements from object features such as buildings, vehicles and vegetation have to be classified and removed. However, the automatic extraction of bare earth from point clouds acquired by airborne laser scanning equipment remains a problem in LIDAR data filtering nowadays. In this paper, a filter algorithm based on wavelet analysis is proposed. Relying on the capability of detecting discontinuities of continuous wavelet transform and the feature of multi-resolution analysis, the object points can be removed, while ground data are preserved. In order to evaluate the performance of this approach, we applied it to the data set used in the ISPRS filter test in 2003. 15 samples have been tested by the proposed approach. Results showed that it filtered most of the objects like vegetation and buildings, and extracted a well defined ground model.
NASA Astrophysics Data System (ADS)
Kushwaha, Alok Kumar Singh; Srivastava, Rajeev
2015-09-01
Moving object segmentation using change detection in wavelet domain under continuous variations of lighting condition is a challenging problem in video surveillance systems. There are several methods proposed in the literature for change detection in wavelet domain for moving object segmentation having static backgrounds, but it has not been addressed effectively for dynamic background changes. The methods proposed in the literature suffer from various problems, such as ghostlike appearance, object shadows, and noise. To deal with these issues, a framework for dynamic background modeling and shadow suppression under rapidly changing illumination conditions for moving object segmentation in complex wavelet domain is proposed. The proposed method consists of eight steps applied on given video frames, which include wavelet decomposition of frame using complex wavelet transform; use of change detection on detail coefficients (LH, HL, and HH), use of improved Gaussian mixture-based dynamic background modeling on approximate coefficient (LL subband); cast shadow suppression; use of soft thresholding for noise removal; strong edge detection; inverse wavelet transformation for reconstruction; and finally using closing morphology operator. A comparative analysis of the proposed method is presented both qualitatively and quantitatively with other standard methods available in the literature for six datasets in terms of various performance measures. Experimental results demonstrate the efficacy of the proposed method.
A multiple digital watermarking algorithm based on 1D and 2D chaotic sequences
NASA Astrophysics Data System (ADS)
Ji, Zhen; Jiang, Lai; Jin, Jing; Zhang, Jihong
2003-09-01
Multiple digital watermarking is attracting more and more researchers because it is more valuable in the practical applications than single watermarking. In this paper, a multiple watermarking algorithm based on 1-D and 2-D chaotic sequences is proposed. The chaotic sequences have the advantages of massive, high security, and weakest correlation. The massive and independent digital watermark signals are generated through 1-D chaotic maps, which are determined by different initial conditions and parameters. The chaotic digital watermark signals effectively resolve the construction of massive watermarks with good performance. The embedding of multiple watermakrs is more complex than the single watermarking scheme. In this paper, each watermark is added to the middle frequency coefficients of wavelet domain randomly by exploiting 2-D chaotic system, so the embedding and extracting of each watermark would not disturb each other. Considering the parameters of 2-D chaotic systsem as the key to embedding procedure can prevent the watermarks to be removed maliciously, therefore the performance of security is better. The capacity of the multiple watermarking is also analyzed in this paper. The experimental results demonstrate that this proposed watermarking algorithm is robust to many common attacks and it is a reliable copyright protection for multiple legal owners.
Periodically sheared 2D Yukawa systems
Kovács, Anikó Zsuzsa; Hartmann, Peter; Donkó, Zoltán
2015-10-15
We present non-equilibrium molecular dynamics simulation studies on the dynamic (complex) shear viscosity of a 2D Yukawa system. We have identified a non-monotonic frequency dependence of the viscosity at high frequencies and shear rates, an energy absorption maximum (local resonance) at the Einstein frequency of the system at medium shear rates, an enhanced collective wave activity, when the excitation is near the plateau frequency of the longitudinal wave dispersion, and the emergence of significant configurational anisotropy at small frequencies and high shear rates.
ENERGY LANDSCAPE OF 2D FLUID FORMS
Y. JIANG; ET AL
2000-04-01
The equilibrium states of 2D non-coarsening fluid foams, which consist of bubbles with fixed areas, correspond to local minima of the total perimeter. (1) The authors find an approximate value of the global minimum, and determine directly from an image how far a foam is from its ground state. (2) For (small) area disorder, small bubbles tend to sort inwards and large bubbles outwards. (3) Topological charges of the same sign repel while charges of opposite sign attract. (4) They discuss boundary conditions and the uniqueness of the pattern for fixed topology.
Codon Constraints on Closed 2D Shapes,
2014-09-26
19843$ CODON CONSTRAINTS ON CLOSED 2D SHAPES Go Whitman Richards "I Donald D. Hoffman’ D T 18 Abstract: Codons are simple primitives for describing plane...RSONAL AUT"ORtIS) Richards, Whitman & Hoffman, Donald D. 13&. TYPE OF REPORT 13b. TIME COVERED N/A P8 AT F RRrT t~r. Ago..D,) is, PlE COUNT Reprint...outlines, if figure and ground are ignored. Later, we will address the problem of indexing identical codon descriptors that have different figure
Filtering of the Radon transform to enhance linear signal features via wavelet pyramid decomposition
NASA Astrophysics Data System (ADS)
Meckley, John R.
1995-09-01
The information content in many signal processing applications can be reduced to a set of linear features in a 2D signal transform. Examples include the narrowband lines in a spectrogram, ship wakes in a synthetic aperture radar image, and blood vessels in a medical computer-aided tomography scan. The line integrals that generate the values of the projections of the Radon transform can be characterized as a bank of matched filters for linear features. This localization of energy in the Radon transform for linear features can be exploited to enhance these features and to reduce noise by filtering the Radon transform with a filter explicitly designed to pass only linear features, and then reconstructing a new 2D signal by inverting the new filtered Radon transform (i.e., via filtered backprojection). Previously used methods for filtering the Radon transform include Fourier based filtering (a 2D elliptical Gaussian linear filter) and a nonlinear filter ((Radon xfrm)**y with y >= 2.0). Both of these techniques suffer from the mismatch of the filter response to the true functional form of the Radon transform of a line. The Radon transform of a line is not a point but is a function of the Radon variables (rho, theta) and the total line energy. This mismatch leads to artifacts in the reconstructed image and a reduction in achievable processing gain. The Radon transform for a line is computed as a function of angle and offset (rho, theta) and the line length. The 2D wavelet coefficients are then compared for the Haar wavelets and the Daubechies wavelets. These filter responses are used as frequency filters for the Radon transform. The filtering is performed on the wavelet pyramid decomposition of the Radon transform by detecting the most likely positions of lines in the transform and then by convolving the local area with the appropriate response and zeroing the pyramid coefficients outside of the response area. The response area is defined to contain 95% of the total
2003-02-01
Micchelli and Sauer have proposed to extend the Hölder notion of continuity to -space by introducing what they call generalized Lipschitz spaces [40]. Their...partitioning in hierarchical trees,” IEEE Trans. Circuits Syst. Video Technol., vol. 6, pp. 243–250, June 1996. [30] S. Jaffard, “Pointwise smoothness, two...Télécom Paris (ENST), in 1988. In 1996, he received the Ph.D degree in electrical engineering from ENST for a study on iterated rational filterbanks ap
A novel hybrid motion detection algorithm based on 2D histogram
NASA Astrophysics Data System (ADS)
Su, Xiaomeng; Wang, Haiying
2015-03-01
This article proposes a novel hybrid motion detection algorithm based on 2-D (2-Dimensional) spatio-temporal states histogram. The new algorithm combines the idea of image change detection based on 2-D histogram and spatio-temporal entropy image segmentation. It quantifies the continuity of pixel state in time and space domain which are called TDF (Time Domain Filter) and SDF (Space Domain Filter) respectively. After this, put both channels of output data from TDF and SDF into a 2-D histogram. In the 2-D histogram, a curve division method helps to separate the foreground state points and the background ones more accurately. Innovatively, the new algorithm converts the video sequence to its histogram sequence, and transforms the difference of pixel's value in the video sequence into the difference of pixel's position in the 2-D histogram. Experimental results on different types of scenes added Gaussian noise shows that the proposed technique has strong ability of detecting moving objects.
Remarks on thermalization in 2D CFT
NASA Astrophysics Data System (ADS)
de Boer, Jan; Engelhardt, Dalit
2016-12-01
We revisit certain aspects of thermalization in 2D conformal field theory (CFT). In particular, we consider similarities and differences between the time dependence of correlation functions in various states in rational and non-rational CFTs. We also consider the distinction between global and local thermalization and explain how states obtained by acting with a diffeomorphism on the ground state can appear locally thermal, and we review why the time-dependent expectation value of the energy-momentum tensor is generally a poor diagnostic of global thermalization. Since all 2D CFTs have an infinite set of commuting conserved charges, generic initial states might be expected to give rise to a generalized Gibbs ensemble rather than a pure thermal ensemble at late times. We construct the holographic dual of the generalized Gibbs ensemble and show that, to leading order, it is still described by a Banados-Teitelboim-Zanelli black hole. The extra conserved charges, while rendering c <1 theories essentially integrable, therefore seem to have little effect on large-c conformal field theories.
Microwave Assisted 2D Materials Exfoliation
NASA Astrophysics Data System (ADS)
Wang, Yanbin
Two-dimensional materials have emerged as extremely important materials with applications ranging from energy and environmental science to electronics and biology. Here we report our discovery of a universal, ultrafast, green, solvo-thermal technology for producing excellent-quality, few-layered nanosheets in liquid phase from well-known 2D materials such as such hexagonal boron nitride (h-BN), graphite, and MoS2. We start by mixing the uniform bulk-layered material with a common organic solvent that matches its surface energy to reduce the van der Waals attractive interactions between the layers; next, the solutions are heated in a commercial microwave oven to overcome the energy barrier between bulk and few-layers states. We discovered the minutes-long rapid exfoliation process is highly temperature dependent, which requires precise thermal management to obtain high-quality inks. We hypothesize a possible mechanism of this proposed solvo-thermal process; our theory confirms the basis of this novel technique for exfoliation of high-quality, layered 2D materials by using an as yet unknown role of the solvent.
Bingi, Jayachandra; Murukeshan, Vadakke Matham
2015-01-01
Laser speckle pattern is a granular structure formed due to random coherent wavelet interference and generally considered as noise in optical systems including photolithography. Contrary to this, in this paper, we use the speckle pattern to generate predictable and controlled Gaussian random structures and quasi-random structures photo-lithographically. The random structures made using this proposed speckle lithography technique are quantified based on speckle statistics, radial distribution function (RDF) and fast Fourier transform (FFT). The control over the speckle size, density and speckle clustering facilitates the successful fabrication of black silicon with different surface structures. The controllability and tunability of randomness makes this technique a robust method for fabricating predictable 2D Gaussian random structures and black silicon structures. These structures can enhance the light trapping significantly in solar cells and hence enable improved energy harvesting. Further, this technique can enable efficient fabrication of disordered photonic structures and random media based devices. PMID:26679513
Bingi, Jayachandra; Murukeshan, Vadakke Matham
2015-12-18
Laser speckle pattern is a granular structure formed due to random coherent wavelet interference and generally considered as noise in optical systems including photolithography. Contrary to this, in this paper, we use the speckle pattern to generate predictable and controlled Gaussian random structures and quasi-random structures photo-lithographically. The random structures made using this proposed speckle lithography technique are quantified based on speckle statistics, radial distribution function (RDF) and fast Fourier transform (FFT). The control over the speckle size, density and speckle clustering facilitates the successful fabrication of black silicon with different surface structures. The controllability and tunability of randomness makes this technique a robust method for fabricating predictable 2D Gaussian random structures and black silicon structures. These structures can enhance the light trapping significantly in solar cells and hence enable improved energy harvesting. Further, this technique can enable efficient fabrication of disordered photonic structures and random media based devices.
2-D or not 2-D, that is the question: A Northern California test
Mayeda, K; Malagnini, L; Phillips, W S; Walter, W R; Dreger, D
2005-06-06
Reliable estimates of the seismic source spectrum are necessary for accurate magnitude, yield, and energy estimation. In particular, how seismic radiated energy scales with increasing earthquake size has been the focus of recent debate within the community and has direct implications on earthquake source physics studies as well as hazard mitigation. The 1-D coda methodology of Mayeda et al. has provided the lowest variance estimate of the source spectrum when compared against traditional approaches that use direct S-waves, thus making it ideal for networks that have sparse station distribution. The 1-D coda methodology has been mostly confined to regions of approximately uniform complexity. For larger, more geophysically complicated regions, 2-D path corrections may be required. The complicated tectonics of the northern California region coupled with high quality broadband seismic data provides for an ideal ''apples-to-apples'' test of 1-D and 2-D path assumptions on direct waves and their coda. Using the same station and event distribution, we compared 1-D and 2-D path corrections and observed the following results: (1) 1-D coda results reduced the amplitude variance relative to direct S-waves by roughly a factor of 8 (800%); (2) Applying a 2-D correction to the coda resulted in up to 40% variance reduction from the 1-D coda results; (3) 2-D direct S-wave results, though better than 1-D direct waves, were significantly worse than the 1-D coda. We found that coda-based moment-rate source spectra derived from the 2-D approach were essentially identical to those from the 1-D approach for frequencies less than {approx}0.7-Hz, however for the high frequencies (0.7{le} f {le} 8.0-Hz), the 2-D approach resulted in inter-station scatter that was generally 10-30% smaller. For complex regions where data are plentiful, a 2-D approach can significantly improve upon the simple 1-D assumption. In regions where only 1-D coda correction is available it is still preferable over 2
Group theoretical methods and wavelet theory: coorbit theory and applications
NASA Astrophysics Data System (ADS)
Feichtinger, Hans G.
2013-05-01
theory of coorbit spaces,12, 13 established by the author jointly with K. Gröchenig. Starting from an integrable and irreducible representation of some locally compact group (such as the "ax+b"-group or the Heisenberg group) one can derive families of Banach spaces having natural atomic characterizations, or alternatively a continuous transform associated to it. So at the end function spaces of locally compact groups come into play, and their generic properties help to explain why and how it is possible to obtain (nonorthogonal) decompositions. While unification of these two groups was one important aspect of the approach given in the late 80th, it was also clear that this approach allows to formulate and exploit the analogy to Banach spaces of analytic functions invariant under the Moebius group have been at the heart in this context. Recent years have seen further new instances and generalizations. Among them shearlets or the Blaschke product should be mentioned here, and the increased interest in the connections between wavelet theory and complex analysis. The talk will try to summarize a few of the general principles which can be derived from the general theory, but also highlight the difference between the different groups and signal expansions arising from corresponding group representations. There is still a lot more to be done, also from the point of view of applications and the numerical realization of such non-orthogonal expansions.
Wavelet Local Extrema Applied to Image Processing
1992-12-01
The research project had two components. In the first part, we developed a numerical method, based on the wavelet transform , for the solution of...on the orthogonal wavelet transform , that adapts the computational resolution in space and time to the regularity of the solution. This scheme saves
Wavelet=Galerkin discretization of hyperbolic equations
Restrepo, J.M.; Leaf, G.K.
1994-12-31
The relative merits of the wavelet-Galerkin solution of hyperbolic partial differential equations, typical of geophysical problems, are quantitatively and qualitatively compared to traditional finite difference and Fourier-pseudo-spectral methods. The wavelet-Galerkin solution presented here is found to be a viable alternative to the two conventional techniques.
3D steerable wavelets in practice.
Chenouard, Nicolas; Unser, Michael
2012-11-01
We introduce a systematic and practical design for steerable wavelet frames in 3D. Our steerable wavelets are obtained by applying a 3D version of the generalized Riesz transform to a primary isotropic wavelet frame. The novel transform is self-reversible (tight frame) and its elementary constituents (Riesz wavelets) can be efficiently rotated in any 3D direction by forming appropriate linear combinations. Moreover, the basis functions at a given location can be linearly combined to design custom (and adaptive) steerable wavelets. The features of the proposed method are illustrated with the processing and analysis of 3D biomedical data. In particular, we show how those wavelets can be used to characterize directional patterns and to detect edges by means of a 3D monogenic analysis. We also propose a new inverse-problem formalism along with an optimization algorithm for reconstructing 3D images from a sparse set of wavelet-domain edges. The scheme results in high-quality image reconstructions which demonstrate the feature-reduction ability of the steerable wavelets as well as their potential for solving inverse problems.
Improvements of embedded zerotree wavelet (EZW) coding
NASA Astrophysics Data System (ADS)
Li, Jin; Cheng, Po-Yuen; Kuo, C.-C. Jay
1995-04-01
In this research, we investigate several improvements of embedded zerotree wavelet (EZW) coding. Several topics addressed include: the choice of wavelet transforms and boundary conditions, the use of arithmetic coder and arithmetic context and the design of encoding order for effective embedding. The superior performance of our improvements is demonstrated with extensive experimental results.
Quantum damped oscillator II: Bateman's Hamiltonian vs. 2D parabolic potential barrier
Chruscinski, Dariusz . E-mail: darch@phys.uni.torun.pl
2006-04-15
We show that quantum Bateman's system which arises in the quantization of a damped harmonic oscillator is equivalent to a quantum problem with 2D parabolic potential barrier known also as 2D inverted isotropic oscillator. It turns out that this system displays the family of complex eigenvalues corresponding to the poles of analytical continuation of the resolvent operator to the complex energy plane. It is shown that this representation is more suitable than the hyperbolic one used recently by Blasone and Jizba.
Using wavelets to learn pattern templates
NASA Astrophysics Data System (ADS)
Scott, Clayton D.; Nowak, Robert D.
2002-07-01
Despite the success of wavelet decompositions in other areas of statistical signal and image processing, current wavelet-based image models are inadequate for modeling patterns in images, due to the presence of unknown transformations (e.g., translation, rotation, location of lighting source) inherent in most pattern observations. In this paper we introduce a hierarchical wavelet-based framework for modeling patterns in digital images. This framework takes advantage of the efficient image representations afforded by wavelets, while accounting for unknown translation and rotation. Given a trained model, we can use this framework to synthesize pattern observations. If the model parameters are unknown, we can infer them from labeled training data using TEMPLAR (Template Learning from Atomic Representations), a novel template learning algorithm with linear complexity. TEMPLAR employs minimum description length (MDL) complexity regularization to learn a template with a sparse representation in the wavelet domain. We discuss several applications, including template learning, pattern classification, and image registration.
Finite element wavelets with improved quantitative properties
NASA Astrophysics Data System (ADS)
Nguyen, Hoang; Stevenson, Rob
2009-08-01
In [W. Dahmen, R. Stevenson, Element-by-element construction of wavelets satisfying stability and moment conditions, SIAM J. Numer. Anal. 37 (1) (1999) 319-352 (electronic)], finite element wavelets were constructed on polygonal domains or Lipschitz manifolds that are piecewise parametrized by mappings with constant Jacobian determinants. The wavelets could be arranged to have any desired order of cancellation properties, and they generated stable bases for the Sobolev spaces Hs for (or s<=1 on manifolds). Unfortunately, it appears that the quantitative properties of these wavelets are rather disappointing. In this paper, we modify the construction from the above-mentioned work to obtain finite element wavelets which are much better conditioned.
2D quantum gravity from quantum entanglement.
Gliozzi, F
2011-01-21
In quantum systems with many degrees of freedom the replica method is a useful tool to study the entanglement of arbitrary spatial regions. We apply it in a way that allows them to backreact. As a consequence, they become dynamical subsystems whose position, form, and extension are determined by their interaction with the whole system. We analyze, in particular, quantum spin chains described at criticality by a conformal field theory. Its coupling to the Gibbs' ensemble of all possible subsystems is relevant and drives the system into a new fixed point which is argued to be that of the 2D quantum gravity coupled to this system. Numerical experiments on the critical Ising model show that the new critical exponents agree with those predicted by the formula of Knizhnik, Polyakov, and Zamolodchikov.
Simulation of Yeast Cooperation in 2D.
Wang, M; Huang, Y; Wu, Z
2016-03-01
Evolution of cooperation has been an active research area in evolutionary biology in decades. An important type of cooperation is developed from group selection, when individuals form spatial groups to prevent them from foreign invasions. In this paper, we study the evolution of cooperation in a mixed population of cooperating and cheating yeast strains in 2D with the interactions among the yeast cells restricted to their small neighborhoods. We conduct a computer simulation based on a game theoretic model and show that cooperation is increased when the interactions are spatially restricted, whether the game is of a prisoner's dilemma, snow drifting, or mutual benefit type. We study the evolution of homogeneous groups of cooperators or cheaters and describe the conditions for them to sustain or expand in an opponent population. We show that under certain spatial restrictions, cooperator groups are able to sustain and expand as group sizes become large, while cheater groups fail to expand and keep them from collapse.
2D Electrostatic Actuation of Microshutter Arrays
NASA Technical Reports Server (NTRS)
Burns, Devin E.; Oh, Lance H.; Li, Mary J.; Jones, Justin S.; Kelly, Daniel P.; Zheng, Yun; Kutyrev, Alexander S.; Moseley, Samuel H.
2015-01-01
An electrostatically actuated microshutter array consisting of rotational microshutters (shutters that rotate about a torsion bar) were designed and fabricated through the use of models and experiments. Design iterations focused on minimizing the torsional stiffness of the microshutters, while maintaining their structural integrity. Mechanical and electromechanical test systems were constructed to measure the static and dynamic behavior of the microshutters. The torsional stiffness was reduced by a factor of four over initial designs without sacrificing durability. Analysis of the resonant behavior of the microshutter arrays demonstrates that the first resonant mode is a torsional mode occurring around 3000 Hz. At low vacuum pressures, this resonant mode can be used to significantly reduce the drive voltage necessary for actuation requiring as little as 25V. 2D electrostatic latching and addressing was demonstrated using both a resonant and pulsed addressing scheme.
Graphene suspensions for 2D printing
NASA Astrophysics Data System (ADS)
Soots, R. A.; Yakimchuk, E. A.; Nebogatikova, N. A.; Kotin, I. A.; Antonova, I. V.
2016-04-01
It is shown that, by processing a graphite suspension in ethanol or water by ultrasound and centrifuging, it is possible to obtain particles with thicknesses within 1-6 nm and, in the most interesting cases, 1-1.5 nm. Analogous treatment of a graphite suspension in organic solvent yields eventually thicker particles (up to 6-10 nm thick) even upon long-term treatment. Using the proposed ink based on graphene and aqueous ethanol with ethylcellulose and terpineol additives for 2D printing, thin (~5 nm thick) films with sheet resistance upon annealing ~30 MΩ/□ were obtained. With the ink based on aqueous graphene suspension, the sheet resistance was ~5-12 kΩ/□ for 6- to 15-nm-thick layers with a carrier mobility of ~30-50 cm2/(V s).
Canard configured aircraft with 2-D nozzle
NASA Technical Reports Server (NTRS)
Child, R. D.; Henderson, W. P.
1978-01-01
A closely-coupled canard fighter with vectorable two-dimensional nozzle was designed for enhanced transonic maneuvering. The HiMAT maneuver goal of a sustained 8g turn at a free-stream Mach number of 0.9 and 30,000 feet was the primary design consideration. The aerodynamic design process was initiated with a linear theory optimization minimizing the zero percent suction drag including jet effects and refined with three-dimensional nonlinear potential flow techniques. Allowances were made for mutual interference and viscous effects. The design process to arrive at the resultant configuration is described, and the design of a powered 2-D nozzle model to be tested in the LRC 16-foot Propulsion Wind Tunnel is shown.
Numerical Evaluation of 2D Ground States
NASA Astrophysics Data System (ADS)
Kolkovska, Natalia
2016-02-01
A ground state is defined as the positive radial solution of the multidimensional nonlinear problem
Wavelet transforms for electroencephalographic spike and seizure detection
NASA Astrophysics Data System (ADS)
Schiff, Steven J.; Milton, John G.
1993-11-01
The application of wavelet transforms (WT) to experimental data from the nervous system has been hindered by the lack of a straightforward method to handle noise. A noise reduction technique, developed recently for use in wavelet cluster analysis in cosmology and astronomy, is here adapted for electroencephalographic (EEG) time-series data. Noise is filtered using control surrogate data sets generated from randomized aspects of the original time-series. In this study, WT were applied to EEG data from human patients undergoing brain mapping with implanted subdural electrodes for the localization of epileptic seizure foci. EEG data in 1D were analyzed from individual electrodes, and 2D data from electrode grids. These techniques are a powerful means to identify epileptic spikes in such data, and offer a method to identity the onset and spatial extent of epileptic seizure foci. The method is readily applied to the detection of structure in stationary and non-stationary time-series from a variety of physical systems.
Metrology for graphene and 2D materials
NASA Astrophysics Data System (ADS)
Pollard, Andrew J.
2016-09-01
The application of graphene, a one atom-thick honeycomb lattice of carbon atoms with superlative properties, such as electrical conductivity, thermal conductivity and strength, has already shown that it can be used to benefit metrology itself as a new quantum standard for resistance. However, there are many application areas where graphene and other 2D materials, such as molybdenum disulphide (MoS2) and hexagonal boron nitride (h-BN), may be disruptive, areas such as flexible electronics, nanocomposites, sensing and energy storage. Applying metrology to the area of graphene is now critical to enable the new, emerging global graphene commercial world and bridge the gap between academia and industry. Measurement capabilities and expertise in a wide range of scientific areas are required to address this challenge. The combined and complementary approach of varied characterisation methods for structural, chemical, electrical and other properties, will allow the real-world issues of commercialising graphene and other 2D materials to be addressed. Here, examples of metrology challenges that have been overcome through a multi-technique or new approach are discussed. Firstly, the structural characterisation of defects in both graphene and MoS2 via Raman spectroscopy is described, and how nanoscale mapping of vacancy defects in graphene is also possible using tip-enhanced Raman spectroscopy (TERS). Furthermore, the chemical characterisation and removal of polymer residue on chemical vapour deposition (CVD) grown graphene via secondary ion mass spectrometry (SIMS) is detailed, as well as the chemical characterisation of iron films used to grow large domain single-layer h-BN through CVD growth, revealing how contamination of the substrate itself plays a role in the resulting h-BN layer. In addition, the role of international standardisation in this area is described, outlining the current work ongoing in both the International Organization of Standardization (ISO) and the
Wavelet assessment of cerebrospinal compensatory reserve and cerebrovascular pressure reactivity
NASA Astrophysics Data System (ADS)
Latka, M.; Turalska, M.; Kolodziej, W.; Latka, D.; West, B.
2006-03-01
We employ complex continuous wavelet transforms to develop a consistent mathematical framework capable of quantifying both cerebrospinal compensatory reserve and cerebrovascular pressure--reactivity. The wavelet gain, defined as the frequency dependent ratio of time averaged wavelet coefficients of intracranial (ICP) and arterial blood pressure (ABP) fluctuations, characterizes the dampening of spontaneous arterial blood oscillations. This gain is introduced as a novel measure of cerebrospinal compensatory reserve. For a group of 10 patients who died as a result of head trauma (Glasgow Outcome Scale GOS =1) the average gain is 0.45 calculated at 0.05 Hz significantly exceeds that of 16 patients with favorable outcome (GOS=2): with gain of 0.24 with p=4x10-5. We also study the dynamics of instantaneous phase difference between the fluctuations of the ABP and ICP time series. The time-averaged synchronization index, which depends upon frequency, yields the information about the stability of the phase difference and is used as a cerebrovascular pressure--reactivity index. The average phase difference for GOS=1 is close to zero in sharp contrast to the mean value of 30^o for patients with GOS=2. We hypothesize that in patients who died the impairment of cerebral autoregulation is followed by the break down of residual pressure reactivity.
A wavelet based approach to Solar-Terrestrial Coupling
NASA Astrophysics Data System (ADS)
Katsavrias, Ch.; Hillaris, A.; Preka-Papadema, P.
2016-05-01
Transient and recurrent solar activity drive geomagnetic disturbances; these are quantified (amongst others) by DST , AE indices time-series. Transient disturbances are related to the Interplanetary Coronal Mass Ejections (ICMEs) while recurrent disturbances are related to corotating interaction regions (CIR). We study the relationship of the geomagnetic disturbances to the solar wind drivers within solar cycle 23 where the drivers are represented by ICMEs and CIRs occurrence rate and compared to the DST and AE as follows: terms with common periodicity in both the geomagnetic disturbances and the solar drivers are, firstly, detected using continuous wavelet transform (CWT). Then, common power and phase coherence of these periodic terms are calculated from the cross-wavelet spectra (XWT) and wavelet-coherence (WTC) respectively. In time-scales of ≈27 days our results indicate an anti-correlation of the effects of ICMEs and CIRs on the geomagnetic disturbances. The former modulates the DST and AE time series during the cycle maximum the latter during periods of reduced solar activity. The phase relationship of these modulation is highly non-linear. Only the annual frequency component of the ICMEs is phase-locked with DST and AE. In time-scales of ≈1.3-1.7 years the CIR seem to be the dominant driver for both geomagnetic indices throughout the whole solar cycle 23.
Seamless multiresolution isosurfaces using wavelets
Udeshi, T.; Hudson, R.; Papka, M. E.
2000-04-11
Data sets that are being produced by today's simulations, such as the ones generated by DOE's ASCI program, are too large for real-time exploration and visualization. Therefore, new methods of visualizing these data sets need to be investigated. The authors present a method that combines isosurface representations of different resolutions into a seamless solution, virtually free of cracks and overlaps. The solution combines existing isosurface generation algorithms and wavelet theory to produce a real-time solution to multiple-resolution isosurfaces.
Wavelet Neural Network Using Multiple Wavelet Functions in Target Threat Assessment
Guo, Lihong; Duan, Hong
2013-01-01
Target threat assessment is a key issue in the collaborative attack. To improve the accuracy and usefulness of target threat assessment in the aerial combat, we propose a variant of wavelet neural networks, MWFWNN network, to solve threat assessment. How to select the appropriate wavelet function is difficult when constructing wavelet neural network. This paper proposes a wavelet mother function selection algorithm with minimum mean squared error and then constructs MWFWNN network using the above algorithm. Firstly, it needs to establish wavelet function library; secondly, wavelet neural network is constructed with each wavelet mother function in the library and wavelet function parameters and the network weights are updated according to the relevant modifying formula. The constructed wavelet neural network is detected with training set, and then optimal wavelet function with minimum mean squared error is chosen to build MWFWNN network. Experimental results show that the mean squared error is 1.23 × 10−3, which is better than WNN, BP, and PSO_SVM. Target threat assessment model based on the MWFWNN has a good predictive ability, so it can quickly and accurately complete target threat assessment. PMID:23509436
Discrimination of walking patterns using wavelet-based fractal analysis.
Sekine, Masaki; Tamura, Toshiyo; Akay, Metin; Fujimoto, Toshiro; Togawa, Tatsuo; Fukui, Yasuhiro
2002-09-01
In this paper, we attempted to classify the acceleration signals for walking along a corridor and on stairs by using the wavelet-based fractal analysis method. In addition, the wavelet-based fractal analysis method was used to evaluate the gait of elderly subjects and patients with Parkinson's disease. The triaxial acceleration signals were measured close to the center of gravity of the body while the subject walked along a corridor and up and down stairs continuously. Signal measurements were recorded from 10 healthy young subjects and 11 elderly subjects. For comparison, two patients with Parkinson's disease participated in the level walking. The acceleration signal in each direction was decomposed to seven detailed signals at different wavelet scales by using the discrete wavelet transform. The variances of detailed signals at scales 7 to 1 were calculated. The fractal dimension of the acceleration signal was then estimated from the slope of the variance progression. The fractal dimensions were significantly different among the three types of walking for individual subjects (p < 0.01) and showed a high reproducibility. Our results suggest that the fractal dimensions are effective for classifying the walking types. Moreover, the fractal dimensions were significantly higher for the elderly subjects than for the young subjects (p < 0.01). For the patients with Parkinson's disease, the fractal dimensions tended to be higher than those of healthy subjects. These results suggest that the acceleration signals change into a more complex pattern with aging and with Parkinson's disease, and the fractal dimension can be used to evaluate the gait of elderly subjects and patients with Parkinson's disease.
Low Cost 2-D Heatshield Materials
1982-03-05
fabric or tapes (i.e., the warp and fill yarns cross at right angles) do not provide the stretch and conformability characteristics necessary to...manufacture a tapewrapped heatshield which contains a shingle angle greater than a few degrees. This is a result of the continuous yarns in the...needed conformability since neither the warp or fill yarns are continuous. In addition, the material has the ability for limited stretch since movement
Saadi, Slami; Touiza, Maamar; Kharfi, Fayçal; Guessoum, Abderrezak
2013-12-01
In this work, we present a mixed software/hardware implementation of 2-D signals encoder/decoder using dyadic discrete wavelet transform (DWT) based on quadrature mirror filters (QMF); using fast wavelet Mallat's algorithm. This work is designed and compiled on the embedded development kit EDK6.3i, and the synthesis software, ISE6.3i, which is available with Xilinx Virtex-IIV2MB1000 FPGA. Huffman coding scheme is used to encode the wavelet coefficients so that they can be transmitted progressively through an Ethernet TCP/IP based connection. The possible reconfiguration can be exploited to attain higher performance. The design will be integrated with the neutron radiography system that is used with the Es-Salem research reactor.
Tracking of Ice Edges and Ice Floes by Wavelet Analysis of SAR Images
NASA Technical Reports Server (NTRS)
Liu, Antony K.; Martin, Seelye; Kwok, Ronald
1997-01-01
This paper demonstrates the use of wavelet transforms in the tracking of sequential ice features in the ERS-1 synthetic aperture radar (SAR) imagery, especially in situations where feature correlation techniques fail to yield reasonable results. Examples include the evolution of the St. Lawrence polynya and summer sea ice change in the Beaufort Sea. For the polynya, the evolution of the region of young ice growth surrounding a polynya can be easily tracked by wavelet analysis due to the large backscatter difference between the young and old ice. Also within the polynya, a 2D fast Fourier transform (FFT) is used to identify the extent of the Langmuir circulation region, which is coincident with the wave-agitated frazil ice growth region, where the sea ice experiences its fastest growth. Therefore, the combination of wavelet and FFT analysis of SAR images provides for the large-scale monitoring of different polynya features. For summer ice, previous work shows that this is the most difficult period for ice trackers due to the lack of features on the sea ice cover. The multiscale wavelet analysis shows that this method delineates the detailed floe shapes during this period, so that between consecutive images, the floe translation and rotation can be estimated.
Maximally Localized Radial Profiles for Tight Steerable Wavelet Frames.
Pad, Pedram; Uhlmann, Virginie; Unser, Michael
2016-03-22
A crucial component of steerable wavelets is the radial profile of the generating function in the frequency domain. In this work, we present an infinite-dimensional optimization scheme that helps us find the optimal profile for a given criterion over the space of tight frames. We consider two classes of criteria that measure the localization of the wavelet. The first class specifies the spatial localization of the wavelet profile, and the second that of the resulting wavelet coefficients. From these metrics and the proposed algorithm, we construct tight wavelet frames that are optimally localized and provide their analytical expression. In particular, one of the considered criterion helps us finding back the popular Simoncelli wavelet profile. Finally, the investigation of local orientation estimation, image reconstruction from detected contours in the wavelet domain, and denoising, indicate that optimizing wavelet localization improves the performance of steerable wavelets, since our new wavelets outperform the traditional ones.
Maximally Localized Radial Profiles for Tight Steerable Wavelet Frames.
Pad, Pedram; Uhlmann, Virginie; Unser, Michael
2016-05-01
A crucial component of steerable wavelets is the radial profile of the generating function in the frequency domain. In this paper, we present an infinite-dimensional optimization scheme that helps us find the optimal profile for a given criterion over the space of tight frames. We consider two classes of criteria that measure the localization of the wavelet. The first class specifies the spatial localization of the wavelet profile, and the second that of the resulting wavelet coefficients. From these metrics and the proposed algorithm, we construct tight wavelet frames that are optimally localized and provide their analytical expression. In particular, one of the considered criterion helps us finding back the popular Simoncelli wavelet profile. Finally, the investigation of local orientation estimation, image reconstruction from detected contours in the wavelet domain, and denoising indicate that optimizing wavelet localization improves the performance of steerable wavelets, since our new wavelets outperform the traditional ones.
DNN-state identification of 2D distributed parameter systems
NASA Astrophysics Data System (ADS)
Chairez, I.; Fuentes, R.; Poznyak, A.; Poznyak, T.; Escudero, M.; Viana, L.
2012-02-01
There are many examples in science and engineering which are reduced to a set of partial differential equations (PDEs) through a process of mathematical modelling. Nevertheless there exist many sources of uncertainties around the aforementioned mathematical representation. Moreover, to find exact solutions of those PDEs is not a trivial task especially if the PDE is described in two or more dimensions. It is well known that neural networks can approximate a large set of continuous functions defined on a compact set to an arbitrary accuracy. In this article, a strategy based on the differential neural network (DNN) for the non-parametric identification of a mathematical model described by a class of two-dimensional (2D) PDEs is proposed. The adaptive laws for weights ensure the 'practical stability' of the DNN-trajectories to the parabolic 2D-PDE states. To verify the qualitative behaviour of the suggested methodology, here a non-parametric modelling problem for a distributed parameter plant is analysed.
Dynamics of quasi 2D co-rotating vortex merger
NASA Astrophysics Data System (ADS)
Khandekar, Akshay G.
Merger of vortices is examined experimentally to compare the merger of slender parallel vortices generated coincidentally. It is known that like-sign vortices rotate around a common center of circulation and merger between the vortices may occur under certain conditions. This merger is dependent on the strength of the vortex circulation, distance of separation between the centers of the two vortices, ReGamma, and vorticity distribution. Quasi-2D experimental data is examined and merger relations are derived. The 2D experiments conducted in a vortex generator tank uses high aspect ratio rotating paddles. The vortex merger tank generates slender co-rotating vortices and are examined using PIV (Particle Image Velocimetry). Merger characteristics are compared at centerline, 25% span and 5% span for different circulation strengths. Symmetric and asymmetric mergers are studied and it is found that in both cases, the vortex pair rotates around an axis perpendicular to the plane of the vortex pair. Symmetric merger is seen to occur at the center between the two vortices whereas in asymmetric merger the stronger vortex breaks the weaker vortex filaments and continues to follow its path. Wall effects seem to have an effect of vortex braiding and vortex stretching. Closer to the wall, the merger time increases while the merged vortex dissipates faster than at the centerline.
2D NMR-spectroscopic screening reveals polyketides in ladybugs.
Deyrup, Stephen T; Eckman, Laura E; McCarthy, Patrick H; Smedley, Scott R; Meinwald, Jerrold; Schroeder, Frank C
2011-06-14
Small molecules of biological origin continue to yield the most promising leads for drug design, but systematic approaches for exploring nature's cache of structural diversity are lacking. Here, we demonstrate the use of 2D NMR spectroscopy to screen a library of biorationally selected insect metabolite samples for partial structures indicating the presence of new chemical entities. This NMR-spectroscopic survey enabled detection of novel compounds in complex metabolite mixtures without prior fractionation or isolation. Our screen led to discovery and subsequent isolation of two families of tricyclic pyrones in Delphastus catalinae, a tiny ladybird beetle that is employed commercially as a biological pest control agent. The D. catalinae pyrones are based on 23-carbon polyketide chains forming 1,11-dioxo-2,6,10-trioxaanthracene and 4,8-dioxo-1,9,13-trioxaanthracene derivatives, representing ring systems not previously found in nature. This study highlights the utility of 2D NMR-spectroscopic screening for exploring nature's structure space and suggests that insect metabolomes remain vastly underexplored.
2D NMR-spectroscopic screening reveals polyketides in ladybugs
Deyrup, Stephen T.; Eckman, Laura E.; McCarthy, Patrick H.; Smedley, Scott R.; Meinwald, Jerrold; Schroeder, Frank C.
2011-01-01
Small molecules of biological origin continue to yield the most promising leads for drug design, but systematic approaches for exploring nature’s cache of structural diversity are lacking. Here, we demonstrate the use of 2D NMR spectroscopy to screen a library of biorationally selected insect metabolite samples for partial structures indicating the presence of new chemical entities. This NMR-spectroscopic survey enabled detection of novel compounds in complex metabolite mixtures without prior fractionation or isolation. Our screen led to discovery and subsequent isolation of two families of tricyclic pyrones in Delphastus catalinae, a tiny ladybird beetle that is employed commercially as a biological pest control agent. The D. catalinae pyrones are based on 23-carbon polyketide chains forming 1,11-dioxo-2,6,10-trioxaanthracene and 4,8-dioxo-1,9,13-trioxaanthracene derivatives, representing ring systems not previously found in nature. This study highlights the utility of 2D NMR-spectroscopic screening for exploring nature’s structure space and suggests that insect metabolomes remain vastly underexplored. PMID:21646540
Unifying renormalization group and the continuous wavelet transform
NASA Astrophysics Data System (ADS)
Altaisky, M. V.
2016-05-01
It is shown that the renormalization group turns to be a symmetry group in a theory initially formulated in a space of scale-dependent functions, i.e., those depending on both the position x and the resolution a . Such a theory, earlier described in [1,2], is finite by construction. The space of scale-dependent functions {ϕa(x )} is more relevant to a physical reality than the space of square-integrable functions L2(Rd); because of the Heisenberg uncertainty principle, what is really measured in any experiment is always defined in a region rather than a point. The effective action Γ(A ) of our theory turns out to be complementary to the exact renormalization group effective action. The role of the regulator is played by the basic wavelet—an "aperture function" of a measuring device used to produce the snapshot of a field ϕ at the point x with the resolution a . The standard renormalization group results for ϕ4 model are reproduced.
Image coding with geometric wavelets.
Alani, Dror; Averbuch, Amir; Dekel, Shai
2007-01-01
This paper describes a new and efficient method for low bit-rate image coding which is based on recent development in the theory of multivariate nonlinear piecewise polynomial approximation. It combines a binary space partition scheme with geometric wavelet (GW) tree approximation so as to efficiently capture curve singularities and provide a sparse representation of the image. The GW method successfully competes with state-of-the-art wavelet methods such as the EZW, SPIHT, and EBCOT algorithms. We report a gain of about 0.4 dB over the SPIHT and EBCOT algorithms at the bit-rate 0.0625 bits-per-pixels (bpp). It also outperforms other recent methods that are based on "sparse geometric representation." For example, we report a gain of 0.27 dB over the Bandelets algorithm at 0.1 bpp. Although the algorithm is computationally intensive, its time complexity can be significantely reduced by collecting a "global" GW n-term approximation to the image from a collection of GW trees, each constructed separately over tiles of the image.
Detecting the BAO using Discrete Wavelet Packets
NASA Astrophysics Data System (ADS)
Garcia, Noel Anthony; Wu, Yunyun; Kadowaki, Kevin; Pando, Jesus
2017-01-01
We use wavelet packets to investigate the clustering of matter on galactic scales in search of the Baryon Acoustic Oscillations. We do so in two ways. We develop a wavelet packet approach to measure the power spectrum and apply this method to the CMASS galaxy catalogue from the Sloan Digital Sky Survey (SDSS). We compare the resulting power spectrum to published BOSS results by measuring a parameter β that compares our wavelet detected oscillations to the results from the SDSS collaboration. We find that β=1 indicating that our wavelet packet methods are detecting the BAO at a similar level as traditional Fourier techniques. We then use wavelet packets to decompose, denoise, and then reconstruct the galaxy density field. Using this denoised field, we compute the standard two-point correlation function. We are able to successfully detect the BAO at r ≈ 105 h-1 Mpc in line with previous SDSS results. We conclude that wavelet packets do reproduce the results of the key clustering statistics computed by other means. The wavelet packets show distinct advantages in suppressing high frequency noise and in keeping information localized.
Persistence Measures for 2d Soap Froth
NASA Astrophysics Data System (ADS)
Feng, Y.; Ruskin, H. J.; Zhu, B.
Soap froths as typical disordered cellular structures, exhibiting spatial and temporal evolution, have been studied through their distributions and topological properties. Recently, persistence measures, which permit representation of the froth as a two-phase system, have been introduced to study froth dynamics at different length scales. Several aspects of the dynamics may be considered and cluster persistence has been observed through froth experiment. Using a direct simulation method, we have investigated persistent properties in 2D froth both by monitoring the persistence of survivor cells, a topologically independent measure, and in terms of cluster persistence. It appears that the area fraction behavior for both survivor and cluster persistence is similar for Voronoi froth and uniform froth (with defects). Survivor and cluster persistent fractions are also similar for a uniform froth, particularly when geometries are constrained, but differences observed for the Voronoi case appear to be attributable to the strong topological dependency inherent in cluster persistence. Survivor persistence, on the other hand, depends on the number rather than size and position of remaining bubbles and does not exhibit the characteristic decay to zero.
SEM signal emulation for 2D patterns
NASA Astrophysics Data System (ADS)
Sukhov, Evgenii; Muelders, Thomas; Klostermann, Ulrich; Gao, Weimin; Braylovska, Mariya
2016-03-01
The application of accurate and predictive physical resist simulation is seen as one important use model for fast and efficient exploration of new patterning technology options, especially if fully qualified OPC models are not yet available at an early pre-production stage. The methodology of using a top-down CD-SEM metrology to extract the 3D resist profile information, such as the critical dimension (CD) at various resist heights, has to be associated with a series of presumptions which may introduce such small, but systematic CD errors. Ideally, the metrology effects should be carefully minimized during measurement process, or if possible be taken into account through proper metrology modeling. In this paper we discuss the application of a fast SEM signal emulation describing the SEM image formation. The algorithm is applied to simulated resist 3D profiles and produces emulated SEM image results for 1D and 2D patterns. It allows estimating resist simulation quality by comparing CDs which were extracted from the emulated and from the measured SEM images. Moreover, SEM emulation is applied for resist model calibration to capture subtle error signatures through dose and defocus. Finally, it should be noted that our SEM emulation methodology is based on the approximation of physical phenomena which are taking place in real SEM image formation. This approximation allows achieving better speed performance compared to a fully physical model.
Competing coexisting phases in 2D water
NASA Astrophysics Data System (ADS)
Zanotti, Jean-Marc; Judeinstein, Patrick; Dalla-Bernardina, Simona; Creff, Gaëlle; Brubach, Jean-Blaise; Roy, Pascale; Bonetti, Marco; Ollivier, Jacques; Sakellariou, Dimitrios; Bellissent-Funel, Marie-Claire
2016-05-01
The properties of bulk water come from a delicate balance of interactions on length scales encompassing several orders of magnitudes: i) the Hydrogen Bond (HBond) at the molecular scale and ii) the extension of this HBond network up to the macroscopic level. Here, we address the physics of water when the three dimensional extension of the HBond network is frustrated, so that the water molecules are forced to organize in only two dimensions. We account for the large scale fluctuating HBond network by an analytical mean-field percolation model. This approach provides a coherent interpretation of the different events experimentally (calorimetry, neutron, NMR, near and far infra-red spectroscopies) detected in interfacial water at 160, 220 and 250 K. Starting from an amorphous state of water at low temperature, these transitions are respectively interpreted as the onset of creation of transient low density patches of 4-HBonded molecules at 160 K, the percolation of these domains at 220 K and finally the total invasion of the surface by them at 250 K. The source of this surprising behaviour in 2D is the frustration of the natural bulk tetrahedral local geometry and the underlying very significant increase in entropy of the interfacial water molecules.
Competing coexisting phases in 2D water
Zanotti, Jean-Marc; Judeinstein, Patrick; Dalla-Bernardina, Simona; Creff, Gaëlle; Brubach, Jean-Blaise; Roy, Pascale; Bonetti, Marco; Ollivier, Jacques; Sakellariou, Dimitrios; Bellissent-Funel, Marie-Claire
2016-01-01
The properties of bulk water come from a delicate balance of interactions on length scales encompassing several orders of magnitudes: i) the Hydrogen Bond (HBond) at the molecular scale and ii) the extension of this HBond network up to the macroscopic level. Here, we address the physics of water when the three dimensional extension of the HBond network is frustrated, so that the water molecules are forced to organize in only two dimensions. We account for the large scale fluctuating HBond network by an analytical mean-field percolation model. This approach provides a coherent interpretation of the different events experimentally (calorimetry, neutron, NMR, near and far infra-red spectroscopies) detected in interfacial water at 160, 220 and 250 K. Starting from an amorphous state of water at low temperature, these transitions are respectively interpreted as the onset of creation of transient low density patches of 4-HBonded molecules at 160 K, the percolation of these domains at 220 K and finally the total invasion of the surface by them at 250 K. The source of this surprising behaviour in 2D is the frustration of the natural bulk tetrahedral local geometry and the underlying very significant increase in entropy of the interfacial water molecules. PMID:27185018
NASA Astrophysics Data System (ADS)
Cheng, Chingyun; Kangara, Jayampathi; Arakelyan, Ilya; Thomas, John
2016-05-01
We tune the dimensionality of a strongly interacting degenerate 6 Li Fermi gas from 2D to quasi-2D, by adjusting the radial confinement of pancake-shaped clouds to control the radial chemical potential. In the 2D regime with weak radial confinement, the measured pair binding energies are in agreement with 2D-BCS mean field theory, which predicts dimer pairing energies in the many-body regime. In the qausi-2D regime obtained with increased radial confinement, the measured pairing energy deviates significantly from 2D-BCS theory. In contrast to the pairing energy, the measured radii of the cloud profiles are not fit by 2D-BCS theory in either the 2D or quasi-2D regimes, but are fit in both regimes by a beyond mean field polaron-model of the free energy. Supported by DOE, ARO, NSF, and AFOSR.
Brechet, Laurent; Lucas, Marie-Françoise; Doncarli, Christian; Farina, Dario
2007-12-01
We propose a novel scheme for signal compression based on the discrete wavelet packet transform (DWPT) decompositon. The mother wavelet and the basis of wavelet packets were optimized and the wavelet coefficients were encoded with a modified version of the embedded zerotree algorithm. This signal dependant compression scheme was designed by a two-step process. The first (internal optimization) was the best basis selection that was performed for a given mother wavelet. For this purpose, three additive cost functions were applied and compared. The second (external optimization) was the selection of the mother wavelet based on the minimal distortion of the decoded signal given a fixed compression ratio. The mother wavelet was parameterized in the multiresolution analysis framework by the scaling filter, which is sufficient to define the entire decomposition in the orthogonal case. The method was tested on two sets of ten electromyographic (EMG) and ten electrocardiographic (ECG) signals that were compressed with compression ratios in the range of 50%-90%. For 90% compression ratio of EMG (ECG) signals, the percent residual difference after compression decreased from (mean +/- SD) 48.6 +/- 9.9% (21.5 +/- 8.4%) with discrete wavelet transform (DWT) using the wavelet leading to poorest performance to 28.4 +/- 3.0% (6.7 +/- 1.9%) with DWPT, with optimal basis selection and wavelet optimization. In conclusion, best basis selection and optimization of the mother wavelet through parameterization led to substantial improvement of performance in signal compression with respect to DWT and randon selection of the mother wavelet. The method provides an adaptive approach for optimal signal representation for compression and can thus be applied to any type of biomedical signal.
Wavelet Applications for Flight Flutter Testing
NASA Technical Reports Server (NTRS)
Lind, Rick; Brenner, Marty; Freudinger, Lawrence C.
1999-01-01
Wavelets present a method for signal processing that may be useful for analyzing responses of dynamical systems. This paper describes several wavelet-based tools that have been developed to improve the efficiency of flight flutter testing. One of the tools uses correlation filtering to identify properties of several modes throughout a flight test for envelope expansion. Another tool uses features in time-frequency representations of responses to characterize nonlinearities in the system dynamics. A third tool uses modulus and phase information from a wavelet transform to estimate modal parameters that can be used to update a linear model and reduce conservatism in robust stability margins.
Optical Planar Discrete Fourier and Wavelet Transforms
NASA Astrophysics Data System (ADS)
Cincotti, Gabriella; Moreolo, Michela Svaluto; Neri, Alessandro
2007-10-01
We present all-optical architectures to perform discrete wavelet transform (DWT), wavelet packet (WP) decomposition and discrete Fourier transform (DFT) using planar lightwave circuits (PLC) technology. Any compact-support wavelet filter can be implemented as an optical planar two-port lattice-form device, and different subband filtering schemes are possible to denoise, or multiplex optical signals. We consider both parallel and serial input cases. We design a multiport decoder/decoder that is able to generate/process optical codes simultaneously and a flexible logarithmic wavelength multiplexer, with flat top profile and reduced crosstalk.
Transionospheric signal detection with chirped wavelets
Doser, A.B.; Dunham, M.E.
1997-11-01
Chirped wavelets are utilized to detect dispersed signals in the joint time scale domain. Specifically, pulses that become dispersed by transmission through the ionosphere and are received by satellites as nonlinear chirps are investigated. Since the dispersion greatly lowers the signal to noise ratios, it is difficult to isolate the signals in the time domain. Satellite data are examined with discrete wavelet expansions. Detection is accomplished via a template matching threshold scheme. Quantitative experimental results demonstrate that the chirped wavelet detection scheme is successful in detecting the transionospheric pulses at very low signal to noise ratios.
Wavelet analysis of fusion plasma transients
Dose, V.; Venus, G.; Zohm, H.
1997-02-01
Analysis of transient signals in the diagnostic of fusion plasmas often requires the simultaneous consideration of their time and frequency information. The newly emerging technique of wavelet analysis contains both time and frequency domains. Therefore it can be a valuable tool for the analysis of transients. In this paper the basic method of wavelet analysis is described. As an example, wavelet analysis is applied to the well-known phenomena of mode locking and fishbone instability. The results quantify the current qualitative understanding of these events in terms of instantaneous frequencies and amplitudes and encourage applications of the method to other problems. {copyright} {ital 1997 American Institute of Physics.}
Graphene and Other 2D Colloids: Liquid Crystals and Macroscopic Fibers.
Liu, Yingjun; Xu, Zhen; Gao, Weiwei; Cheng, Zhengdong; Gao, Chao
2017-02-24
Two-dimensional colloidal nanomaterials are running into renaissance after the enlightening researches of graphene. Macroscopic one-dimensional fiber is an optimal ordered structural form to express the in-plane merits of 2D nanomaterials, and the formation of liquid crystals (LCs) allows the creation of continuous fibers. In the correlated system from LCs to fibers, understanding their macroscopic organizing behavior and transforming them into new solid fibers is greatly significant for applications. Herein, we retrospect the history of 2D colloids and discuss about the concept of 2D nanomaterial fibers in the context of LCs, elaborating the motivation, principle and possible strategies of fabrication. Then we highlight the creation, development and typical applications of graphene fibers. Additionally, the latest advances of other 2D nanomaterial fibers are also summarized. Finally, conclusions, challenges and perspectives are provided to show great expectations of better and more fibrous materials of 2D nanomaterials. This review gives a comprehensive retrospect of the past century-long effort about the whole development of 2D colloids, and plots a clear roadmap - "lamellar solid - LCs - macroscopic fibers - flexible devices", which will certainly open a new era of structural-multifunctional application for the conventional 2D colloids.
MRAG-I2D: Multi-resolution adapted grids for remeshed vortex methods on multicore architectures
NASA Astrophysics Data System (ADS)
Rossinelli, Diego; Hejazialhosseini, Babak; van Rees, Wim; Gazzola, Mattia; Bergdorf, Michael; Koumoutsakos, Petros
2015-05-01
We present MRAG-I2D, an open source software framework, for multiresolution simulations of two-dimensional, incompressible, viscous flows on multicore architectures. The spatiotemporal scales of the flow field are captured by remeshed vortex methods enhanced by high order average-interpolating wavelets and local time-stepping. The multiresolution solver of the Poisson equation relies on the development of a novel, tree-based multipole method. MRAG-I2D implements a number of HPC strategies to map efficiently the irregular computational workload of wavelet-adapted grids on multicore nodes. The capabilities of the present software are compared to the current state-of-the-art in terms of accuracy, compression rates and time-to-solution. Benchmarks include the inviscid evolution of an elliptical vortex, flow past an impulsively started cylinder at Re = 40- 40 000 and simulations of self-propelled anguilliform swimmers. The results indicate that the present software has the same or better accuracy than state-of-the-art solvers while it exhibits unprecedented performance in terms of time-to-solution.
2D discrete Fourier transform on sliding windows.
Park, Chun-Su
2015-03-01
Discrete Fourier transform (DFT) is the most widely used method for determining the frequency spectra of digital signals. In this paper, a 2D sliding DFT (2D SDFT) algorithm is proposed for fast implementation of the DFT on 2D sliding windows. The proposed 2D SDFT algorithm directly computes the DFT bins of the current window using the precalculated bins of the previous window. Since the proposed algorithm is designed to accelerate the sliding transform process of a 2D input signal, it can be directly applied to computer vision and image processing applications. The theoretical analysis shows that the computational requirement of the proposed 2D SDFT algorithm is the lowest among existing 2D DFT algorithms. Moreover, the output of the 2D SDFT is mathematically equivalent to that of the traditional DFT at all pixel positions.
50 CFR Table 2d to Part 660... - At-Sea Whiting Fishery Annual Set-Asides, 2014 and Beyond
Code of Federal Regulations, 2014 CFR
2014-10-01
... 50 Wildlife and Fisheries 13 2014-10-01 2014-10-01 false At-Sea Whiting Fishery Annual Set-Asides, 2014 and Beyond 2d Table 2d to Part 660, Subpart C Wildlife and Fisheries FISHERY CONSERVATION AND MANAGEMENT, NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE (CONTINUED) FISHERIES...
MAGNUM2D. Radionuclide Transport Porous Media
Langford, D.W.; Baca, R.G.
1989-03-01
MAGNUM2D was developed to analyze thermally driven fluid motion in the deep basalts below the Paco Basin at the Westinghouse Hanford Site. Has been used in the Basalt Waste Isolation Project to simulate nonisothermal groundwater flow in a heterogeneous anisotropic medium and heat transport in a water/rock system near a high level nuclear waste repository. Allows three representations of the hydrogeologic system: an equivalent porous continuum, a system of discrete, unfilled, and interconnecting fractures separated by impervious rock mass, and a low permeability porous continuum with several discrete, unfilled fractures traversing the medium. The calculations assume local thermodynamic equilibrium between the rock and groundwater, nonisothermal Darcian flow in the continuum portions of the rock, and nonisothermal Poiseuille flow in discrete unfilled fractures. In addition, the code accounts for thermal loading within the elements, zero normal gradient and fixed boundary conditions for both temperature and hydraulic head, and simulation of the temperature and flow independently. The Q2DGEOM preprocessor was developed to generate, modify, plot and verify quadratic two dimensional finite element geometries. The BCGEN preprocessor generates the boundary conditions for head and temperature and ICGEN generates the initial conditions. The GRIDDER postprocessor interpolates nonregularly spaced nodal flow and temperature data onto a regular rectangular grid. CONTOUR plots and labels contour lines for a function of two variables and PARAM plots cross sections and time histories for a function of time and one or two spatial variables. NPRINT generates data tables that display the data along horizontal or vertical cross sections. VELPLT differentiates the hydraulic head and buoyancy data and plots the velocity vectors. The PATH postprocessor plots flow paths and computes the corresponding travel times.
MAGNUM2D. Radionuclide Transport Porous Media
Langford, D.W.; Baca, R.G.
1988-08-01
MAGNUM2D was developed to analyze thermally driven fluid motion in the deep basalts below the Paco Basin at the Westinghouse Hanford Site. Has been used in the Basalt Waste Isolation Project to simulate nonisothermal groundwater flow in a heterogeneous anisotropic medium and heat transport in a water/rock system near a high level nuclear waste repository. Allows three representations of the hydrogeologic system: an equivalent porous continuum, a system of discrete, unfilled, and interconnecting fractures separated by impervious rock mass, and a low permeability porous continuum with several discrete, unfilled fractures traversing the medium. The calculation assumes local thermodynamic equilibrium between the rock and groundwater, nonisothermal Darcian flow in the continuum portions of the rock, and nonisothermal Poiseuille flow in discrete unfilled fractures. In addition, the code accounts for thermal loading within the elements, zero normal gradient and fixed boundary conditions for both temperature and hydraulic head, and simulation of the temperature and flow independently. The Q2DGEOM preprocessor was developed to generate, modify, plot and verify quadratic two dimensional finite element geometries. The BCGEN preprocessor generates the boundary conditions for head and temperature and ICGEN generates the initial conditions. The GRIDDER postprocessor interpolates nonregularly spaced nodal flow and temperature data onto a regular rectangular grid. CONTOUR plots and labels contour lines for a function of two variables and PARAM plots cross sections and time histories for a function of time and one or two spatial variables. NPRINT generates data tables that display the data along horizontal or vertical cross sections. VELPLT differentiates the hydraulic head and buoyancy data and plots the velocity vectors. The PATH postprocessor plots flow paths and computes the corresponding travel times.
Serial identification of EEG patterns using adaptive wavelet-based analysis
NASA Astrophysics Data System (ADS)
Nazimov, A. I.; Pavlov, A. N.; Nazimova, A. A.; Grubov, V. V.; Koronovskii, A. A.; Sitnikova, E.; Hramov, A. E.
2013-10-01
A problem of recognition specific oscillatory patterns in the electroencephalograms with the continuous wavelet-transform is discussed. Aiming to improve abilities of the wavelet-based tools we propose a serial adaptive method for sequential identification of EEG patterns such as sleep spindles and spike-wave discharges. This method provides an optimal selection of parameters based on objective functions and enables to extract the most informative features of the recognized structures. Different ways of increasing the quality of patterns recognition within the proposed serial adaptive technique are considered.
Fractal Markets Hypothesis and the Global Financial Crisis: Wavelet Power Evidence
NASA Astrophysics Data System (ADS)
Kristoufek, Ladislav
2013-10-01
We analyze whether the prediction of the fractal markets hypothesis about a dominance of specific investment horizons during turbulent times holds. To do so, we utilize the continuous wavelet transform analysis and obtained wavelet power spectra which give the crucial information about the variance distribution across scales and its evolution in time. We show that the most turbulent times of the Global Financial Crisis can be very well characterized by the dominance of short investment horizons which is in hand with the assertions of the fractal markets hypothesis.
Generates 2D Input for DYNA NIKE & TOPAZ
Hallquist, J. O.; Sanford, Larry
1996-07-15
MAZE is an interactive program that serves as an input and two-dimensional mesh generator for DYNA2D, NIKE2D, TOPAZ2D, and CHEMICAL TOPAZ2D. MAZE also generates a basic template for ISLAND input. MAZE has been applied to the generation of input data to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.
MAZE96. Generates 2D Input for DYNA NIKE & TOPAZ
Sanford, L.; Hallquist, J.O.
1992-02-24
MAZE is an interactive program that serves as an input and two-dimensional mesh generator for DYNA2D, NIKE2D, TOPAZ2D, and CHEMICAL TOPAZ2D. MAZE also generates a basic template for ISLAND input. MAZE has been applied to the generation of input data to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.
NIKE2D96. Static & Dynamic Response of 2D Solids
Raboin, P.; Engelmann, B.; Halquist, J.O.
1992-01-24
NIKE2D is an implicit finite-element code for analyzing the finite deformation, static and dynamic response of two-dimensional, axisymmetric, plane strain, and plane stress solids. The code is fully vectorized and available on several computing platforms. A number of material models are incorporated to simulate a wide range of material behavior including elasto-placicity, anisotropy, creep, thermal effects, and rate dependence. Slideline algorithms model gaps and sliding along material interfaces, including interface friction, penetration and single surface contact. Interactive-graphics and rezoning is included for analyses with large mesh distortions. In addition to quasi-Newton and arc-length procedures, adaptive algorithms can be defined to solve the implicit equations using the solution language ISLAND. Each of these capabilities and more make NIKE2D a robust analysis tool.
Ultrasonic vibration dectection with wavelets: preliminary results.
Plett, Melani; Beach, Kirk W
2005-03-01
Several arterial disorders are known to cause systolic audio vibrations in tissue: they include stenoses, vasospasm, aneurysms, bleeds and arteriovenous fistulas. High-amplitude vibrations can be discovered with conventional Doppler ultrasound (US) instruments; however, differentiating brief, low-amplitude vibrations from other nonstationary echo sources is difficult. Further, characterizing the frequency and amplitude of vibrations is not feasible with conventional Doppler US. The automated detection and estimation of both the frequency and amplitude of vibrations with durations less than 100 ms and amplitudes of a micrometer or less have remained a signal-processing challenge. These vibrations may be associated with both nonstationary colored noise and strong low-frequency clutter. The normalized continuous Morlet wavelet power-spectrum analysis of quadrature Doppler echoes, followed by a binary hypothesis test for noise, results in simulated detection rates above 99.9%, with 0.1% false alarms for signal-on signal-to-noise ratios (SNRs) as low as one. Two clinical examples are included.
Lossless wavelet compression on medical image
NASA Astrophysics Data System (ADS)
Zhao, Xiuying; Wei, Jingyuan; Zhai, Linpei; Liu, Hong
2006-09-01
An increasing number of medical imagery is created directly in digital form. Such as Clinical image Archiving and Communication Systems (PACS), as well as telemedicine networks require the storage and transmission of this huge amount of medical image data. Efficient compression of these data is crucial. Several lossless and lossy techniques for the compression of the data have been proposed. Lossless techniques allow exact reconstruction of the original imagery, while lossy techniques aim to achieve high compression ratios by allowing some acceptable degradation in the image. Lossless compression does not degrade the image, thus facilitating accurate diagnosis, of course at the expense of higher bit rates, i.e. lower compression ratios. Various methods both for lossy (irreversible) and lossless (reversible) image compression are proposed in the literature. The recent advances in the lossy compression techniques include different methods such as vector quantization. Wavelet coding, neural networks, and fractal coding. Although these methods can achieve high compression ratios (of the order 50:1, or even more), they do not allow reconstructing exactly the original version of the input data. Lossless compression techniques permit the perfect reconstruction of the original image, but the achievable compression ratios are only of the order 2:1, up to 4:1. In our paper, we use a kind of lifting scheme to generate truly loss-less non-linear integer-to-integer wavelet transforms. At the same time, we exploit the coding algorithm producing an embedded code has the property that the bits in the bit stream are generated in order of importance, so that all the low rate codes are included at the beginning of the bit stream. Typically, the encoding process stops when the target bit rate is met. Similarly, the decoder can interrupt the decoding process at any point in the bit stream, and still reconstruct the image. Therefore, a compression scheme generating an embedded code can
NASA Astrophysics Data System (ADS)
Andre, Julia; Kiremidjian, Anne; Liao, Yizheng; Georgakis, Christos; Rajagopal, Ram
2016-04-01
Ice accretion on cables of bridge structures poses serious risk to the structure as well as to vehicular traffic when the ice falls onto the road. Detection of ice formation, quantification of the amount of ice accumulated, and prediction of icefalls will increase the safety and serviceability of the structure. In this paper, an ice accretion detection algorithm is presented based on the Continuous Wavelet Transform (CWT). In the proposed algorithm, the acceleration signals obtained from bridge cables are transformed using wavelet method. The damage sensitive features (DSFs) are defined as a function of the wavelet energy at specific wavelet scales. It is found that as ice accretes on the cables, the mass of cable increases, thus changing the wavelet energies. Hence, the DSFs can be used to track the change of cables mass. To validate the proposed algorithm, we use the data collected from a laboratory experiment conducted at the Technical University of Denmark (DTU). In this experiment, a cable was placed in a wind tunnel as ice volume grew progressively. Several accelerometers were installed at various locations along the testing cable to collect vibration signals.
Thermally Conductive Structural 2D Composite Materials
2012-08-14
5 Figure 3. Micrographs of Carbon Nanostructures Grown on Carbon Fibers Using Microwave Generated Plasmas at MSU...methods provided in literature, however, utilize a microwave plasma technique, not conducive to continuous manufacturing. Therefore, in the current work...carbon fibers per the methodologies reported by Bhuvana et al. [1], which used microwave plasma chemical vapor deposition. The MSU unit is a “cold
CW-THz image contrast enhancement using wavelet transform and Retinex
NASA Astrophysics Data System (ADS)
Chen, Lin; Zhang, Min; Hu, Qi-fan; Huang, Ying-Xue; Liang, Hua-Wei
2015-10-01
To enhance continuous wave terahertz (CW-THz) scanning images contrast and denoising, a method based on wavelet transform and Retinex theory was proposed. In this paper, the factors affecting the quality of CW-THz images were analysed. Second, an approach of combination of the discrete wavelet transform (DWT) and a designed nonlinear function in wavelet domain for the purpose of contrast enhancing was applied. Then, we combine the Retinex algorithm for further contrast enhancement. To evaluate the effectiveness of the proposed method in qualitative and quantitative, it was compared with the adaptive histogram equalization method, the homomorphic filtering method and the SSR(Single-Scale-Retinex) method. Experimental results demonstrated that the presented algorithm can effectively enhance the contrast of CW-THZ image and obtain better visual effect.
Smart-phone based electrocardiogram wavelet decomposition and neural network classification
NASA Astrophysics Data System (ADS)
Jannah, N.; Hadjiloucas, S.; Hwang, F.; Galvão, R. K. H.
2013-06-01
This paper discusses ECG classification after parametrizing the ECG waveforms in the wavelet domain. The aim of the work is to develop an accurate classification algorithm that can be used to diagnose cardiac beat abnormalities detected using a mobile platform such as smart-phones. Continuous time recurrent neural network classifiers are considered for this task. Records from the European ST-T Database are decomposed in the wavelet domain using discrete wavelet transform (DWT) filter banks and the resulting DWT coefficients are filtered and used as inputs for training the neural network classifier. Advantages of the proposed methodology are the reduced memory requirement for the signals which is of relevance to mobile applications as well as an improvement in the ability of the neural network in its generalization ability due to the more parsimonious representation of the signal to its inputs.
A new edge detection based on pyramid-structure wavelet transform
NASA Astrophysics Data System (ADS)
Yi, Sheng; Cao, Hanqiang; Li, Xutao; Liu, Miao
2006-05-01
Many advance image processing, like segmentation and recognition, are based on contour extraction which usually lack of ability to allocate edge precisely in the image of heavy noise with low computation burden. For such problem, in this paper, we proposed a new approach of edge detection based on pyramid-structure wavelet transform. In order to suppress noise and keep good continuity of edge, the proposed edge representation considered both inter-correlations across the multi-scales and intra-correlations within the single-scale. The former one is described by point-wise singularity. The later one is described by the magnitude and ratio of wavelet coefficients in different sub-bands. Based on such edge modeling, the edge point allocation is then complemented in wavelet domain by synthesizing the edge information in multi-scales. The experimental results shows that our approaches achieve the pixel-level edge detection with strong resistant against noise due to scattering in water.
Wavelet differential neural network observer.
Chairez, Isaac
2009-09-01
State estimation for uncertain systems affected by external noises is an important problem in control theory. This paper deals with a state observation problem when the dynamic model of a plant contains uncertainties or it is completely unknown. Differential neural network (NN) approach is applied in this uninformative situation but with activation functions described by wavelets. A new learning law, containing an adaptive adjustment rate, is suggested to imply the stability condition for the free parameters of the observer. Nominal weights are adjusted during the preliminary training process using the least mean square (LMS) method. Lyapunov theory is used to obtain the upper bounds for the weights dynamics as well as for the mean squared estimation error. Two numeric examples illustrate this approach: first, a nonlinear electric system, governed by the Chua's equation and second the Lorentz oscillator. Both systems are assumed to be affected by external perturbations and their parameters are unknown.
Nonuniform spatially adaptive wavelet packets
NASA Astrophysics Data System (ADS)
Carre, Philippe; Fernandez-Maloigne, Christine
2000-12-01
In this paper, we propose a new decomposition scheme for spatially adaptive wavelet packets. Contrary to the double tree algorithm, our method is non-uniform and shift- invariant in the time and frequency domains, and is minimal for an information cost function. We prose some-restrictions to our algorithm to reduce the complexity and permitting us to provide some time-frequency partitions of the signal in agreement with its structure. This new 'totally' non-uniform transform, more adapted than Malvar, Packets or dyadic double-tree decomposition, allows the study of all possible time-frequency partitions with the only restriction that the blocks are rectangular. It permits one to obtain a satisfying Time-Frequency representation, and is applied for the study of EEG signals.
Wavelet filtering for data recovery
NASA Astrophysics Data System (ADS)
Schmidt, W.
2013-09-01
In case of electrical wave measurements in space instruments, digital filtering and data compression on board can significantly enhance the signal and reduce the amount of data to be transferred to Earth. While often the instrument's transfer function is well known making the application of an optimized wavelet algorithm feasible the computational power requirements may be prohibitive as normally complex floating point operations are needed. This article presents a simplified possibility implemented in low-power 16-bit integer processors used for plasma wave measurements in the SPEDE instrument on SMART-1 and for the Permittivity Probe measurements of the SESAME/PP instrument in Rosetta's Philae Lander on its way to comet 67P/Churyumov-Gerasimenko.
Hsu, Wei-Yen
2013-04-01
An electroencephalogram (EEG) analysis system is proposed for single-trial classification of motor imagery (MI) data in this study. Applying event-related brain potential (ERP) data acquired from the sensorimotor cortices, the system mainly consists of enhanced active segment selection, feature extraction, feature selection and classification. In addition to the original use of continuous wavelet transform (CWT) and Student's two-sample t-statistics, the 2D anisotropic Gaussian filter is proposed to further refine the selection of active segments. We then extract several features, including spectral power and asymmetry ratio, coherence and phase-locking value, and multiresolution fractal feature vector, for subsequent classification. Next, genetic algorithm (GA) is used to select features from the combination of above-mentioned features. Finally, support vector machine (SVM) is used for classification. Compared with "without enhanced active segment selection," several potential features and linear discriminant analysis (LDA) on MI data from two data sets for 10 subjects, the results indicate that the proposed method achieves 86.7% average classification accuracy, which is promising in BCI applications.
Signal Approximation with a Wavelet Neural Network
1992-12-01
specialized electronic devices like the Intel Electronically Trainable Analog Neural Network (ETANN) chip. The WNN representation allows the...accurately approximated with a WNN trained with irregularly sampled data. Signal approximation, Wavelet neural network .
Digital transceiver implementation for wavelet packet modulation
NASA Astrophysics Data System (ADS)
Lindsey, Alan R.; Dill, Jeffrey C.
1998-03-01
Current transceiver designs for wavelet-based communication systems are typically reliant on analog waveform synthesis, however, digital processing is an important part of the eventual success of these techniques. In this paper, a transceiver implementation is introduced for the recently introduced wavelet packet modulation scheme which moves the analog processing as far as possible toward the antenna. The transceiver is based on the discrete wavelet packet transform which incorporates level and node parameters for generalized computation of wavelet packets. In this transform no particular structure is imposed on the filter bank save dyadic branching, and a maximum level which is specified a priori and dependent mainly on speed and/or cost considerations. The transmitter/receiver structure takes a binary sequence as input and, based on the desired time- frequency partitioning, processes the signal through demultiplexing, synthesis, analysis, multiplexing and data determination completely in the digital domain - with exception of conversion in and out of the analog domain for transmission.
Wavelet Analysis for Acoustic Phased Array
NASA Astrophysics Data System (ADS)
Kozlov, Inna; Zlotnick, Zvi
2003-03-01
Wavelet spectrum analysis is known to be one of the most powerful tools for exploring quasistationary signals. In this paper we use wavelet technique to develop a new Direction Finding (DF) Algorithm for the Acoustic Phased Array (APA) systems. Utilising multi-scale analysis of libraries of wavelets allows us to work with frequency bands instead of individual frequency of an acoustic source. These frequency bands could be regarded as features extracted from quasistationary signals emitted by a noisy object. For detection, tracing and identification of a sound source in a noisy environment we develop smart algorithm. The essential part of this algorithm is a special interacting procedure of the above-mentioned DF-algorithm and the wavelet-based Identification (ID) algorithm developed in [4]. Significant improvement of the basic properties of a receiving APA pattern is achieved.
Wavelet-based acoustic recognition of aircraft
Dress, W.B.; Kercel, S.W.
1994-09-01
We describe a wavelet-based technique for identifying aircraft from acoustic emissions during take-off and landing. Tests show that the sensor can be a single, inexpensive hearing-aid microphone placed close to the ground the paper describes data collection, analysis by various technique, methods of event classification, and extraction of certain physical parameters from wavelet subspace projections. The primary goal of this paper is to show that wavelet analysis can be used as a divide-and-conquer first step in signal processing, providing both simplification and noise filtering. The idea is to project the original signal onto the orthogonal wavelet subspaces, both details and approximations. Subsequent analysis, such as system identification, nonlinear systems analysis, and feature extraction, is then carried out on the various signal subspaces.
Contour detection based on wavelet differentiation
NASA Astrophysics Data System (ADS)
Bezuglov, D.; Kuzin, A.; Voronin, V.
2016-05-01
This work proposes a novel algorithm for contour detection based on high-performance algorithm of wavelet analysis for multimedia applications. To solve the noise effect on the result of peaking in this paper we consider the direct and inverse wavelet differentiation. Extensive experimental evaluation on noisy images demonstrates that our contour detection method significantly outperform competing algorithms. The proposed algorithm provides a means of coupling our system to recognition application such as detection and identification of vehicle number plate.
EEG Multiresolution Analysis Using Wavelet Transform
2007-11-02
Wavelet transform (WT) is a new multiresolution time-frequency analysis method. WT possesses well localization feature both in tine and frequency...plays a key role in the diagnosing diseases and is useful for both physiological research and medical applications. Using the dyadic wavelet ... transform the EEG signals are successfully decomposed to the alpha rhythm (8-13Hz) beta rhythm (14-30Hz) theta rhythm (4-7Hz) and delta rhythm (0.3-3Hz) and
A Wavelet Model for Vocalic Speech Coarticulation
1994-10-01
128 Figure 8. 1 Wavelet Transforms of the /d/ words: /did/, / dmd /, /d~d/, /dud/........................... 134 x Figure 8.2 Wavelet Transforms of... Kennedy (1967) used synthetic CVC syllables to demonstrate the influence of adjacent consonants on the perception of the vowel. A series of vowel sounds...34 The Journal of the Acoustical Society of America 35(11), pp. 1773-1781. 172 Lindblom, B.E.F. and Studdert- Kennedy , M. (1967). "On the Role of Formant
On a Wavelet-Based Method for the Numerical Simulation of Wave Propagation
NASA Astrophysics Data System (ADS)
Hong, Tae-Kyung; Kennett, B. L. N.
2002-12-01
A wavelet-based method for the numerical simulation of acoustic and elastic wave propagation is developed. Using a displacement-velocity formulation and treating spatial derivatives with linear operators, the wave equations are rewritten as a system of equations whose evolution in time is controlled by first-order derivatives. The linear operators for spatial derivatives are implemented in wavelet bases using an operator projection technique with nonstandard forms of wavelet transform. Using a semigroup approach, the discretized solution in time can be represented in an explicit recursive form, based on Taylor expansion of exponential functions of operator matrices. The boundary conditions are implemented by augmenting the system of equations with equivalent force terms at the boundaries. The wavelet-based method is applied to the acoustic wave equation with rigid boundary conditions at both ends in 1-D domain and to the elastic wave equation with a traction-free boundary conditions at a free surface in 2-D spatial media. The method can be applied directly to media with plane surfaces, and surface topography can be included with the aid of distortion of the grid describing the properties of the medium. The numerical results are compared with analytic solutions based on the Cagniard technique and show high accuracy. The wavelet-based approach is also demonstrated for complex media including highly varying topography or stochastic heterogeneity with rapid variations in physical parameters. These examples indicate the value of the approach as an accurate and stable tool for the simulation of wave propagation in general complex media.
Optimal wavelet denoising for smart biomonitor systems
NASA Astrophysics Data System (ADS)
Messer, Sheila R.; Agzarian, John; Abbott, Derek
2001-03-01
Future smart-systems promise many benefits for biomedical diagnostics. The ideal is for simple portable systems that display and interpret information from smart integrated probes or MEMS-based devices. In this paper, we will discuss a step towards this vision with a heart bio-monitor case study. An electronic stethoscope is used to record heart sounds and the problem of extracting noise from the signal is addressed via the use of wavelets and averaging. In our example of heartbeat analysis, phonocardiograms (PCGs) have many advantages in that they may be replayed and analysed for spectral and frequency information. Many sources of noise may pollute a PCG including foetal breath sounds if the subject is pregnant, lung and breath sounds, environmental noise and noise from contact between the recording device and the skin. Wavelets can be employed to denoise the PCG. The signal is decomposed by a discrete wavelet transform. Due to the efficient decomposition of heart signals, their wavelet coefficients tend to be much larger than those due to noise. Thus, coefficients below a certain level are regarded as noise and are thresholded out. The signal can then be reconstructed without significant loss of information in the signal. The questions that this study attempts to answer are which wavelet families, levels of decomposition, and thresholding techniques best remove the noise in a PCG. The use of averaging in combination with wavelet denoising is also addressed. Possible applications of the Hilbert Transform to heart sound analysis are discussed.
Trabecular bone texture classification using wavelet leaders
NASA Astrophysics Data System (ADS)
Zou, Zilong; Yang, Jie; Megalooikonomou, Vasileios; Jennane, Rachid; Cheng, Erkang; Ling, Haibin
2016-03-01
In this paper we propose to use the Wavelet Leader (WL) transformation for studying trabecular bone patterns. Given an input image, its WL transformation is defined as the cross-channel-layer maximum pooling of an underlying wavelet transformation. WL inherits the advantage of the original wavelet transformation in capturing spatial-frequency statistics of texture images, while being more robust against scale and orientation thanks to the maximum pooling strategy. These properties make WL an attractive alternative to replace wavelet transformations which are used for trabecular analysis in previous studies. In particular, in this paper, after extracting wavelet leader descriptors from a trabecular texture patch, we feed them into two existing statistic texture characterization methods, namely the Gray Level Co-occurrence Matrix (GLCM) and the Gray Level Run Length Matrix (GLRLM). The most discriminative features, Energy of GLCM and Gray Level Non-Uniformity of GLRLM, are retained to distinguish two different populations between osteoporotic patients and control subjects. Receiver Operating Characteristics (ROC) curves are used to measure performance of classification. Experimental results on a recently released benchmark dataset show that WL significantly boosts the performance of baseline wavelet transformations by 5% in average.
Fast wavelet estimation of weak biosignals.
Causevic, Elvir; Morley, Robert E; Wickerhauser, M Victor; Jacquin, Arnaud E
2005-06-01
Wavelet-based signal processing has become commonplace in the signal processing community over the past decade and wavelet-based software tools and integrated circuits are now commercially available. One of the most important applications of wavelets is in removal of noise from signals, called denoising, accomplished by thresholding wavelet coefficients in order to separate signal from noise. Substantial work in this area was summarized by Donoho and colleagues at Stanford University, who developed a variety of algorithms for conventional denoising. However, conventional denoising fails for signals with low signal-to-noise ratio (SNR). Electrical signals acquired from the human body, called biosignals, commonly have below 0 dB SNR. Synchronous linear averaging of a large number of acquired data frames is universally used to increase the SNR of weak biosignals. A novel wavelet-based estimator is presented for fast estimation of such signals. The new estimation algorithm provides a faster rate of convergence to the underlying signal than linear averaging. The algorithm is implemented for processing of auditory brainstem response (ABR) and of auditory middle latency response (AMLR) signals. Experimental results with both simulated data and human subjects demonstrate that the novel wavelet estimator achieves superior performance to that of linear averaging.
CYP2D7 Sequence Variation Interferes with TaqMan CYP2D6*15 and *35 Genotyping
Riffel, Amanda K.; Dehghani, Mehdi; Hartshorne, Toinette; Floyd, Kristen C.; Leeder, J. Steven; Rosenblatt, Kevin P.; Gaedigk, Andrea
2016-01-01
TaqMan™ genotyping assays are widely used to genotype CYP2D6, which encodes a major drug metabolizing enzyme. Assay design for CYP2D6 can be challenging owing to the presence of two pseudogenes, CYP2D7 and CYP2D8, structural and copy number variation and numerous single nucleotide polymorphisms (SNPs) some of which reflect the wild-type sequence of the CYP2D7 pseudogene. The aim of this study was to identify the mechanism causing false-positive CYP2D6*15 calls and remediate those by redesigning and validating alternative TaqMan genotype assays. Among 13,866 DNA samples genotyped by the CompanionDx® lab on the OpenArray platform, 70 samples were identified as heterozygotes for 137Tins, the key SNP of CYP2D6*15. However, only 15 samples were confirmed when tested with the Luminex xTAG CYP2D6 Kit and sequencing of CYP2D6-specific long range (XL)-PCR products. Genotype and gene resequencing of CYP2D6 and CYP2D7-specific XL-PCR products revealed a CC>GT dinucleotide SNP in exon 1 of CYP2D7 that reverts the sequence to CYP2D6 and allows a TaqMan assay PCR primer to bind. Because CYP2D7 also carries a Tins, a false-positive mutation signal is generated. This CYP2D7 SNP was also responsible for generating false-positive signals for rs769258 (CYP2D6*35) which is also located in exon 1. Although alternative CYP2D6*15 and *35 assays resolved the issue, we discovered a novel CYP2D6*15 subvariant in one sample that carries additional SNPs preventing detection with the alternate assay. The frequency of CYP2D6*15 was 0.1% in this ethnically diverse U.S. population sample. In addition, we also discovered linkage between the CYP2D7 CC>GT dinucleotide SNP and the 77G>A (rs28371696) SNP of CYP2D6*43. The frequency of this tentatively functional allele was 0.2%. Taken together, these findings emphasize that regardless of how careful genotyping assays are designed and evaluated before being commercially marketed, rare or unknown SNPs underneath primer and/or probe regions can impact
CYP2D7 Sequence Variation Interferes with TaqMan CYP2D6 (*) 15 and (*) 35 Genotyping.
Riffel, Amanda K; Dehghani, Mehdi; Hartshorne, Toinette; Floyd, Kristen C; Leeder, J Steven; Rosenblatt, Kevin P; Gaedigk, Andrea
2015-01-01
TaqMan™ genotyping assays are widely used to genotype CYP2D6, which encodes a major drug metabolizing enzyme. Assay design for CYP2D6 can be challenging owing to the presence of two pseudogenes, CYP2D7 and CYP2D8, structural and copy number variation and numerous single nucleotide polymorphisms (SNPs) some of which reflect the wild-type sequence of the CYP2D7 pseudogene. The aim of this study was to identify the mechanism causing false-positive CYP2D6 (*) 15 calls and remediate those by redesigning and validating alternative TaqMan genotype assays. Among 13,866 DNA samples genotyped by the CompanionDx® lab on the OpenArray platform, 70 samples were identified as heterozygotes for 137Tins, the key SNP of CYP2D6 (*) 15. However, only 15 samples were confirmed when tested with the Luminex xTAG CYP2D6 Kit and sequencing of CYP2D6-specific long range (XL)-PCR products. Genotype and gene resequencing of CYP2D6 and CYP2D7-specific XL-PCR products revealed a CC>GT dinucleotide SNP in exon 1 of CYP2D7 that reverts the sequence to CYP2D6 and allows a TaqMan assay PCR primer to bind. Because CYP2D7 also carries a Tins, a false-positive mutation signal is generated. This CYP2D7 SNP was also responsible for generating false-positive signals for rs769258 (CYP2D6 (*) 35) which is also located in exon 1. Although alternative CYP2D6 (*) 15 and (*) 35 assays resolved the issue, we discovered a novel CYP2D6 (*) 15 subvariant in one sample that carries additional SNPs preventing detection with the alternate assay. The frequency of CYP2D6 (*) 15 was 0.1% in this ethnically diverse U.S. population sample. In addition, we also discovered linkage between the CYP2D7 CC>GT dinucleotide SNP and the 77G>A (rs28371696) SNP of CYP2D6 (*) 43. The frequency of this tentatively functional allele was 0.2%. Taken together, these findings emphasize that regardless of how careful genotyping assays are designed and evaluated before being commercially marketed, rare or unknown SNPs underneath primer
SALE2D. General Transient Fluid Flow Algorithm
Amsden, A.A.; Ruppel, H.M.; Hirt, C.W.
1981-06-01
SALE2D calculates two-dimensional fluid flows at all speeds, from the incompressible limit to highly supersonic. An implicit treatment of the pressure calculation similar to that in the Implicit Continuous-fluid Eulerian (ICE) technique provides this flow speed flexibility. In addition, the computing mesh may move with the fluid in a typical Lagrangian fashion, be held fixed in an Eulerian manner, or move in some arbitrarily specified way to provide a continuous rezoning capability. This latitude results from use of an Arbitrary Lagrangian-Eulerian (ALE) treatment of the mesh. The partial differential equations solved are the Navier-Stokes equations and the mass and internal energy equations. The fluid pressure is determined from an equation of state and supplemented with an artificial viscous pressure for the computation of shock waves. The computing mesh consists of a two-dimensional network of quadrilateral cells for either cylindrical or Cartesian coordinates, and a variety of user-selectable boundary conditions are provided in the program.
3-D wavelet compression and progressive inverse wavelet synthesis rendering of concentric mosaic.
Luo, Lin; Wu, Yunnan; Li, Jin; Zhang, Ya-Qin
2002-01-01
Using an array of photo shots, the concentric mosaic offers a quick way to capture and model a realistic three-dimensional (3-D) environment. We compress the concentric mosaic image array with a 3-D wavelet transform and coding scheme. Our compression algorithm and bitstream syntax are designed to ensure that a local view rendering of the environment requires only a partial bitstream, thereby eliminating the need to decompress the entire compressed bitstream before rendering. By exploiting the ladder-like structure of the wavelet lifting scheme, the progressive inverse wavelet synthesis (PIWS) algorithm is proposed to maximally reduce the computational cost of selective data accesses on such wavelet compressed datasets. Experimental results show that the 3-D wavelet coder achieves high-compression performance. With the PIWS algorithm, a 3-D environment can be rendered in real time from a compressed dataset.
Residual lens effects in 2D mode of auto-stereoscopic lenticular-based switchable 2D/3D displays
NASA Astrophysics Data System (ADS)
Sluijter, M.; IJzerman, W. L.; de Boer, D. K. G.; de Zwart, S. T.
2006-04-01
We discuss residual lens effects in multi-view switchable auto-stereoscopic lenticular-based 2D/3D displays. With the introduction of a switchable lenticular, it is possible to switch between a 2D mode and a 3D mode. The 2D mode displays conventional content, whereas the 3D mode provides the sensation of depth to the viewer. The uniformity of a display in the 2D mode is quantified by the quality parameter modulation depth. In order to reduce the modulation depth in the 2D mode, birefringent lens plates are investigated analytically and numerically, by ray tracing. We can conclude that the modulation depth in the 2D mode can be substantially decreased by using birefringent lens plates with a perfect index match between lens material and lens plate. Birefringent lens plates do not disturb the 3D performance of a switchable 2D/3D display.
Substrate-assisted 2D DNA lattices and algorithmic lattices from single-stranded tiles.
Kim, Junghoon; Ha, Tai Hwan; Park, Sung Ha
2015-08-07
We present a simple route to circumvent kinetic traps which affect many types of DNA nanostructures in their self-assembly process. Using this method, a new 2D DNA lattice made up of short, single-stranded tile (SST) motifs was created. Previously, the growth of SST DNA assemblies was restricted to 1D (tubes and ribbons) or finite-sized 2D (molecular canvases). By utilizing the substrate-assisted growth method, sets of SSTs were designed as unit cells to self-assemble into periodic and aperiodic 2D lattices which continuously grow both along and orthogonal to the helical axis. Notably, large-scale (∼1 μm(2)) fully periodic 2D lattices were fabricated using a minimum of just 2 strand species. Furthermore, the ability to create 2D lattices from a few motifs enables certain rules to be encoded into these SSTs to carry out algorithmic self-assembly. A set of these motifs was designed to execute simple 1-input 1-output COPY and NOT algorithms, the space-time manifestations which were aperiodic 2D algorithmic SST lattices. The methodology presented here can be straightforwardly applied to other motifs which fall into this type of kinetic trap to create novel DNA crystals.
Use of autocorrelation of wavelet coefficients for fault diagnosis
NASA Astrophysics Data System (ADS)
Rafiee, J.; Tse, P. W.
2009-07-01
This paper presents a novel time-frequency-based feature recognition system for gear fault diagnosis using autocorrelation of continuous wavelet coefficients (CWC). Furthermore, it introduces an original mathematical approximation of gearbox vibration signals which approximates sinusoidal components of noisy vibration signals generated from gearboxes, including incipient and serious gear failures using autocorrelation of CWC. First, the drawbacks of the continuous wavelet transform (CWT) have been eliminated using autocorrelation function. Secondly, the autocorrelation of CWC is introduced as an original pattern for fault identification in machine condition monitoring. Thirdly, a sinusoidal summation function consisting of eight terms was used to approximate the periodic waveforms generated by autocorrelation of CWC for normal gearboxes (NGs) as well as occurrences of incipient and severe gear fault (e.g. slight-worn, medium-worn, and broken-tooth gears). In other words, the size of vibration signals can be reduced with minimal loss of significant frequency content by means of the sinusoidal approximation of generated autocorrelation waveforms of CWC as reported in this paper.
Differential CYP 2D6 metabolism alters primaquine pharmacokinetics.
Potter, Brittney M J; Xie, Lisa H; Vuong, Chau; Zhang, Jing; Zhang, Ping; Duan, Dehui; Luong, Thu-Lan T; Bandara Herath, H M T; Dhammika Nanayakkara, N P; Tekwani, Babu L; Walker, Larry A; Nolan, Christina K; Sciotti, Richard J; Zottig, Victor E; Smith, Philip L; Paris, Robert M; Read, Lisa T; Li, Qigui; Pybus, Brandon S; Sousa, Jason C; Reichard, Gregory A; Marcsisin, Sean R
2015-04-01
Primaquine (PQ) metabolism by the cytochrome P450 (CYP) 2D family of enzymes is required for antimalarial activity in both humans (2D6) and mice (2D). Human CYP 2D6 is highly polymorphic, and decreased CYP 2D6 enzyme activity has been linked to decreased PQ antimalarial activity. Despite the importance of CYP 2D metabolism in PQ efficacy, the exact role that these enzymes play in PQ metabolism and pharmacokinetics has not been extensively studied in vivo. In this study, a series of PQ pharmacokinetic experiments were conducted in mice with differential CYP 2D metabolism characteristics, including wild-type (WT), CYP 2D knockout (KO), and humanized CYP 2D6 (KO/knock-in [KO/KI]) mice. Plasma and liver pharmacokinetic profiles from a single PQ dose (20 mg/kg of body weight) differed significantly among the strains for PQ and carboxy-PQ. Additionally, due to the suspected role of phenolic metabolites in PQ efficacy, these were probed using reference standards. Levels of phenolic metabolites were highest in mice capable of metabolizing CYP 2D6 substrates (WT and KO/KI 2D6 mice). PQ phenolic metabolites were present in different quantities in the two strains, illustrating species-specific differences in PQ metabolism between the human and mouse enzymes. Taking the data together, this report furthers understanding of PQ pharmacokinetics in the context of differential CYP 2D metabolism and has important implications for PQ administration in humans with different levels of CYP 2D6 enzyme activity.
NASA Astrophysics Data System (ADS)
Vaudor, Lise; Piegay, Herve; Wawrzyniak, Vincent; Spitoni, Marie
2016-04-01
The form and functioning of a geomorphic system result from processes operating at various spatial and temporal scales. Longitudinal channel characteristics thus exhibit complex patterns which vary according to the scale of study, might be periodic or segmented, and are generally blurred by noise. Describing the intricate, multiscale structure of such signals, and identifying at which scales the patterns are dominant and over which sub-reach, could help determine at which scales they should be investigated, and provide insights into the main controlling factors. Wavelet transforms aim at describing data at multiple scales (either in time or space), and are now exploited in geophysics for the analysis of nonstationary series of data. They provide a consistent, non-arbitrary, and multiscale description of a signal's variations and help explore potential causalities. Nevertheless, their use in fluvial geomorphology, notably to study longitudinal patterns, is hindered by a lack of user-friendly tools to help understand, implement, and interpret them. We have developed a free application, The Wavelet ToolKat, designed to facilitate the use of wavelet transforms on temporal or spatial series. We illustrate its usefulness describing longitudinal channel curvature and slope of three freely meandering rivers in the Amazon basin (the Purus, Juruá and Madre de Dios rivers), using topographic data generated from NASA's Shuttle Radar Topography Mission (SRTM) in 2000. Three types of wavelet transforms are used, with different purposes. Continuous Wavelet Transforms are used to identify in a non-arbitrary way the dominant scales and locations at which channel curvature and slope vary. Cross-wavelet transforms, and wavelet coherence and phase are used to identify scales and locations exhibiting significant channel curvature and slope co-variations. Maximal Overlap Discrete Wavelet Transforms decompose data into their variations at a series of scales and are used to provide
Mechanical characterization of 2D, 2D stitched, and 3D braided/RTM materials
NASA Technical Reports Server (NTRS)
Deaton, Jerry W.; Kullerd, Susan M.; Portanova, Marc A.
1993-01-01
Braided composite materials have potential for application in aircraft structures. Fuselage frames, floor beams, wing spars, and stiffeners are examples where braided composites could find application if cost effective processing and damage tolerance requirements are met. Another important consideration for braided composites relates to their mechanical properties and how they compare to the properties of composites produced by other textile composite processes being proposed for these applications. Unfortunately, mechanical property data for braided composites do not appear extensively in the literature. Data are presented in this paper on the mechanical characterization of 2D triaxial braid, 2D triaxial braid plus stitching, and 3D (through-the-thickness) braid composite materials. The braided preforms all had the same graphite tow size and the same nominal braid architectures, (+/- 30 deg/0 deg), and were resin transfer molded (RTM) using the same mold for each of two different resin systems. Static data are presented for notched and unnotched tension, notched and unnotched compression, and compression after impact strengths at room temperature. In addition, some static results, after environmental conditioning, are included. Baseline tension and compression fatigue results are also presented, but only for the 3D braided composite material with one of the resin systems.
Non Lyapunov stability of a constant spatially developing 2-D gas flow
NASA Astrophysics Data System (ADS)
Balint, Agneta M.; Balint, Stefan; Tanasie, Loredana
2017-01-01
Different types of stabilities (global, local) and instabilities (global absolute, local convective) of the constant spatially developing 2-D gas flow are analyzed in a particular phase space of continuously differentiable functions, endowed with the usual algebraic operations and the topology generated by the uniform convergence on the plane. For this purpose the Euler equations linearized at the constant flow are used. The Lyapunov stability analysis was presented in [1] and this paper is a continuation of [1].
NASA Astrophysics Data System (ADS)
Wang, Zhengzi; Ren, Zhong; Liu, Guodong
2015-10-01
Noninvasive measurement of blood glucose concentration has become a hotspot research in the world due to its characteristic of convenient, rapid and non-destructive etc. The blood glucose concentration monitoring based on photoacoustic technique has attracted many attentions because the detected signal is ultrasonic signals rather than the photo signals. But during the acquisition of the photoacoustic signals of glucose, the photoacoustic signals are not avoid to be polluted by some factors, such as the pulsed laser, electronic noises and circumstance noises etc. These disturbances will impact the measurement accuracy of the glucose concentration, So, the denoising of the glucose photoacoustic signals is a key work. In this paper, a wavelet shift-invariant threshold denoising method is improved, and a novel wavelet threshold function is proposed. For the novel wavelet threshold function, two threshold values and two different factors are set, and the novel function is high order derivative and continuous, which can be looked as the compromise between the wavelet soft threshold denoising and hard threshold denoising. Simulation experimental results illustrate that, compared with other wavelet threshold denoising, this improved wavelet shift-invariant threshold denoising has higher signal-to-noise ratio(SNR) and smaller root mean-square error (RMSE) value. And this improved denoising also has better denoising effect than others. Therefore, this improved denoising has a certain of potential value in the denoising of glucose photoacoustic signals.
NASA Astrophysics Data System (ADS)
Hoang, Vu Dang; Loan, Nguyen Thi; Tho, Vu Thi; Nguyen, Hue Minh Thi
2014-03-01
Signal processing methods based on the use of derivative, Fourier and wavelet transforms were proposed for the spectrophotometric simultaneous determination of cefoperazone and sulbactam in powders for injection. These transforms were successfully applied to UV spectra and ratio spectra to find suitable working wavelengths. Wavelet signal processing was proved to have distinct advantages (i.e. higher peak intensity obtained, additional smooth function and scaling factor process eliminated) over derivative and Fourier transforms. Especially, a better resolution of spectral overlapping bands was obtained by the use of double signal transform in the sequences such as (i) spectra pre-processed by Fractional Wavelet Transform and subsequently subjected to Continuous Wavelet Transform or Discrete Wavelet Transform, and (ii) derivative - wavelet transforms combined. Calibration graphs for cefoperazone and sulbactam were recorded for the range 10-35 mg/L. Good accuracy and precision were reported for all proposed methods by analyzing synthetic mixtures of cefoperazone and sulbactam. Furthermore, these methods were statistically comparable to RP-HPLC.
Hoang, Vu Dang; Loan, Nguyen Thi; Tho, Vu Thi; Nguyen, Hue Minh Thi
2014-01-01
Signal processing methods based on the use of derivative, Fourier and wavelet transforms were proposed for the spectrophotometric simultaneous determination of cefoperazone and sulbactam in powders for injection. These transforms were successfully applied to UV spectra and ratio spectra to find suitable working wavelengths. Wavelet signal processing was proved to have distinct advantages (i.e. higher peak intensity obtained, additional smooth function and scaling factor process eliminated) over derivative and Fourier transforms. Especially, a better resolution of spectral overlapping bands was obtained by the use of double signal transform in the sequences such as (i) spectra pre-processed by Fractional Wavelet Transform and subsequently subjected to Continuous Wavelet Transform or Discrete Wavelet Transform, and (ii) derivative - wavelet transforms combined. Calibration graphs for cefoperazone and sulbactam were recorded for the range 10-35 mg/L. Good accuracy and precision were reported for all proposed methods by analyzing synthetic mixtures of cefoperazone and sulbactam. Furthermore, these methods were statistically comparable to RP-HPLC.
Zhu, Xiaojun; Lei, Guangtsai; Pan, Guangwen
1997-04-01
In this paper, the continuous operator is discretized into matrix forms by Galerkin`s procedure, using periodic Battle-Lemarie wavelets as basis/testing functions. The polynomial decomposition of wavelets is applied to the evaluation of matrix elements, which makes the computational effort of the matrix elements no more expensive than that of method of moments (MoM) with conventional piecewise basis/testing functions. A new algorithm is developed employing the fast wavelet transform (FWT). Owing to localization, cancellation, and orthogonal properties of wavelets, very sparse matrices have been obtained, which are then solved by the LSQR iterative method. This algorithm is also adaptive in that one can add at will finer wavelet bases in the regions where fields vary rapidly, without any damage to the system orthogonality of the wavelet basis functions. To demonstrate the effectiveness of the new algorithm, we applied it to the evaluation of frequency-dependent resistance and inductance matrices of multiple lossy transmission lines. Numerical results agree with previously published data and laboratory measurements. The valid frequency range of the boundary integral equation results has been extended two to three decades in comparison with the traditional MoM approach. The new algorithm has been integrated into the computer aided design tool, MagiCAD, which is used for the design and simulation of high-speed digital systems and multichip modules Pan et al. 29 refs., 7 figs., 6 tabs.
Wavelet-aided pavement distress image processing
NASA Astrophysics Data System (ADS)
Zhou, Jian; Huang, Peisen S.; Chiang, Fu-Pen
2003-11-01
A wavelet-based pavement distress detection and evaluation method is proposed. This method consists of two main parts, real-time processing for distress detection and offline processing for distress evaluation. The real-time processing part includes wavelet transform, distress detection and isolation, and image compression and noise reduction. When a pavement image is decomposed into different frequency subbands by wavelet transform, the distresses, which are usually irregular in shape, appear as high-amplitude wavelet coefficients in the high-frequency details subbands, while the background appears in the low-frequency approximation subband. Two statistical parameters, high-amplitude wavelet coefficient percentage (HAWCP) and high-frequency energy percentage (HFEP), are established and used as criteria for real-time distress detection and distress image isolation. For compression of isolated distress images, a modified EZW (Embedded Zerotrees of Wavelet coding) is developed, which can simultaneously compress the images and reduce the noise. The compressed data are saved to the hard drive for further analysis and evaluation. The offline processing includes distress classification, distress quantification, and reconstruction of the original image for distress segmentation, distress mapping, and maintenance decision-making. The compressed data are first loaded and decoded to obtain wavelet coefficients. Then Radon transform is then applied and the parameters related to the peaks in the Radon domain are used for distress classification. For distress quantification, a norm is defined that can be used as an index for evaluating the severity and extent of the distress. Compared to visual or manual inspection, the proposed method has the advantages of being objective, high-speed, safe, automated, and applicable to different types of pavements and distresses.
NASA Astrophysics Data System (ADS)
Xin, Shihe; Le Quéré, Patrick
2012-06-01
Following our previous two-dimensional (2D) studies of flows in differentially heated cavities filled with air, we studied the stability of 2D natural convection flows in these cavities with respect to 3D periodic perturbations. The basis of the numerical methods is a time-stepping code using the Chebyshev spectral collocation method and the direct Uzawa method for velocity-pressure coupling. Newton's iteration, Arnoldi's method and the continuation method have been used in order to, respectively, compute the 2D steady-state base solution, estimate the leading eigenmodes of the Jacobian and perform linear stability analysis. Differentially heated air-filled cavities of aspect ratios from 1 to 7 were investigated. Neutral curves (Rayleigh number versus wave number) have been obtained. It turned out that only for aspect ratio 7, 3D stationary instability occurs at slightly higher Rayleigh numbers than the onset of 2D time-dependent flow and that for other aspect ratios 3D instability always takes place before 2D time-dependent flows. 3D unstable modes are stationary and anti-centro-symmetric. 3D nonlinear simulations revealed that the corresponding pitchfork bifurcations are supercritical and that 3D instability leads only to weak flow in the third direction. Further 3D computations are also performed at higher Rayleigh number in order to understand the effects of the weak 3D fluid motion on the onset of time-dependent flow. 3D flow structures are responsible for the onset of time-dependent flow for aspect ratios 1, 2 and 3, while for larger aspect ratios they do not alter the transition scenario, which was observed in the 2D cases and that vertical boundary layers become unstable to traveling waves.
Learning from graphically integrated 2D and 3D representations improves retention of neuroanatomy
NASA Astrophysics Data System (ADS)
Naaz, Farah
Visualizations in the form of computer-based learning environments are highly encouraged in science education, especially for teaching spatial material. Some spatial material, such as sectional neuroanatomy, is very challenging to learn. It involves learning the two dimensional (2D) representations that are sampled from the three dimensional (3D) object. In this study, a computer-based learning environment was used to explore the hypothesis that learning sectional neuroanatomy from a graphically integrated 2D and 3D representation will lead to better learning outcomes than learning from a sequential presentation. The integrated representation explicitly demonstrates the 2D-3D transformation and should lead to effective learning. This study was conducted using a computer graphical model of the human brain. There were two learning groups:
Computational Screening of 2D Materials for Photocatalysis.
Singh, Arunima K; Mathew, Kiran; Zhuang, Houlong L; Hennig, Richard G
2015-03-19
Two-dimensional (2D) materials exhibit a range of extraordinary electronic, optical, and mechanical properties different from their bulk counterparts with potential applications for 2D materials emerging in energy storage and conversion technologies. In this Perspective, we summarize the recent developments in the field of solar water splitting using 2D materials and review a computational screening approach to rapidly and efficiently discover more 2D materials that possess properties suitable for solar water splitting. Computational tools based on density-functional theory can predict the intrinsic properties of potential photocatalyst such as their electronic properties, optical absorbance, and solubility in aqueous solutions. Computational tools enable the exploration of possible routes to enhance the photocatalytic activity of 2D materials by use of mechanical strain, bias potential, doping, and pH. We discuss future research directions and needed method developments for the computational design and optimization of 2D materials for photocatalysis.
3D weak lensing with spin wavelets on the ball
NASA Astrophysics Data System (ADS)
Leistedt, Boris; McEwen, Jason D.; Kitching, Thomas D.; Peiris, Hiranya V.
2015-12-01
We construct the spin flaglet transform, a wavelet transform to analyze spin signals in three dimensions. Spin flaglets can probe signal content localized simultaneously in space and frequency and, moreover, are separable so that their angular and radial properties can be controlled independently. They are particularly suited to analyzing cosmological observations such as the weak gravitational lensing of galaxies. Such observations have a unique 3D geometrical setting since they are natively made on the sky, have spin angular symmetries, and are extended in the radial direction by additional distance or redshift information. Flaglets are constructed in the harmonic space defined by the Fourier-Laguerre transform, previously defined for scalar functions and extended here to signals with spin symmetries. Thanks to various sampling theorems, both the Fourier-Laguerre and flaglet transforms are theoretically exact when applied to bandlimited signals. In other words, in numerical computations the only loss of information is due to the finite representation of floating point numbers. We develop a 3D framework relating the weak lensing power spectrum to covariances of flaglet coefficients. We suggest that the resulting novel flaglet weak lensing estimator offers a powerful alternative to common 2D and 3D approaches to accurately capture cosmological information. While standard weak lensing analyses focus on either real- or harmonic-space representations (i.e., correlation functions or Fourier-Bessel power spectra, respectively), a wavelet approach inherits the advantages of both techniques, where both complicated sky coverage and uncertainties associated with the physical modeling of small scales can be handled effectively. Our codes to compute the Fourier-Laguerre and flaglet transforms are made publicly available.
Synthetic Covalent and Non-Covalent 2D Materials.
Boott, Charlotte E; Nazemi, Ali; Manners, Ian
2015-11-16
The creation of synthetic 2D materials represents an attractive challenge that is ultimately driven by their prospective uses in, for example, electronics, biomedicine, catalysis, sensing, and as membranes for separation and filtration. This Review illustrates some recent advances in this diverse field with a focus on covalent and non-covalent 2D polymers and frameworks, and self-assembled 2D materials derived from nanoparticles, homopolymers, and block copolymers.
[Baseline correction method for spectrum signal of SF6 insulating air with optimum wavelet basis].
Liu, Yan; Liu, Kai; Tao, Wei-Liang; Wang, Xian-Pei
2010-06-01
SF6 gas has been widely used in the power equipments as an excellent electric insulating and arc-quenching medium. In the present paper, a baseline correction method based on the optimum wavelet basis for spectrum detection is proposed to measure the composition content of the SF6 insulating gas to secure the power safety. In this method, the optimum wavelet basis is selected in the wavelet packet according to constructor function on the energy concentration criterion to express the spectrum signal in the time-frequency domain. Then the strong spectrum composition is removed from the spectrum signal with the threshold method to eliminate the interference with the continuous spectrum fitting. Finally we remove the continuous spectrum which is fitting result from the origin spectrum and obtain the useful signal of line spectrum. The intensities of spectral line processed with the proposed algorithm could reflect the concentration of the conponents to be measured in SF6 gas. Experiments to analyze the absorption spectrum of the SF6 insulating gas mixture show that the proposed algorithm can estimate and correct the drifting baseline accurately, and its performance is better than the algorithm based on iterative wavelet.
Laboratory studies on N(2D) reactions of relevance to the chemistry of planetary atmospheres
NASA Astrophysics Data System (ADS)
Balucani, N.; Casavecchia, P.
Molecular nitrogen is a very stable molecule, practically inert from a chemical point of view. For a nitrogen chemistry to occur in the planetary atmospheres which contain N2 , it is necessary to transform it into an active form, such as atoms or ions. As far as the production of atomic nitrogen in the upper atmospheres of planets (like Mars) or moons (like Titan) is concerned, several processes - as N2 dissociation induced by electron impact, EUV photolysis (λ <80 nm) and dissociative photoionization, or galactic cosmic ray absorption and N+ dissociative recombination all 2 lead to atomic nitrogen, notably in the ground, 4 S3/2 , and first electronically excited, 2 D3/2,5/2 , states with comparable yields. The radiative lifetimes of the metastable states 2 D3/2 and 2 D5/2 are quite long (12.3 and 48 hours, respectively), because the transition from a doublet to a quartet state is strongly forbidden. In addition, the physical quenching of N(2 D) is often a slow process and in some important cases the main fate of N(2 D) is chemical reaction with other constituents of the planetary atmospheres. The production of N atoms in the 2 D state is an important fact, because N(4 S) atoms exhibit very low reactivity with closed-shell molecules and the probability of collision with an open-shell radical is small. Unfortunately laboratory experiments on the gas-phase reactions of N(2 D) have been lacking until recently, because of serious experimental difficulties in studying these reactive systems. Accurate kinetic data on the reactions of N(2 D) with the some molecules of relevance to the chemistry of planetary atmospheres have finally become available in the late 90's, but a better knowledge of the reactive behavior requires a dynamical investigation of N(2 D) reactions. The capability of generating intense continuous beams of N(2 D) achieved in our laboratory some years ago has opened up the possibility of studying the reactive scattering of this species under single
An application of wavelet analysis to paleoproductivity records from the Southern Ocean
NASA Astrophysics Data System (ADS)
Sen, Asok K.; Filippelli, Gabriel M.; Flores, José-Abel
2009-07-01
We have performed wavelet analysis of the paleoproductivity records from the southeastern Atlantic sector of the Southern Ocean. In particular, we have applied a continuous wavelet transform to the phosphorus-to-titanium (P/Ti) ratios obtained from the Ocean Drilling Program (ODP) Sites 1089 and 1094 over the past ˜600 kyr, and computed their wavelet power spectra in order to elucidate the spectral-temporal aspects of phosphorus deposition at these sites. Because data are unevenly sampled in time, they are first resampled using a uniform sampling interval prior to wavelet analysis. The wavelet power spectra of the P/Ti data are presented on a time-period plane from which the dominant periodicities of P export and their duration in time are discerned by visual inspection. Our results indicate that at the ODP Site 1089, the strongest P export occurs within a periodic band with the most dominant period of ˜100 kyr, which corresponds to the eccentricity period of Milankovitch cyclicity. On the other hand, at the ODP Site 1094, which is completely covered with ice during the glacial times, the strongest periodicity of P export is found to be around 82 kyr. This periodicity is twice the period of the 41-kyr Milankovitch obliquity cycle, implying that obliquity forcing drives the productivity at this site in a period doubling scenario. Given the strong influence of ice cover at this site, another implication is that sea ice extent itself is strongly influenced by the obliquity signal, and productivity simply responds to the availability of ice-free conditions. We have also performed wavelet analysis of the carbonate production data at the ODP Site 1089, and found a dominant periodicity of ˜100 kyr. In addition, a few weaker decadal-scale periodicities are observed in both P/Ti and carbonate data which can be linked to Milankovitch cycles.
Image wavelet decomposition and applications
NASA Technical Reports Server (NTRS)
Treil, N.; Mallat, S.; Bajcsy, R.
1989-01-01
The general problem of computer vision has been investigated for more that 20 years and is still one of the most challenging fields in artificial intelligence. Indeed, taking a look at the human visual system can give us an idea of the complexity of any solution to the problem of visual recognition. This general task can be decomposed into a whole hierarchy of problems ranging from pixel processing to high level segmentation and complex objects recognition. Contrasting an image at different representations provides useful information such as edges. An example of low level signal and image processing using the theory of wavelets is introduced which provides the basis for multiresolution representation. Like the human brain, we use a multiorientation process which detects features independently in different orientation sectors. So, images of the same orientation but of different resolutions are contrasted to gather information about an image. An interesting image representation using energy zero crossings is developed. This representation is shown to be experimentally complete and leads to some higher level applications such as edge and corner finding, which in turn provides two basic steps to image segmentation. The possibilities of feedback between different levels of processing are also discussed.
Functional calculus using wavelet transforms
NASA Astrophysics Data System (ADS)
Holschneider, Matthias
1994-07-01
It is shown how the wavelet transform may be used to compute for a function s the symbol s(A) for any (not necessarily) self-adjoint operator A whose spectrum is contained in the upper half plane. For self-adjoint operators it is shown that this functional calculus coincides with the usual one. In particular it is shown how the exponential eitA can be written in terms of the resolvent Rz=(A-z)-1 of A as follows: eitA=(1/c) ∫0∞da an-2∫-∞+∞ dbĝ¯ (at)eitbRb-ian(A), with c=-2iπ×∫0∞(dω/ω) (-iω)n-1ĝ¯(ω)e-ω, and n∈N, and the integral is understood as the Cesaro limit. This shows explicitly how the behavior for large t is determined by the behavior of Rz at Iz ≂1/t.
Generalizing Lifted Tensor-Product Wavelets to Irregular Polygonal Domains
Bertram, M.; Duchaineau, M.A.; Hamann, B.; Joy, K.I.
2002-04-11
We present a new construction approach for symmetric lifted B-spline wavelets on irregular polygonal control meshes defining two-manifold topologies. Polygonal control meshes are recursively refined by stationary subdivision rules and converge to piecewise polynomial limit surfaces. At every subdivision level, our wavelet transforms provide an efficient way to add geometric details that are expanded from wavelet coefficients. Both wavelet decomposition and reconstruction operations are based on local lifting steps and have linear-time complexity.
Wavelet Based Feature Extraction for Target Recognition and Minefield Detection
2007-11-02
with Ron Gross (NSWC); presentation of course "Wavelets and Filter Banks " to NSWC personnel; application of simulated annealing to optimize RF absorption...characteristics of multilayer surfaces; generalization of wavelet transform to M-band wavelets; algorithm to generate a wavelet filter bank using any...filter whatsoever as the analysis filter; implementation of an algorithm to parameterize all M-band paraunitary filter banks .
Multiresolution Stochastic Models, Data Fusion, and Wavelet Transforms
1992-05-01
based on the wavelet transform . The statistical structure of these models is Markovian in scale, and in addition the eigenstructure of these models is...given by the wavelet transform . The implication of this is that by using the wavelet transform we can convert the apparently complicated problem of...plays the role of the time-like variable. In addition we show how the wavelet transform , which is defined for signals that extend from -infinity to
Undecimated Wavelet Transforms for Image De-noising
Gyaourova, A; Kamath, C; Fodor, I K
2002-11-19
A few different approaches exist for computing undecimated wavelet transform. In this work we construct three undecimated schemes and evaluate their performance for image noise reduction. We use standard wavelet based de-noising techniques and compare the performance of our algorithms with the original undecimated wavelet transform, as well as with the decimated wavelet transform. The experiments we have made show that our algorithms have better noise removal/blurring ratio.
Epitaxial 2D SnSe2/ 2D WSe2 van der Waals Heterostructures.
Aretouli, Kleopatra Emmanouil; Tsoutsou, Dimitra; Tsipas, Polychronis; Marquez-Velasco, Jose; Aminalragia Giamini, Sigiava; Kelaidis, Nicolaos; Psycharis, Vassilis; Dimoulas, Athanasios
2016-09-07
van der Waals heterostructures of 2D semiconductor materials can be used to realize a number of (opto)electronic devices including tunneling field effect devices (TFETs). It is shown in this work that high quality SnSe2/WSe2 vdW heterostructure can be grown by molecular beam epitaxy on AlN(0001)/Si(111) substrates using a Bi2Se3 buffer layer. A valence band offset of 0.8 eV matches the energy gap of SnSe2 in such a way that the VB edge of WSe2 and the CB edge of SnSe2 are lined up, making this materials combination suitable for (nearly) broken gap TFETs.
Review of wavelet transforms for pattern recognitions
NASA Astrophysics Data System (ADS)
Szu, Harold H.
1996-03-01
After relating the adaptive wavelet transform to the human visual and hearing systems, we exploit the synergism between such a smart sensor processing with brain-style neural network computing. The freedom of choosing an appropriate kernel of a linear transform, which is given to us by the recent mathematical foundation of the wavelet transform, is exploited fully and is generally called the adaptive wavelet transform (WT). However, there are several levels of adaptivity: (1) optimum coefficients: adjustable transform coefficients chosen with respect to a fixed mother kernel for better invariant signal representation, (2) super-mother: grouping different scales of daughter wavelets of same or different mother wavelets at different shift location into a new family called a superposition mother kernel for better speech signal classification, (3) variational calculus to determine ab initio a constraint optimization mother for a specific task. The tradeoff between the mathematical rigor of the complete orthonormality and the speed of order (N) with the adaptive flexibility is finally up to the user's needs. Then, to illustrate (1), a new invariant optoelectronic architecture of a wedge- shape filter in the WT domain is given for scale-invariant signal classification by neural networks.
Wavelet applied to computer vision in astrophysics
NASA Astrophysics Data System (ADS)
Bijaoui, Albert; Slezak, Eric; Traina, Myriam
2004-02-01
Multiscale analyses can be provided by application wavelet transforms. For image processing purposes, we applied algorithms which imply a quasi isotropic vision. For a uniform noisy image, a wavelet coefficient W has a probability density function (PDF) p(W) which depends on the noise statistic. The PDF was determined for many statistical noises: Gauss, Poission, Rayleigh, exponential. For CCD observations, the Anscombe transform was generalized to a mixed Gasus+Poisson noise. From the discrete wavelet transform a set of significant wavelet coefficients (SSWC)is obtained. Many applications have been derived like denoising and deconvolution. Our main application is the decomposition of the image into objects, i.e the vision. At each scale an image labelling is performed in the SSWC. An interscale graph linking the fields of significant pixels is then obtained. The objects are identified using this graph. The wavelet coefficients of the tree related to a given object allow one to reconstruct its image by a classical inverse method. This vision model has been applied to astronomical images, improving the analysis of complex structures.
Embedded wavelet video coding with error concealment
NASA Astrophysics Data System (ADS)
Chang, Pao-Chi; Chen, Hsiao-Ching; Lu, Ta-Te
2000-04-01
We present an error-concealed embedded wavelet (ECEW) video coding system for transmission over Internet or wireless networks. This system consists of two types of frames: intra (I) frames and inter, or predicted (P), frames. Inter frames are constructed by the residual frames formed by variable block-size multiresolution motion estimation (MRME). Motion vectors are compressed by arithmetic coding. The image data of intra frames and residual frames are coded by error-resilient embedded zerotree wavelet (ER-EZW) coding. The ER-EZW coding partitions the wavelet coefficients into several groups and each group is coded independently. Therefore, the error propagation effect resulting from an error is only confined in a group. In EZW coding any single error may result in a totally undecodable bitstream. To further reduce the error damage, we use the error concealment at the decoding end. In intra frames, the erroneous wavelet coefficients are replaced by neighbors. In inter frames, erroneous blocks of wavelet coefficients are replaced by data from the previous frame. Simulations show that the performance of ECEW is superior to ECEW without error concealment by 7 to approximately 8 dB at the error-rate of 10-3 in intra frames. The improvement still has 2 to approximately 3 dB at a higher error-rate of 10-2 in inter frames.
Multisensensor Multitemporal Data Fusion Using Wavelet Transform
NASA Astrophysics Data System (ADS)
Ghannam, S.; Awadallah, M.; Abbott, A. L.; Wynne, R. H.
2014-11-01
Interest in data fusion, for remote-sensing applications, continues to grow due to the increasing importance of obtaining data in high resolution both spatially and temporally. Applications that will benefit from data fusion include ecosystem disturbance and recovery assessment, ecological forecasting, and others. This paper introduces a novel spatiotemporal fusion approach, the wavelet-based Spatiotemporal Adaptive Data Fusion Model (WSAD-FM). This new technique is motivated by the popular STARFM tool, which utilizes lower-resolution MODIS imagery to supplement Landsat scenes using a linear model. The novelty of WSAD-FM is twofold. First, unlike STARFM, this technique does not predict an entire new image in one linear step, but instead decomposes input images into separate "approximation" and "detail" parts. The different portions are fed into a prediction model that limits the effects of linear interpolation among images. Low-spatial-frequency components are predicted by a weighted mixture of MODIS images and low-spatial-frequency components of Landsat images that are neighbors in the temporal domain. Meanwhile, high-spatialfrequency components are predicted by a weighted average of high-spatial-frequency components of Landsat images alone. The second novelty is that the method has demonstrated good performance using only one input Landsat image and a pair of MODIS images. The technique has been tested using several Landsat and MODIS images for a study area from Central North Carolina (WRS-2 path/row 16/35 in Landsat and H/V11/5 in MODIS), acquired in 2001. NDVI images that were calculated from the study area were used as input to the algorithm. The technique was tested experimentally by predicting existing Landsat images, and we obtained R2 values in the range 0.70 to 0.92 for estimated Landsat images in the red band, and 0.62 to 0.89 for estimated NDVI images.
Higher-density dyadic wavelet transform and its application
NASA Astrophysics Data System (ADS)
Qin, Yi; Tang, Baoping; Wang, Jiaxu
2010-04-01
This paper proposes a higher-density dyadic wavelet transform with two generators, whose corresponding wavelet filters are band-pass and high-pass. The wavelet coefficients at each scale in this case have the same length as the signal. This leads to a new redundant dyadic wavelet transform, which is strictly shift invariant and further increases the sampling in the time dimension. We describe the definition of higher-density dyadic wavelet transform, and discuss the condition of perfect reconstruction of the signal from its wavelet coefficients. The fast implementation algorithm for the proposed transform is given as well. Compared with the higher-density discrete wavelet transform, the proposed transform is shift invariant. Applications into signal denoising indicate that the proposed wavelet transform has better denoising performance than other commonly used wavelet transforms. In the end, various typical wavelet transforms are applied to analyze the vibration signals of two faulty roller bearings, the results show that the proposed wavelet transform can more effectively extract the fault characteristics of the roller bearings than the other wavelet transforms.
The Discrete, Orthogonal Wavelet Transform, A Protective Approach.
1995-09-01
completely determined by the collection of functions onto which it projects. The wavelet transform projects onto a set of functions which satisfy a...simple linear relationship between different levels of dilation. The properties of the wavelet transform are determined by the coefficients of this linear...relationship. This thesis examines the connections between the wavelet transform properties and the linear relationship coefficients. (AN)
Time Difference of Arrival (TDOA) Estimation Using Wavelet Based Denoising
1999-03-01
NAVAL POSTGRADUATE SCHOOL Monterey, California THESIS TIME DIFFERENCE OF ARRIVAL (TDOA) ESTIMATION USING WAVELET BASED DENOISING by Unal Aktas...4. TITLE AND SUBTITLE TIME DIFFERENCE OF ARRIVAL (TDOA) ESTIMATION USING WAVELET BASED DENOISING 6. AUTHOR(S) Unal Aktas 7...difference of arrival (TDOA) method. The wavelet transform is used to increase the accuracy of TDOA estimation. Several denoising techniques based on
The future of 2D metrology for display manufacturing
NASA Astrophysics Data System (ADS)
Sandstrom, Tor; Wahlsten, Mikael; Park, Youngjin
2016-10-01
The race to 800 PPI and higher in mobile devices and the transition to OLED displays are driving a dramatic development of mask quality: resolution, CDU, registration, and complexity. 2D metrology for large area masks is necessary and must follow the roadmap. Driving forces in the market place point to continued development of even more dense displays. State-of-the-art metrology has proven itself capable of overlay below 40 nm and registration below 65 nm for G6 masks. Future developments include incoming and recurrent measurements of pellicalized masks at the panel maker's factory site. Standardization of coordinate systems across supplier networks is feasible. This will enable better yield and production economy for both mask and panel maker. Better distortion correction methods will give better registration on the panels and relax the flatness requirements of the mask blanks. If panels are measured together with masks and the results are used to characterize the aligners, further quality and yield improvements are possible. Possible future developments include in-cell metrology and integration with other instruments in the same platform.
Significance tests for the wavelet power and the wavelet power spectrum
NASA Astrophysics Data System (ADS)
Ge, Z.
2007-11-01
Significance tests usually address the issue how to distinguish statistically significant results from those due to pure randomness when only one sample of the population is studied. This issue is also important when the results obtained using the wavelet analysis are to be interpreted. Torrence and Compo (1998) is one of the earliest works that has systematically discussed this problem. Their results, however, were based on Monte Carlo simulations, and hence, failed to unveil many interesting and important properties of the wavelet analysis. In the present work, the sampling distributions of the wavelet power and power spectrum of a Gaussian White Noise (GWN) were derived in a rigorous statistical framework, through which the significance tests for these two fundamental quantities in the wavelet analysis were established. It was found that the results given by Torrence and Compo (1998) are numerically accurate when adjusted by a factor of the sampling period, while some of their statements require reassessment. More importantly, the sampling distribution of the wavelet power spectrum of a GWN was found to be highly dependent on the local covariance structure of the wavelets, a fact that makes the significance levels intimately related to the specific wavelet family. In addition to simulated signals, the significance tests developed in this work were demonstrated on an actual wave elevation time series observed from a buoy on Lake Michigan. In this simple application in geophysics, we showed how proper significance tests helped to sort out physically meaningful peaks from those created by random noise. The derivations in the present work can be readily extended to other wavelet-based quantities or analyses using other wavelet families.
NASA Astrophysics Data System (ADS)
Magarill, L. I.; Entin, M. V.
2016-12-01
The electron absorption and the edge photocurrent of a 2D topological insulator are studied for transitions between edge states to 2D states. The circular polarized light is found to produce the edge photocurrent, the direction of which is determined by light polarization and edge orientation. It is shown that the edge-state current is found to exceed the 2D current owing to the topological protection of the edge states.
Dinç, Erdal; Baleanu, Dumitru
2004-01-01
The discrete and continuous wavelet transforms were applied to the overlapping signal analysis of the ratio data signal for simultaneous quantitative determination of the title subject compounds in samples. The ratio spectra data of the binary mixtures containing benazepril (BE) and hydrochlorothiazide (HCT) were transferred as data vectors into the wavelet domain. Signal compression, followed by a 1-dimension continuous wavelet transform (CWT), was used to obtain coincident transformed signals for pure BE and HCT and their mixtures. The coincident transformed amplitudes corresponding to both maximum and minimum points allowed construction of calibration graphs for each compound in the binary mixture. The validity of CWT calibrations was tested by analyzing synthetic mixtures of the investigated compounds, and successful results were obtained. All calculations were performed within EXCEL, C++, and MATLAB6.5 softwares. The obtained results indicated that our approach was flexible and applicable for the binary mixture analysis.
NASA Astrophysics Data System (ADS)
Harikumar, Rajaguru; Vijayakumar, Thangavel
2014-12-01
The objective of this paper is to compare the performance of singular value decomposition (SVD), expectation maximization (EM), and modified expectation maximization (MEM) as the postclassifiers for classifications of the epilepsy risk levels obtained from extracted features through wavelet transforms and morphological filters from electroencephalogram (EEG) signals. The code converter acts as a level one classifier. The seven features such as energy, variance, positive and negative peaks, spike and sharp waves, events, average duration, and covariance are extracted from EEG signals. Out of which four parameters like positive and negative peaksand spike and sharp waves, events and average duration are extracted using Haar, dB2, dB4, and Sym 8 wavelet transforms with hard and soft thresholding methods. The above said four features are also extracted through morphological filters. Then, the performance of the code converter and classifiers are compared based on the parameters such as performance index (PI) and quality value (QV).The performance index and quality value of code converters are at low value of 33.26% and 12.74, respectively. The highest PI of 98.03% and QV of 23.82 are attained at dB2 wavelet with hard thresholding method for SVD classifier. All the postclassifiers are settled at PI value of more than 90% at QV of 20.
Novel wavelet coder for color image compression
NASA Astrophysics Data System (ADS)
Wang, Houng-Jyh M.; Kuo, C.-C. Jay
1997-10-01
A new still image compression algorithm based on the multi-threshold wavelet coding (MTWC) technique is proposed in this work. It is an embedded wavelet coder in the sense that its compression ratio can be controlled depending on the bandwidth requirement of image transmission. At low bite rates, MTWC can avoid the blocking artifact from JPEG to result in a better reconstructed image quality. An subband decision scheme is developed based on the rate-distortion theory to enhance the image fidelity. Moreover, a new quantization sequence order is introduced based on our analysis of error energy reduction in significant and refinement maps. Experimental results are given to demonstrate the superior performance of the proposed new algorithm in its high reconstructed quality for color and gray level image compression and low computational complexity. Generally speaking, it gives a better rate- distortion tradeoff and performs faster than most existing state-of-the-art wavelet coders.
Applicability analysis of wavelet-transform profilometry.
Zhang, Zibang; Zhong, Jingang
2013-08-12
The applicability of the wavelet-transform profilometry is examined in detail. The wavelet-ridge-based phase demodulation is an integral operation of the fringe signal in the spatial domain. The accuracy of the phase demodulation is related to the local linearity of the phase modulated by the object surface. We present a more robust applicability condition which is based on the evaluation of the local linearity. Since high carrier frequency leads to the phase demodulation integral in a narrow interval and the narrow interval results in the high local linearity of modulated phase, we propose to increase the carrier fringe frequency to improve the applicability of the wavelet-transform profilometry and the measurement accuracy. The numerical simulations and the experiment are presented.
Wavelet Analysis for Wind Fields Estimation
Leite, Gladeston C.; Ushizima, Daniela M.; Medeiros, Fátima N. S.; de Lima, Gilson G.
2010-01-01
Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B3 spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms−1. Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms. PMID:22219699
Wavelet analysis for wind fields estimation.
Leite, Gladeston C; Ushizima, Daniela M; Medeiros, Fátima N S; de Lima, Gilson G
2010-01-01
Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B(3) spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms(-1). Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms.
Predictive depth coding of wavelet transformed images
NASA Astrophysics Data System (ADS)
Lehtinen, Joonas
1999-10-01
In this paper, a new prediction based method, predictive depth coding, for lossy wavelet image compression is presented. It compresses a wavelet pyramid composition by predicting the number of significant bits in each wavelet coefficient quantized by the universal scalar quantization and then by coding the prediction error with arithmetic coding. The adaptively found linear prediction context covers spatial neighbors of the coefficient to be predicted and the corresponding coefficients on lower scale and in the different orientation pyramids. In addition to the number of significant bits, the sign and the bits of non-zero coefficients are coded. The compression method is tested with a standard set of images and the results are compared with SFQ, SPIHT, EZW and context based algorithms. Even though the algorithm is very simple and it does not require any extra memory, the compression results are relatively good.
Energy Efficiency of D2D Multi-User Cooperation.
Zhang, Zufan; Wang, Lu; Zhang, Jie
2017-03-28
The Device-to-Device (D2D) communication system is an important part of heterogeneous networks. It has great potential to improve spectrum efficiency, throughput and energy efficiency cooperation of multiple D2D users with the advantage of direct communication. When cooperating, D2D users expend extraordinary energy to relay data to other D2D users. Hence, the remaining energy of D2D users determines the life of the system. This paper proposes a cooperation scheme for multiple D2D users who reuse the orthogonal spectrum and are interested in the same data by aiming to solve the energy problem of D2D users. Considering both energy availability and the Signal to Noise Ratio (SNR) of each D2D user, the Kuhn-Munkres algorithm is introduced in the cooperation scheme to solve relay selection problems. Thus, the cooperation issue is transformed into a maximum weighted matching (MWM) problem. In order to enhance energy efficiency without the deterioration of Quality of Service (QoS), the link outage probability is derived according to the Shannon Equation by considering the data rate and delay. The simulation studies the relationships among the number of cooperative users, the length of shared data, the number of data packets and energy efficiency.
Integrating Mobile Multimedia into Textbooks: 2D Barcodes
ERIC Educational Resources Information Center
Uluyol, Celebi; Agca, R. Kagan
2012-01-01
The major goal of this study was to empirically compare text-plus-mobile phone learning using an integrated 2D barcode tag in a printed text with three other conditions described in multimedia learning theory. The method examined in the study involved modifications of the instructional material such that: a 2D barcode was used near the text, the…
Efficient Visible Quasi-2D Perovskite Light-Emitting Diodes.
Byun, Jinwoo; Cho, Himchan; Wolf, Christoph; Jang, Mi; Sadhanala, Aditya; Friend, Richard H; Yang, Hoichang; Lee, Tae-Woo
2016-09-01
Efficient quasi-2D-structure perovskite light-emitting diodes (4.90 cd A(-1) ) are demonstrated by mixing a 3D-structured perovskite material (methyl ammonium lead bromide) and a 2D-structured perovskite material (phenylethyl ammonium lead bromide), which can be ascribed to better film uniformity, enhanced exciton confinement, and reduced trap density.
Adaptation algorithms for 2-D feedforward neural networks.
Kaczorek, T
1995-01-01
The generalized weight adaptation algorithms presented by J.G. Kuschewski et al. (1993) and by S.H. Zak and H.J. Sira-Ramirez (1990) are extended for 2-D madaline and 2-D two-layer feedforward neural nets (FNNs).
Regulation of ligands for the NKG2D activating receptor
Raulet, David H.; Gasser, Stephan; Gowen, Benjamin G.; Deng, Weiwen; Jung, Heiyoun
2014-01-01
NKG2D is an activating receptor expressed by all NK cells and subsets of T cells. It serves as a major recognition receptor for detection and elimination of transformed and infected cells and participates in the genesis of several inflammatory diseases. The ligands for NKG2D are self-proteins that are induced by pathways that are active in certain pathophysiological states. NKG2D ligands are regulated transcriptionally, at the level of mRNA and protein stability, and by cleavage from the cell surface. In some cases, ligand induction can be attributed to pathways that are activated specifically in cancer cells or infected cells. We review the numerous pathways that have been implicated in the regulation of NKG2D ligands, discuss the pathologic states in which those pathways are likely to act, and attempt to synthesize the findings into general schemes of NKG2D ligand regulation in NK cell responses to cancer and infection. PMID:23298206
2D materials and van der Waals heterostructures.
Novoselov, K S; Mishchenko, A; Carvalho, A; Castro Neto, A H
2016-07-29
The physics of two-dimensional (2D) materials and heterostructures based on such crystals has been developing extremely fast. With these new materials, truly 2D physics has begun to appear (for instance, the absence of long-range order, 2D excitons, commensurate-incommensurate transition, etc.). Novel heterostructure devices--such as tunneling transistors, resonant tunneling diodes, and light-emitting diodes--are also starting to emerge. Composed from individual 2D crystals, such devices use the properties of those materials to create functionalities that are not accessible in other heterostructures. Here we review the properties of novel 2D crystals and examine how their properties are used in new heterostructure devices.
New generation transistor technologies enabled by 2D crystals
NASA Astrophysics Data System (ADS)
Jena, D.
2013-05-01
The discovery of graphene opened the door to 2D crystal materials. The lack of a bandgap in 2D graphene makes it unsuitable for electronic switching transistors in the conventional field-effect sense, though possible techniques exploiting the unique bandstructure and nanostructures are being explored. The transition metal dichalcogenides have 2D crystal semiconductors, which are well-suited for electronic switching. We experimentally demonstrate field effect transistors with current saturation and carrier inversion made from layered 2D crystal semiconductors such as MoS2, WS2, and the related family. We also evaluate the feasibility of such semiconducting 2D crystals for tunneling field effect transistors for low-power digital logic. The article summarizes the current state of new generation transistor technologies either proposed, or demonstrated, with a commentary on the challenges and prospects moving forward.
Efficient Combustion Simulation via the Adaptive Wavelet Collocation Method
NASA Astrophysics Data System (ADS)
Lung, Kevin; Brown-Dymkoski, Eric; Guerrero, Victor; Doran, Eric; Museth, Ken; Balme, Jo; Urberger, Bob; Kessler, Andre; Jones, Stephen; Moses, Billy; Crognale, Anthony
Rocket engine development continues to be driven by the intuition and experience of designers, progressing through extensive trial-and-error test campaigns. Extreme temperatures and pressures frustrate direct observation, while high-fidelity simulation can be impractically expensive owing to the inherent muti-scale, multi-physics nature of the problem. To address this cost, an adaptive multi-resolution PDE solver has been designed which targets the high performance, many-core architecture of GPUs. The adaptive wavelet collocation method is used to maintain a sparse-data representation of the high resolution simulation, greatly reducing the memory footprint while tightly controlling physical fidelity. The tensorial, stencil topology of wavelet-based grids lends itself to highly vectorized algorithms which are necessary to exploit the performance of GPUs. This approach permits efficient implementation of direct finite-rate kinetics, and improved resolution of steep thermodynamic gradients and the smaller mixing scales that drive combustion dynamics. Resolving these scales is crucial for accurate chemical kinetics, which are typically degraded or lost in statistical modeling approaches.
A Wavelet Analysis Approach for Categorizing Air Traffic Behavior
NASA Technical Reports Server (NTRS)
Drew, Michael; Sheth, Kapil
2015-01-01
In this paper two frequency domain techniques are applied to air traffic analysis. The Continuous Wavelet Transform (CWT), like the Fourier Transform, is shown to identify changes in historical traffic patterns caused by Traffic Management Initiatives (TMIs) and weather with the added benefit of detecting when in time those changes take place. Next, with the expectation that it could detect anomalies in the network and indicate the extent to which they affect traffic flows, the Spectral Graph Wavelet Transform (SGWT) is applied to a center based graph model of air traffic. When applied to simulations based on historical flight plans, it identified the traffic flows between centers that have the greatest impact on either neighboring flows, or flows between centers many centers away. Like the CWT, however, it can be difficult to interpret SGWT results and relate them to simulations where major TMIs are implemented, and more research may be warranted in this area. These frequency analysis techniques can detect off-nominal air traffic behavior, but due to the nature of air traffic time series data, so far they prove difficult to apply in a way that provides significant insight or specific identification of traffic patterns.
Numerical Algorithms Based on Biorthogonal Wavelets
NASA Technical Reports Server (NTRS)
Ponenti, Pj.; Liandrat, J.
1996-01-01
Wavelet bases are used to generate spaces of approximation for the resolution of bidimensional elliptic and parabolic problems. Under some specific hypotheses relating the properties of the wavelets to the order of the involved operators, it is shown that an approximate solution can be built. This approximation is then stable and converges towards the exact solution. It is designed such that fast algorithms involving biorthogonal multi resolution analyses can be used to resolve the corresponding numerical problems. Detailed algorithms are provided as well as the results of numerical tests on partial differential equations defined on the bidimensional torus.
Turbulence dynamics in the wavelet representation
NASA Technical Reports Server (NTRS)
Meneveau, C.
1990-01-01
The phenomenon of small-scale intermittency is shown to motivate the decomposition of the velocity fields into modes that exhibit both localization in wavenumber and physical space. We review some basic properties of such a decomposition, called the wavelet transform. The wavelet-transformed Navier-Stokes equations are derived, and we define a new quantity Pi(r, vector-x, t), which is the flux of kinetic energy to scales smaller than r at position vector-x (at time t). The main goals of this research are also summarized.
Analysis of wavelet technology for NASA applications
NASA Technical Reports Server (NTRS)
Wells, R. O., Jr.
1994-01-01
The purpose of this grant was to introduce a broad group of NASA researchers and administrators to wavelet technology and to determine its future role in research and development at NASA JSC. The activities of several briefings held between NASA JSC scientists and Rice University researchers are discussed. An attached paper, 'Recent Advances in Wavelet Technology', summarizes some aspects of these briefings. Two proposals submitted to NASA reflect the primary areas of common interest. They are image analysis and numerical solutions of partial differential equations arising in computational fluid dynamics and structural mechanics.
Scalable still image coding based on wavelet
NASA Astrophysics Data System (ADS)
Yan, Yang; Zhang, Zhengbing
2005-02-01
The scalable image coding is an important objective of the future image coding technologies. In this paper, we present a kind of scalable image coding scheme based on wavelet transform. This method uses the famous EZW (Embedded Zero tree Wavelet) algorithm; we give a high-quality encoding to the ROI (region of interest) of the original image and a rough encoding to the rest. This method is applied well in limited memory space condition, and we encode the region of background according to the memory capacity. In this way, we can store the encoded image in limited memory space easily without losing its main information. Simulation results show it is effective.
Wavelet encoding and variable resolution progressive transmission
NASA Technical Reports Server (NTRS)
Blanford, Ronald P.
1993-01-01
Progressive transmission is a method of transmitting and displaying imagery in stages of successively improving quality. The subsampled lowpass image representations generated by a wavelet transformation suit this purpose well, but for best results the order of presentation is critical. Candidate data for transmission are best selected using dynamic prioritization criteria generated from image contents and viewer guidance. We show that wavelets are not only suitable but superior when used to encode data for progressive transmission at non-uniform resolutions. This application does not preclude additional compression using quantization of highpass coefficients, which to the contrary results in superior image approximations at low data rates.
Wavelet analysis applied to the IRAS cirrus
NASA Technical Reports Server (NTRS)
Langer, William D.; Wilson, Robert W.; Anderson, Charles H.
1994-01-01
The structure of infrared cirrus clouds is analyzed with Laplacian pyramid transforms, a form of non-orthogonal wavelets. Pyramid and wavelet transforms provide a means to decompose images into their spatial frequency components such that all spatial scales are treated in an equivalent manner. The multiscale transform analysis is applied to IRAS 100 micrometer maps of cirrus emission in the north Galactic pole region to extract features on different scales. In the maps we identify filaments, fragments and clumps by separating all connected regions. These structures are analyzed with respect to their Hausdorff dimension for evidence of the scaling relationships in the cirrus clouds.
[Application of wavelet transform to infrared analysis].
Li, Dan-ting; Zhang, Chang-jiang; Wang, Jin; Cheng, Cun-gui
2006-11-01
In the present article the FTIR spectra of the xylems of Smilax glabra Roxb. and its three kinds of counterfeits were obtained by Fourier transform infrared spectroscopy (FTIR) with OMNI-sampler directly, fast and accurately. By adopting wavelet transform analytical method the samples were studied in detail. The results showed that wavelet transform could remove the noises and condense variable, and have the advantages of fast operating speed, high degree of accuracy, and no noise disposal. It will have a good application prospect in infrared spectroscopic analysis.
Estrogen-Induced Cholestasis Leads to Repressed CYP2D6 Expression in CYP2D6-Humanized Mice.
Pan, Xian; Jeong, Hyunyoung
2015-07-01
Cholestasis activates bile acid receptor farnesoid X receptor (FXR) and subsequently enhances hepatic expression of small heterodimer partner (SHP). We previously demonstrated that SHP represses the transactivation of cytochrome P450 2D6 (CYP2D6) promoter by hepatocyte nuclear factor (HNF) 4α. In this study, we investigated the effects of estrogen-induced cholestasis on CYP2D6 expression. Estrogen-induced cholestasis occurs in subjects receiving estrogen for contraception or hormone replacement, or in susceptible women during pregnancy. In CYP2D6-humanized transgenic (Tg-CYP2D6) mice, cholestasis triggered by administration of 17α-ethinylestradiol (EE2) at a high dose led to 2- to 3-fold decreases in CYP2D6 expression. This was accompanied by increased hepatic SHP expression and subsequent decreases in the recruitment of HNF4α to CYP2D6 promoter. Interestingly, estrogen-induced cholestasis also led to increased recruitment of estrogen receptor (ER) α, but not that of FXR, to Shp promoter, suggesting a predominant role of ERα in transcriptional regulation of SHP in estrogen-induced cholestasis. EE2 at a low dose (that does not cause cholestasis) also increased SHP (by ∼ 50%) and decreased CYP2D6 expression (by 1.5-fold) in Tg-CYP2D6 mice, the magnitude of differences being much smaller than that shown in EE2-induced cholestasis. Taken together, our data indicate that EE2-induced cholestasis increases SHP and represses CYP2D6 expression in Tg-CYP2D6 mice in part through ERα transactivation of Shp promoter.
Parallel object-oriented, denoising system using wavelet multiresolution analysis
Kamath, Chandrika; Baldwin, Chuck H.; Fodor, Imola K.; Tang, Nu A.
2005-04-12
The present invention provides a data de-noising system utilizing processors and wavelet denoising techniques. Data is read and displayed in different formats. The data is partitioned into regions and the regions are distributed onto the processors. Communication requirements are determined among the processors according to the wavelet denoising technique and the partitioning of the data. The data is transforming onto different multiresolution levels with the wavelet transform according to the wavelet denoising technique, the communication requirements, and the transformed data containing wavelet coefficients. The denoised data is then transformed into its original reading and displaying data format.
Mass spectrometry cancer data classification using wavelets and genetic algorithm.
Nguyen, Thanh; Nahavandi, Saeid; Creighton, Douglas; Khosravi, Abbas
2015-12-21
This paper introduces a hybrid feature extraction method applied to mass spectrometry (MS) data for cancer classification. Haar wavelets are employed to transform MS data into orthogonal wavelet coefficients. The most prominent discriminant wavelets are then selected by genetic algorithm (GA) to form feature sets. The combination of wavelets and GA yields highly distinct feature sets that serve as inputs to classification algorithms. Experimental results show the robustness and significant dominance of the wavelet-GA against competitive methods. The proposed method therefore can be applied to cancer classification models that are useful as real clinical decision support systems for medical practitioners.
Xie, Donghao; Ji, Ding-Kun; Zhang, Yue; Cao, Jun; Zheng, Hu; Liu, Lin; Zang, Yi; Li, Jia; Chen, Guo-Rong; James, Tony D; He, Xiao-Peng
2016-08-04
Here we demonstrate that 2D MoS2 can enhance the receptor-targeting and imaging ability of a fluorophore-labelled ligand. The 2D MoS2 has an enhanced working concentration range when compared with graphene oxide, resulting in the improved imaging of both cell and tissue samples.
Study on the FOG's signal based on wavelet
NASA Astrophysics Data System (ADS)
Tang, Ji-qiang; Fang, Jian-cheng; Zhang, Yan-shun
2006-11-01
In order to study on the fiber optical gyro (abbreviated as FOG) signal based on wavelet, this paper researches the FOG signal drift model and the properties of wavelet analyzed noise, introduces the wavelet filtering method, wavelet base selection, soft and hard threshold value de-noising algorithm and compulsive filtering based on The Haar wavelet. These threshold value filtering results of both of the soft and of the hard threshold value for the same wavelet base of db4 with the same Donoho threshold values and these results of compulsive filtering based on The Haar wavelet and db4 wavelet are presented also in this paper and then these main conclusions based on foregoing analysis are reached: Larger the resolving scale is, the filtering effect is more perfect. The soft threshold value filtering effect is better than that of the hard threshold value filtering at the cost of calculation when the threshold value is same. The zero shift of the compulsive filtering is least when both the wavelet and the resolving scale are same for these filtering methods. For the compulsive filtering with same wavelets, the filtering effect of Harr is better than that of db4 and the calculation of the former is fewer. Finally the author point out that applying the compulsive filtering with the Harr wavelet base and suitable resolving scale to the signal processing of FOG be helpful for the FOG's design and manufacturing.
Research of Gear Fault Detection in Morphological Wavelet Domain
NASA Astrophysics Data System (ADS)
Hong, Shi; Fang-jian, Shan; Bo, Cong; Wei, Qiu
2016-02-01
For extracting mutation information from gear fault signal and achieving a valid fault diagnosis, a gear fault diagnosis method based on morphological mean wavelet transform was designed. Morphological mean wavelet transform is a linear wavelet in the framework of morphological wavelet. Decomposing gear fault signal by this morphological mean wavelet transform could produce signal synthesis operators and detailed synthesis operators. For signal synthesis operators, it was just close to orginal signal, and for detailed synthesis operators, it contained fault impact signal or interference signal and could be catched. The simulation experiment result indicates that, compared with Fourier transform, the morphological mean wavelet transform method can do time-frequency analysis for original signal, effectively catch impact signal appears position; and compared with traditional linear wavelet transform, it has simple structure, easy realization, signal local extremum sensitivity and high denoising ability, so it is more adapted to gear fault real-time detection.
Denoising and robust non-linear wavelet analysis
NASA Astrophysics Data System (ADS)
Bruce, Andrew G.; Donoho, David L.; Gao, Hong-Ye; Martin, R. D.
1994-04-01
In a series of papers, Donoho and Johnstone develop a powerful theory based on wavelets for extracting non-smooth signals from noisy data. Several nonlinear smoothing algorithms are presented which provide high performance for removing Gaussian noise from a wide range of spatially inhomogeneous signals. However, like other methods based on the linear wavelet transform, these algorithms are very sensitive to certain types of non-Gaussian noise, such as outliers. In this paper, we develop outlier resistance wavelet transforms. In these transforms, outliers and outlier patches are localized to just a few scales. By using the outlier resistant wavelet transforms, we improve upon the Donoho and Johnstone nonlinear signal extraction methods. The outlier resistant wavelet algorithms are included with the S+Wavelets object-oriented toolkit for wavelet analysis.
1/f Noise decomposition in random telegraph signals using the wavelet transform
NASA Astrophysics Data System (ADS)
Principato, Fabio; Ferrante, Gaetano
2007-07-01
By using the continuous wavelet transform with Haar basis the second-order properties of the wavelet coefficients are derived for the random telegraph signal (RTS) and for the 1/f noise which is obtained by summation of many RTSs. The correlation structure of the Haar wavelet coefficients for these processes is found. For the wavelet spectrum of the 1/f noise some characteristics related to the distribution of the relaxation times of the RTS are derived. A statistical test based on the characterization of the time evolution of the scalogram is developed, which allows to detect non-stationarity in the times τ's which compose the 1/f process and to identify the time scales of the relaxation times where the non-stationarity is localized. The proposed method allows to distinguish noise signals with 1/f power spectral density generated by RTSs, and thus gives informations on the origin of this type of 1/f noise which cannot be obtained using the Fourier transform or other methods based on second-order statistical analysis. The reported treatment is applied to both simulated and experimental signals. The present analysis is based on the McWhorter [ 1/f Noise and germanium surface properties, in: R.H. Kingstone (Ed.), Semiconductor Surface Physics, University of Pennsylvania Press, Philadelphia, PA, 1957, pp. 207-228] model of low frequency electric noise, and the obtained results are expected to prove especially useful for semiconductor devices.
NASA Astrophysics Data System (ADS)
Ker, Stephan; Le Gonidec, Yves; Gibert, Dominique
2012-09-01
A wavelet-based method was presented in a previous work to introduce multiscale seismic attributes for high-resolution seismic data. Because of the limited frequency bandwidth of the seismic source, we observed distortions in the seismic attributes based on the wavelet response of the subsurface discontinuities (Le Gonidec et al.). In this paper, we go further in the seismic source-correction by considering Lévy alpha-stable distributions introduced in the formalism of the continuous wavelet transform (CWT). The wavelets are Gaussian derivative functions (GDF), characterized by a derivative order. We show that a high-resolution seismic source, after a classical signature processing, can be taken into account with a GDF. We demonstrate that in the framework of the Born approximation, the CWT of a seismic trace involving such a finite frequency bandwidth can be made equivalent to the CWT of the impulse response of the subsurface and is defined for a reduced range of dilations. We apply the method for the SYSIF seismic device (Marsset et al.; Ker et al.) and show that the source-corrections allow to define seismic attributes for layer thicknesses in the range [24; 115 cm]. We present the analysis for two seismic reflectors identified on a SYSIF profile, and we show that the source-corrected multiscale analysis quantifies their complex geometries.
Lipid-gramicidin interactions: dynamic structure of the boundary lipid by 2D-ELDOR.
Costa-Filho, Antonio J; Crepeau, Richard H; Borbat, Petr P; Ge, Mingtao; Freed, Jack H
2003-05-01
The use of 2D-electron-electron double resonance (2D-ELDOR) for the characterization of the boundary lipid in membrane vesicles of DPPC and gramicidin A' (GA) is reported. We show that 2D-ELDOR, with its enhanced spectral resolution to dynamic structure as compared with continuous-wave electron spin resonance, provides a reliable and useful way of studying lipid-protein interactions. The 2D-ELDOR spectra of the end-chain spin label 16-PC in DPPC/GA vesicles is composed of two components, which are assigned to the bulk lipids (with sharp auto peaks and crosspeaks) and to the boundary lipids (with broad auto peaks). Their distinction is clearest for higher temperatures and higher GA concentrations. The quantitative analysis of these spectra shows relatively faster motions and very low ordering for the end chain of the bulk lipids, whereas the boundary lipids show very high "y-ordering" and slower motions. The y-ordering represents a dynamic bending at the end of the boundary lipid acyl chain, which can then coat the GA molecules. These results are consistent with the previous studies by Ge and Freed (1999) using continuous-wave electron spin resonance, thereby supporting their model for GA aggregation and H(II) phase formation for high GA concentrations. Improved instrumental and simulation methods have been employed.
Efficient 2D MRI relaxometry using compressed sensing
NASA Astrophysics Data System (ADS)
Bai, Ruiliang; Cloninger, Alexander; Czaja, Wojciech; Basser, Peter J.
2015-06-01
Potential applications of 2D relaxation spectrum NMR and MRI to characterize complex water dynamics (e.g., compartmental exchange) in biology and other disciplines have increased in recent years. However, the large amount of data and long MR acquisition times required for conventional 2D MR relaxometry limits its applicability for in vivo preclinical and clinical MRI. We present a new MR pipeline for 2D relaxometry that incorporates compressed sensing (CS) as a means to vastly reduce the amount of 2D relaxation data needed for material and tissue characterization without compromising data quality. Unlike the conventional CS reconstruction in the Fourier space (k-space), the proposed CS algorithm is directly applied onto the Laplace space (the joint 2D relaxation data) without compressing k-space to reduce the amount of data required for 2D relaxation spectra. This framework is validated using synthetic data, with NMR data acquired in a well-characterized urea/water phantom, and on fixed porcine spinal cord tissue. The quality of the CS-reconstructed spectra was comparable to that of the conventional 2D relaxation spectra, as assessed using global correlation, local contrast between peaks, peak amplitude and relaxation parameters, etc. This result brings this important type of contrast closer to being realized in preclinical, clinical, and other applications.
2D vs. 3D mammography observer study
NASA Astrophysics Data System (ADS)
Fernandez, James Reza F.; Hovanessian-Larsen, Linda; Liu, Brent
2011-03-01
Breast cancer is the most common type of non-skin cancer in women. 2D mammography is a screening tool to aid in the early detection of breast cancer, but has diagnostic limitations of overlapping tissues, especially in dense breasts. 3D mammography has the potential to improve detection outcomes by increasing specificity, and a new 3D screening tool with a 3D display for mammography aims to improve performance and efficiency as compared to 2D mammography. An observer study using a mammography phantom was performed to compare traditional 2D mammography with this ne 3D mammography technique. In comparing 3D and 2D mammography there was no difference in calcification detection, and mass detection was better in 2D as compared to 3D. There was a significant decrease in reading time for masses, calcifications, and normals in 3D compared to 2D, however, as well as more favorable confidence levels in reading normal cases. Given the limitations of the mammography phantom used, however, a clearer picture in comparing 3D and 2D mammography may be better acquired with the incorporation of human studies in the future.
Wei, Hongjiang; Zhang, Yuyao; Gibbs, Eric; Chen, Nan-Kuei; Wang, Nian; Liu, Chunlei
2017-04-01
Quantitative susceptibility mapping (QSM) measures tissue magnetic susceptibility and typically relies on time-consuming three-dimensional (3D) gradient-echo (GRE) MRI. Recent studies have shown that two-dimensional (2D) multi-slice gradient-echo echo-planar imaging (GRE-EPI), which is commonly used in functional MRI (fMRI) and other dynamic imaging techniques, can also be used to produce data suitable for QSM with much shorter scan times. However, the production of high-quality QSM maps is difficult because data obtained by 2D multi-slice scans often have phase inconsistencies across adjacent slices and strong susceptibility field gradients near air-tissue interfaces. To address these challenges in 2D EPI-based QSM studies, we present a new data processing procedure that integrates 2D and 3D phase processing. First, 2D Laplacian-based phase unwrapping and 2D background phase removal are performed to reduce phase inconsistencies between slices and remove in-plane harmonic components of the background phase. This is followed by 3D background phase removal for the through-plane harmonic components. The proposed phase processing was evaluated with 2D EPI data obtained from healthy volunteers, and compared against conventional 3D phase processing using the same 2D EPI datasets. Our QSM results were also compared with QSM values from time-consuming 3D GRE data, which were taken as ground truth. The experimental results show that this new 2D EPI-based QSM technique can produce quantitative susceptibility measures that are comparable with those of 3D GRE-based QSM across different brain regions (e.g. subcortical iron-rich gray matter, cortical gray and white matter). This new 2D EPI QSM reconstruction method is implemented within STI Suite, which is a comprehensive shareware for susceptibility imaging and quantification. Copyright © 2016 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Deliège, Adrien; Kleyntssens, Thomas; Nicolay, Samuel
2017-02-01
This work examines the scaling properties of Mars topography through a wavelet-based formalism. We conduct exhaustive one-dimensional (both longitudinal and latitudinal) and two-dimensional studies based on Mars Orbiter Laser Altimeter (MOLA) data using the multifractal formalism called Wavelet Leaders Method (WLM). This approach shows that a scale break occurs at approximately 15 km, giving two scaling regimes in both 1D and 2D cases. At small scales, these topographic profiles mostly display a monofractal behavior while a switch to multifractality is observed in several areas at larger scales. The scaling exponents extracted from this framework tend to be greater at small scales. In the 1D context, these observations are in agreement with previous works and thus suggest that the WLM is well-suited for examining scaling properties of topographic fields. Moreover, the 2D analysis is the first such complete study to our knowledge. It gives both a local and global insight on the scaling regimes of the surface of Mars and allows to exhibit the link between the scaling exponents and several famous features of the Martian topography. These results may be used as a solid basis for further investigations of the scaling laws of the Red planet and show that the WLM could be used to perform systematic analyses of the surface roughness of other celestial bodies.
NKG2D receptor and its ligands in host defense
Lanier, Lewis L.
2015-01-01
NKG2D is an activating receptor expressed on the surface of natural killer (NK) cells, CD8+ T cells, and subsets of CD4+ T cells, iNKT cells, and γδ T cells. In humans NKG2D transmits signals by its association with the DAP10 adapter subunit and in mice alternatively spliced isoforms transmit signals either using DAP10 or DAP12 adapter subunits. Although NKG2D is encoded by a highly conserved gene (KLRK1) with limited polymorphism, the receptor recognizes an extensive repertoire of ligands, encoded by at least 8 genes in humans (MICA, MICB, RAET1E, RAET1G, RAET1H, RAET1I, RAET1L, and RAET1N), some with extensive allelic polymorphism. Expression of the NKG2D ligands is tightly regulated at the level of transcription, translation, and post-translation. In general healthy adult tissues do not express NKG2D glycoproteins on the cell surface, but these ligands can be induced by hyper-proliferation and transformation, as well as when cells are infected by pathogens. Thus, the NKG2D pathway serves a mechanism for the immune system to detect and eliminate cells that have undergone “stress”. Viruses and tumor cells have devised numerous strategies to evade detection by the NKG2D surveillance system and diversification of the NKG2D ligand genes likely has been driven by selective pressures imposed by pathogens. NKG2D provides an attractive target for therapeutics in the treatment of infectious diseases, cancer, and autoimmune diseases. PMID:26041808
NKG2D Receptor and Its Ligands in Host Defense.
Lanier, Lewis L
2015-06-01
NKG2D is an activating receptor expressed on the surface of natural killer (NK) cells, CD8(+) T cells, and subsets of CD4(+) T cells, invariant NKT cells (iNKT), and γδ T cells. In humans, NKG2D transmits signals by its association with the DAP10 adapter subunit, and in mice alternatively spliced isoforms transmit signals either using DAP10 or DAP12 adapter subunits. Although NKG2D is encoded by a highly conserved gene (KLRK1) with limited polymorphism, the receptor recognizes an extensive repertoire of ligands, encoded by at least eight genes in humans (MICA, MICB, RAET1E, RAET1G, RAET1H, RAET1I, RAET1L, and RAET1N), some with extensive allelic polymorphism. Expression of the NKG2D ligands is tightly regulated at the level of transcription, translation, and posttranslation. In general, healthy adult tissues do not express NKG2D glycoproteins on the cell surface, but these ligands can be induced by hyperproliferation and transformation, as well as when cells are infected by pathogens. Thus, the NKG2D pathway serves as a mechanism for the immune system to detect and eliminate cells that have undergone "stress." Viruses and tumor cells have devised numerous strategies to evade detection by the NKG2D surveillance system, and diversification of the NKG2D ligand genes likely has been driven by selective pressures imposed by pathogens. NKG2D provides an attractive target for therapeutics in the treatment of infectious diseases, cancer, and autoimmune diseases.
2-D Versus 3-D Magnetotelluric Data Interpretation
NASA Astrophysics Data System (ADS)
Ledo, Juanjo
2005-09-01
In recent years, the number of publications dealing with the mathematical and physical 3-D aspects of the magnetotelluric method has increased drastically. However, field experiments on a grid are often impractical and surveys are frequently restricted to single or widely separated profiles. So, in many cases we find ourselves with the following question: is the applicability of the 2-D hypothesis valid to extract geoelectric and geological information from real 3-D environments? The aim of this paper is to explore a few instructive but general situations to understand the basics of a 2-D interpretation of 3-D magnetotelluric data and to determine which data subset (TE-mode or TM-mode) is best for obtaining the electrical conductivity distribution of the subsurface using 2-D techniques. A review of the mathematical and physical fundamentals of the electromagnetic fields generated by a simple 3-D structure allows us to prioritise the choice of modes in a 2-D interpretation of responses influenced by 3-D structures. This analysis is corroborated by numerical results from synthetic models and by real data acquired by other authors. One important result of this analysis is that the mode most unaffected by 3-D effects depends on the position of the 3-D structure with respect to the regional 2-D strike direction. When the 3-D body is normal to the regional strike, the TE-mode is affected mainly by galvanic effects, while the TM-mode is affected by galvanic and inductive effects. In this case, a 2-D interpretation of the TM-mode is prone to error. When the 3-D body is parallel to the regional 2-D strike the TE-mode is affected by galvanic and inductive effects and the TM-mode is affected mainly by galvanic effects, making it more suitable for 2-D interpretation. In general, a wise 2-D interpretation of 3-D magnetotelluric data can be a guide to a reasonable geological interpretation.
Fast algorithm of byte-to-byte wavelet transform for image compression applications
NASA Astrophysics Data System (ADS)
Pogrebnyak, Oleksiy B.; Sossa Azuela, Juan H.; Ramirez, Pablo M.
2002-11-01
A new fast algorithm of 2D DWT transform is presented. The algorithm operates on byte represented images and performs image transformation with the Cohen-Daubechies-Feauveau wavelet of the second order. It uses the lifting scheme for the calculations. The proposed algorithm is based on the "checkerboard" computation scheme for non-separable 2D wavelet. The problem of data extension near the image borders is resolved computing 1D Haar wavelet in the vicinity of the borders. With the checkerboard splitting, at each level of decomposition only one detail image is produced that simplify the further analysis for data compression. The calculations are rather simple, without any floating point operation allowing the implementation of the designed algorithm in fixed point DSP processors for fast, near real time processing. The proposed algorithm does not possesses perfect restoration of the processed data because of rounding that is introduced at each level of decomposition/restoration to perform operations with byte represented data. The designed algorithm was tested on different images. The criterion to estimate quantitatively the quality of the restored images was the well known PSNR. For the visual quality estimation the error maps between original and restored images were calculated. The obtained simulation results show that the visual and quantitative quality of the restored images is degraded with number of decomposition level increasing but is sufficiently high even after 6 levels. The introduced distortion are concentrated in the vicinity of high spatial activity details and are absent in the homogeneous regions. The designed algorithm can be used for image lossy compression and in noise suppression applications.
Recent advances in 2D materials for photocatalysis.
Luo, Bin; Liu, Gang; Wang, Lianzhou
2016-04-07
Two-dimensional (2D) materials have attracted increasing attention for photocatalytic applications because of their unique thickness dependent physical and chemical properties. This review gives a brief overview of the recent developments concerning the chemical synthesis and structural design of 2D materials at the nanoscale and their applications in photocatalytic areas. In particular, recent progress on the emerging strategies for tailoring 2D material-based photocatalysts to improve their photo-activity including elemental doping, heterostructure design and functional architecture assembly is discussed.
Comparison of 2D and 3D gamma analyses
Pulliam, Kiley B.; Huang, Jessie Y.; Howell, Rebecca M.; Followill, David; Kry, Stephen F.; Bosca, Ryan; O’Daniel, Jennifer
2014-02-15
Purpose: As clinics begin to use 3D metrics for intensity-modulated radiation therapy (IMRT) quality assurance, it must be noted that these metrics will often produce results different from those produced by their 2D counterparts. 3D and 2D gamma analyses would be expected to produce different values, in part because of the different search space available. In the present investigation, the authors compared the results of 2D and 3D gamma analysis (where both datasets were generated in the same manner) for clinical treatment plans. Methods: Fifty IMRT plans were selected from the authors’ clinical database, and recalculated using Monte Carlo. Treatment planning system-calculated (“evaluated dose distributions”) and Monte Carlo-recalculated (“reference dose distributions”) dose distributions were compared using 2D and 3D gamma analysis. This analysis was performed using a variety of dose-difference (5%, 3%, 2%, and 1%) and distance-to-agreement (5, 3, 2, and 1 mm) acceptance criteria, low-dose thresholds (5%, 10%, and 15% of the prescription dose), and data grid sizes (1.0, 1.5, and 3.0 mm). Each comparison was evaluated to determine the average 2D and 3D gamma, lower 95th percentile gamma value, and percentage of pixels passing gamma. Results: The average gamma, lower 95th percentile gamma value, and percentage of passing pixels for each acceptance criterion demonstrated better agreement for 3D than for 2D analysis for every plan comparison. The average difference in the percentage of passing pixels between the 2D and 3D analyses with no low-dose threshold ranged from 0.9% to 2.1%. Similarly, using a low-dose threshold resulted in a difference between the mean 2D and 3D results, ranging from 0.8% to 1.5%. The authors observed no appreciable differences in gamma with changes in the data density (constant difference: 0.8% for 2D vs 3D). Conclusions: The authors found that 3D gamma analysis resulted in up to 2.9% more pixels passing than 2D analysis. It must
Characterization and Simulation of Gunfire with Wavelets
Smallwood, David O.
1999-01-01
Gunfire is used as an example to show how the wavelet transform can be used to characterize and simulate nonstationary random events when an ensemble of events is available. The structural response to nearby firing of a high-firing rate gun has been characterized in several ways as a nonstationary random process. The current paper will explore a method to describe the nonstationary random process using a wavelet transform. The gunfire record is broken up into a sequence of transient waveforms each representing the response to the firing of a single round. A wavelet transform is performed on each of thesemore » records. The gunfire is simulated by generating realizations of records of a single-round firing by computing an inverse wavelet transform from Gaussian random coefficients with the same mean and standard deviation as those estimated from the previously analyzed gunfire record. The individual records are assembled into a realization of many rounds firing. A second-order correction of the probability density function is accomplished with a zero memory nonlinear function. The method is straightforward, easy to implement, and produces a simulated record much like the measured gunfire record.« less
Information retrieval system utilizing wavelet transform
Brewster, Mary E.; Miller, Nancy E.
2000-01-01
A method for automatically partitioning an unstructured electronically formatted natural language document into its sub-topic structure. Specifically, the document is converted to an electronic signal and a wavelet transform is then performed on the signal. The resultant signal may then be used to graphically display and interact with the sub-topic structure of the document.
Wavelet Analysis of Long GRB Profiles
NASA Astrophysics Data System (ADS)
Greene, J. E.; Norris, J. P.; Bonnell, J. T.
1997-12-01
Previously, time-dilation studies have been performed in which gamma-ray burst (GRB) time profiles were analyzed for average wavelet amplitude integrated over time, or in which widths of average profiles in peak registration were measured (e.g., Norris et al. 1994, ApJ, 424, 540). Here we investigate average wavelet amplitude as a function of position and timescale, using the 'Mexican Hat' as the orthonormal basis function. The sample consists of more than 825 long GRBs (duration > 2 s) recorded by the Burst and Transient Source Experiment (BATSE). In order to nullify brightness bias, signal-to-noise levels and intensities were equalized for all bursts in the sample. In the time dimension, profiles were peak-aligned, and ranked according to intensity into six brightness groups. We find that the average, peak-aligned wavelet transforms of dim bursts evince greater activity on longer timescales at all times than do bright bursts. We quantify the degree of self-similarity of this time-dilation effect by stretching and redshifting profiles of bright bursts by a factor of two and comparing their average wavelet transforms with those of dimmer burst groups.
Information retrieval system utilizing wavelet transform
Brewster, M.E.; Miller, N.E.
2000-05-30
A method is disclosed for automatically partitioning an unstructured electronically formatted natural language document into its sub-topic structure. Specifically, the document is converted to an electronic signal and a wavelet transform is then performed on the signal. The resultant signal may then be used to graphically display and interact with the sub-topic structure of the document.
Parallel adaptive wavelet collocation method for PDEs
Nejadmalayeri, Alireza; Vezolainen, Alexei; Brown-Dymkoski, Eric; Vasilyev, Oleg V.
2015-10-01
A parallel adaptive wavelet collocation method for solving a large class of Partial Differential Equations is presented. The parallelization is achieved by developing an asynchronous parallel wavelet transform, which allows one to perform parallel wavelet transform and derivative calculations with only one data synchronization at the highest level of resolution. The data are stored using tree-like structure with tree roots starting at a priori defined level of resolution. Both static and dynamic domain partitioning approaches are developed. For the dynamic domain partitioning, trees are considered to be the minimum quanta of data to be migrated between the processes. This allows fully automated and efficient handling of non-simply connected partitioning of a computational domain. Dynamic load balancing is achieved via domain repartitioning during the grid adaptation step and reassigning trees to the appropriate processes to ensure approximately the same number of grid points on each process. The parallel efficiency of the approach is discussed based on parallel adaptive wavelet-based Coherent Vortex Simulations of homogeneous turbulence with linear forcing at effective non-adaptive resolutions up to 2048{sup 3} using as many as 2048 CPU cores.
Parallel adaptive wavelet collocation method for PDEs
NASA Astrophysics Data System (ADS)
Nejadmalayeri, Alireza; Vezolainen, Alexei; Brown-Dymkoski, Eric; Vasilyev, Oleg V.
2015-10-01
A parallel adaptive wavelet collocation method for solving a large class of Partial Differential Equations is presented. The parallelization is achieved by developing an asynchronous parallel wavelet transform, which allows one to perform parallel wavelet transform and derivative calculations with only one data synchronization at the highest level of resolution. The data are stored using tree-like structure with tree roots starting at a priori defined level of resolution. Both static and dynamic domain partitioning approaches are developed. For the dynamic domain partitioning, trees are considered to be the minimum quanta of data to be migrated between the processes. This allows fully automated and efficient handling of non-simply connected partitioning of a computational domain. Dynamic load balancing is achieved via domain repartitioning during the grid adaptation step and reassigning trees to the appropriate processes to ensure approximately the same number of grid points on each process. The parallel efficiency of the approach is discussed based on parallel adaptive wavelet-based Coherent Vortex Simulations of homogeneous turbulence with linear forcing at effective non-adaptive resolutions up to 20483 using as many as 2048 CPU cores.
Gramatikov, B; Brinker, J; Yi-chun, S; Thakor, N V
2000-06-01
In a pilot study, electrocardiographic (ECG) recordings of patients with left and right coronary stenosis taken before and after angioplasty were analyzed using the continuous wavelet transform. Time-frequency distributions were obtained for different leads in order to examine the dynamics of the QRS-spectrum and establish features specific of ischemia in the time-frequency domain. We found relevant changes in the mid-frequency range, reflecting the ECG's response to percutaneous transluminal coronary angioplasty (PTCA). The changes appeared in ECG leads close to ischemic zones of the myocardium. Time-frequency distributions of the ECG during the QRS may thus become another electrocardiographic indicator of ischemia, alternative to ST-level in standard ECG or body surface mapping. The paper demonstrates the ability of the continuous wavelet transform to detect short lasting events of low amplitude superimposed on large signal deflections.
Investigation of aquifer-estuary interaction using wavelet analysis of fiber-optic temperature data
Henderson, R.D.; Day-Lewis, F. D.; Harvey, C.F.
2009-01-01
Fiber-optic distributed temperature sensing (FODTS) provides sub-minute temporal and meter-scale spatial resolution over kilometer-long cables. Compared to conventional thermistor or thermocouple-based technologies, which measure temperature at discrete (and commonly sparse) locations, FODTS offers nearly continuous spatial coverage, thus providing hydrologie information at spatiotemporal scales previously impossible. Large and information-rich FODTS datasets, however, pose challenges for data exploration and analysis. To date, FODTS analyses have focused on time-series variance as the means to discriminate between hydrologic phenomena. Here, we demonstrate the continuous wavelet transform (CWT) and cross-wavelet transform (XWT) to analyze FODTS in the context of related hydrologic time series. We apply the CWT and XWT to data from Waquoit Bay, Massachusetts to identify the location and timing of tidal pumping of submarine groundwater Copyright 2009 by the American Geophysical Union.
Classification of mammographic microcalcifications using wavelets
NASA Astrophysics Data System (ADS)
Chitre, Yateen S.; Dhawan, Atam P.; Moskowitz, Myron; Sarwal, Alok; Bonasso, Christine; Narayan, Suresh B.
1995-05-01
Breast cancer is the leading cause of death among women. Breast cancer can be detected earlier by mammography than any other non-invasive examination. About 30% to 50% of breast cancers demonstrate tiny granulelike deposits of calcium called microcalcifications. It is difficult to distinguish between benign and malignant cases based on an examination of calcification regions, especially in hard-to-diagnose cases. We investigate the potential of using energy and entropy features computed from wavelet packets for their correlation with malignancy. Two types of Daubechies discrete filters were used as prototype wavelets. The energy and entropy features were computed for 128 benign and 63 malignant cases and analyzed using a multivariate cluster analysis and a univariate statistical analysis to reduce the feature set to a `five best set of features.' The efficacy of the reduced feature set to discriminate between the malignant and benign categories was evaluated using different multilayer perceptron architectures. The multilayer perceptron was trained using the backpropagation algorithm for various training and test set sizes. For each case 40 partitions of the data set were used to set up the training and test sets. The performance of the features was evaluated by computing the best area under the relative operating characteristic (ROC) curve and the average area under the ROC curve. The performance of the features computed from the wavelet packets was compared to a second set of features consisting of the wavelet packet features, image structure features and cluster features. The classification results are encouraging and indicate the potential of using features derived from wavelet packets in discriminating microcalcification regions into benign and malignant categories.
Fingerprint data acquisition, desmearing, wavelet feature extraction, and identification
NASA Astrophysics Data System (ADS)
Szu, Harold H.; Hsu, Charles C.; Garcia, Joseph P.; Telfer, Brian A.
1995-04-01
In this paper, we present (1) a design concept of a fingerprint scanning system that can reject severely blurred inputs for retakes and then de-smear those less blurred prints. The de-smear algorithm is new and is based on the digital filter theory of the lossless QMF (quadrature mirror filter) subband coding. Then, we present (2) a new fingerprint minutia feature extraction methodology which uses a 2D STAR mother wavelet that can efficiently locate the fork feature anywhere on the fingerprints in parallel and is independent of its scale, shift, and rotation. Such a combined system can achieve high data compression to send through a binary facsimile machine that when combined with a tabletop computer can achieve the automatic finger identification systems (AFIS) using today's technology in the office environment. An interim recommendation for the National Crime Information Center is given about how to reduce the crime rate by an upgrade of today's police office technology in the light of the military expertise in ATR.
Unbalanced multiple description wavelet coding for scalable video transmission
NASA Astrophysics Data System (ADS)
Choupani, Roya; Wong, Stephan; Tolun, Mehmet
2012-10-01
Scalable video coding and multiple description coding are the two different adaptation schemes for video transmission over heterogeneous and best-effort networks such as the Internet. We propose a new method to encode video for unreliable networks with rate adaptation capability. Our proposed method groups three dimensional discrete wavelet transform coefficients in different descriptions and applies a modified embedded zero tree data for rate adaptation. The proposed method optimizes the bit-rates of the descriptions with respect to the channel bit rates and the maximum acceptable distortion. The experimental results in the presence of one description loss indicate that on average the videos at the rate of 1000 Kbit/s are reconstructed with Y-component of peak signal to noise ratio (Y-PSNR) value of 36.2 dB. The dynamic allocation of descriptions to the network channels is optimized for rate distortion minimization. The improvement in term of Y-PSNR achieved by rate distortion optimization has been between 0.7 and 5.3 dB in different bit rates.
Efficient architecture for adaptive directional lifting-based wavelet transform
NASA Astrophysics Data System (ADS)
Yin, Zan; Zhang, Li; Shi, Guangming
2010-07-01
Adaptive direction lifting-based wavelet transform (ADL) has better performance than conventional lifting both in image compression and de-noising. However, no architecture has been proposed to hardware implement it because of its high computational complexity and huge internal memory requirements. In this paper, we propose a four-stage pipelined architecture for 2 Dimensional (2D) ADL with fast computation and high data throughput. The proposed architecture comprises column direction estimation, column lifting, row direction estimation and row lifting which are performed in parallel in a pipeline mode. Since the column processed data is transposed, the row processor can reuse the column processor which can decrease the design complexity. In the lifting step, predict and update are also performed in parallel. For an 8×8 image sub-block, the proposed architecture can finish the ADL forward transform within 78 clock cycles. The architecture is implemented on Xilinx Virtex5 device on which the frequency can achieve 367 MHz. The processed time is 212.5 ns, which can meet the request of real-time system.
Discrete Wavelet Transforms: The Relationship of the a Trous and Mallat Algorithms
1991-12-01
single filter bank structure, the discrete wavelet transform, the behavior of which is governed by one’s choice of filters . In fact, the a trous algorithm...particulierSd’une unique structure banc de filtres, both special cases of a single filter bank structure, the appel6e transforme d’ondelettes discrete, dont le com...tie literature has been devoted to linking discrete implemen- filter bank output will be referred to as the Discrete tations to the continuous
Double resonance rotational spectroscopy of CH2D+
NASA Astrophysics Data System (ADS)
Töpfer, Matthias; Jusko, Pavol; Schlemmer, Stephan; Asvany, Oskar
2016-09-01
Context. Deuterated forms of CH are thought to be responsible for deuterium enrichment in lukewarm astronomical environments. There is no unambiguous detection of CH2D+ in space to date. Aims: Four submillimetre rotational lines of CH2D+ are documented in the literature. Our aim is to present a complete dataset of highly resolved rotational lines, including millimetre (mm) lines needed for a potential detection. Methods: We used a low-temperature ion trap and applied a novel IR-mm-wave double resonance method to measure the rotational lines of CH2D+. Results: We measured 21 low-lying (J ≤ 4) rotational transitions of CH2D+ between 23 GHz and 1.1 THz with accuracies close to 2 ppb.
Recovering 3D particle size distributions from 2D sections
NASA Astrophysics Data System (ADS)
Cuzzi, Jeffrey N.; Olson, Daniel M.
2017-03-01
We discuss different ways to convert observed, apparent particle size distributions from 2D sections (thin sections, SEM maps on planar surfaces, etc.) into true 3D particle size distributions. We give a simple, flexible, and practical method to do this; show which of these techniques gives the most faithful conversions; and provide (online) short computer codes to calculate both 2D-3D recoveries and simulations of 2D observations by random sectioning. The most important systematic bias of 2D sectioning, from the standpoint of most chondrite studies, is an overestimate of the abundance of the larger particles. We show that fairly good recoveries can be achieved from observed size distributions containing 100-300 individual measurements of apparent particle diameter.
Phonon thermal conduction in novel 2D materials
NASA Astrophysics Data System (ADS)
Xu, Xiangfan; Chen, Jie; Li, Baowen
2016-12-01
Recently, there has been increasing interest in phonon thermal transport in low-dimensional materials, due to the crucial importance of dissipating and managing heat in micro- and nano-electronic devices. Significant progress has been achieved for one-dimensional (1D) systems, both theoretically and experimentally. However, the study of heat conduction in two-dimensional (2D) systems is still in its infancy due to the limited availability of 2D materials and the technical challenges of fabricating suspended samples that are suitable for thermal measurements. In this review, we outline different experimental techniques and theoretical approaches for phonon thermal transport in 2D materials, discuss the problems and challenges of phonon thermal transport measurements and provide a comparison between existing experimental data. Special attention will be given to the effects of size, dimensionality, anisotropy and mode contributions in novel 2D systems, including graphene, boron nitride, MoS2, black phosphorous and silicene.
Recent developments in 2D layered inorganic nanomaterials for sensing
NASA Astrophysics Data System (ADS)
Kannan, Padmanathan Karthick; Late, Dattatray J.; Morgan, Hywel; Rout, Chandra Sekhar
2015-08-01
Two dimensional layered inorganic nanomaterials (2D-LINs) have recently attracted huge interest because of their unique thickness dependent physical and chemical properties and potential technological applications. The properties of these layered materials can be tuned via both physical and chemical processes. Some 2D layered inorganic nanomaterials like MoS2, WS2 and SnS2 have been recently developed and employed in various applications, including new sensors because of their layer-dependent electrical properties. This article presents a comprehensive overview of recent developments in the application of 2D layered inorganic nanomaterials as sensors. Some of the salient features of 2D materials for different sensing applications are discussed, including gas sensing, electrochemical sensing, SERS and biosensing, SERS sensing and photodetection. The working principles of the sensors are also discussed together with examples.
Phonon thermal conduction in novel 2D materials.
Xu, Xiangfan; Chen, Jie; Li, Baowen
2016-12-07
Recently, there has been increasing interest in phonon thermal transport in low-dimensional materials, due to the crucial importance of dissipating and managing heat in micro- and nano-electronic devices. Significant progress has been achieved for one-dimensional (1D) systems, both theoretically and experimentally. However, the study of heat conduction in two-dimensional (2D) systems is still in its infancy due to the limited availability of 2D materials and the technical challenges of fabricating suspended samples that are suitable for thermal measurements. In this review, we outline different experimental techniques and theoretical approaches for phonon thermal transport in 2D materials, discuss the problems and challenges of phonon thermal transport measurements and provide a comparison between existing experimental data. Special attention will be given to the effects of size, dimensionality, anisotropy and mode contributions in novel 2D systems, including graphene, boron nitride, MoS2, black phosphorous and silicene.
Exact Solution of Ising Model in 2d Shortcut Network
NASA Astrophysics Data System (ADS)
Shanker, O.
We give the exact solution to the Ising model in the shortcut network in the 2D limit. The solution is found by mapping the model to the square lattice model with Brascamp and Kunz boundary conditions.
Technical Review of the UNET2D Hydraulic Model
Perkins, William A.; Richmond, Marshall C.
2009-05-18
The Kansas City District of the US Army Corps of Engineers is engaged in a broad range of river management projects that require knowledge of spatially-varied hydraulic conditions such as velocities and water surface elevations. This information is needed to design new structures, improve existing operations, and assess aquatic habitat. Two-dimensional (2D) depth-averaged numerical hydraulic models are a common tool that can be used to provide velocity and depth information. Kansas City District is currently using a specific 2D model, UNET2D, that has been developed to meet the needs of their river engineering applications. This report documents a tech- nical review of UNET2D.
Reconstruction-based 3D/2D image registration.
Tomazevic, Dejan; Likar, Bostjan; Pernus, Franjo
2005-01-01
In this paper we present a novel 3D/2D registration method, where first, a 3D image is reconstructed from a few 2D X-ray images and next, the preoperative 3D image is brought into the best possible spatial correspondence with the reconstructed image by optimizing a similarity measure. Because the quality of the reconstructed image is generally low, we introduce a novel asymmetric mutual information similarity measure, which is able to cope with low image quality as well as with different imaging modalities. The novel 3D/2D registration method has been evaluated using standardized evaluation methodology and publicly available 3D CT, 3DRX, and MR and 2D X-ray images of two spine phantoms, for which gold standard registrations were known. In terms of robustness, reliability and capture range the proposed method outperformed the gradient-based method and the method based on digitally reconstructed radiographs (DRRs).
Alloyed 2D Metal-Semiconductor Atomic Layer Junctions.
Kim, Ah Ra; Kim, Yonghun; Nam, Jaewook; Chung, Hee-Suk; Kim, Dong Jae; Kwon, Jung-Dae; Park, Sang Won; Park, Jucheol; Choi, Sun Young; Lee, Byoung Hun; Park, Ji Hyeon; Lee, Kyu Hwan; Kim, Dong-Ho; Choi, Sung Mook; Ajayan, Pulickel M; Hahm, Myung Gwan; Cho, Byungjin
2016-03-09
Heterostructures of compositionally and electronically variant two-dimensional (2D) atomic layers are viable building blocks for ultrathin optoelectronic devices. We show that the composition of interfacial transition region between semiconducting WSe2 atomic layer channels and metallic NbSe2 contact layers can be engineered through interfacial doping with Nb atoms. WxNb1-xSe2 interfacial regions considerably lower the potential barrier height of the junction, significantly improving the performance of the corresponding WSe2-based field-effect transistor devices. The creation of such alloyed 2D junctions between dissimilar atomic layer domains could be the most important factor in controlling the electronic properties of 2D junctions and the design and fabrication of 2D atomic layer devices.
Dominant 2D magnetic turbulence in the solar wind
NASA Technical Reports Server (NTRS)
Bieber, John W.; Wanner, Wolfgang; Matthaeus, William H.
1995-01-01
There have been recent suggestions that solar wind magnetic turbulence may be a composite of slab geometry (wavevector aligned with the mean magnetic field) and 2D geometry (wavevectors perpendicular to the mean field). We report results of two new tests of this hypothesis using Helios measurements of inertial ranged magnetic spectra in the solar wind. The first test is based upon a characteristic difference between perpendicular and parallel reduced power spectra which is expected for the 2D component but not for the slab component. The second test examines the dependence of power spectrum density upon the magnetic field angle (i.e., the angle between the mean magnetic field and the radial direction), a relationship which is expected to be in opposite directions for the slab and 2D components. Both tests support the presence of a dominant (approximately 85 percent by energy) 2D component in solar wind magnetic turbulence.
Studying Zeolite Catalysts with a 2D Model System
Boscoboinik, Anibal
2016-12-07
Anibal Boscoboinik, a materials scientist at Brookhaven’s Center for Functional Nanomaterials, discusses the surface-science tools and 2D model system he uses to study catalysis in nanoporous zeolites, which catalyze reactions in many industrial processes.
ORION96. 2-d Finite Element Code Postprocessor
Sanford, L.A.; Hallquist, J.O.
1992-02-02
ORION is an interactive program that serves as a postprocessor for the analysis programs NIKE2D, DYNA2D, TOPAZ2D, and CHEMICAL TOPAZ2D. ORION reads binary plot files generated by the two-dimensional finite element codes currently used by the Methods Development Group at LLNL. Contour and color fringe plots of a large number of quantities may be displayed on meshes consisting of triangular and quadrilateral elements. ORION can compute strain measures, interface pressures along slide lines, reaction forces along constrained boundaries, and momentum. ORION has been applied to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.
Emerging and potential opportunities for 2D flexible nanoelectronics
NASA Astrophysics Data System (ADS)
Zhu, Weinan; Park, Saungeun; Akinwande, Deji
2016-05-01
The last 10 years have seen the emergence of two-dimensional (2D) nanomaterials such as graphene, transition metal dichalcogenides (TMDs), and black phosphorus (BP) among the growing portfolio of layered van der Waals thin films. Graphene, the prototypical 2D material has advanced rapidly in device, circuit and system studies that has resulted in commercial large-area applications. In this work, we provide a perspective of the emerging and potential translational applications of 2D materials including semiconductors, semimetals, and insulators that comprise the basic material set for diverse nanosystems. Applications include RF transceivers, smart systems, the so-called internet of things, and neurotechnology. We will review the DC and RF electronic performance of graphene and BP thin film transistors. 2D materials at sub-um channel length have so far enabled cut-off frequencies from baseband to 100GHz suitable for low-power RF and sub-THz concepts.