Sample records for wavelet leaders cumulant

  1. Joint multifractal analysis based on wavelet leaders (United States)

    Jiang, Zhi-Qiang; Yang, Yan-Hong; Wang, Gang-Jin; Zhou, Wei-Xing


    Mutually interacting components form complex systems and these components usually have long-range cross-correlated outputs. Using wavelet leaders, we propose a method for characterizing the joint multifractal nature of these long-range cross correlations; we call this method joint multifractal analysis based on wavelet leaders (MF-X-WL). We test the validity of the MF-X-WL method by performing extensive numerical experiments on dual binomial measures with multifractal cross correlations and bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. Both experiments indicate that MF-X-WL is capable of detecting cross correlations in synthetic data with acceptable estimating errors. We also apply the MF-X-WL method to pairs of series from financial markets (returns and volatilities) and online worlds (online numbers of different genders and different societies) and determine intriguing joint multifractal behavior.

  2. Parameters effective on estimating a nonstationary mixed-phase wavelet using cumulant matching approach (United States)

    Vosoughi, Ehsan; Javaherian, Abdolrahim


    Seismic inversion is a process performed to remove the effects of propagated wavelets in order to recover the acoustic impedance. To obtain valid velocity and density values related to subsurface layers through the inversion process, it is highly essential to perform reliable wavelet estimation such as cumulant matching approach. For this purpose, the seismic data were windowed in this work in such a way that two consecutive windows were only one sample apart. Also, we did not consider any fixed wavelet for any window and let the phase of each wavelet rotate in each sample in the window. Comparing the fourth order cumulant of the whitened trace and fourth-order moment of the all-pass operator in each window generated a cost function that should be minimized with a non-linear optimization method. In this regard, parameters effective on the estimation of the nonstationary mixed-phase wavelets were tested over the created nonstationary seismic trace at 0.82 s and 1.6 s. Besides, we compared the consequences of each parameter on estimated wavelets at two mentioned times. The parameters studied in this work are window length, taper type, the number of iteration, signal-to-noise ratio, bandwidth to central frequency ratio, and Q factor. The results show that applying the optimum values of the effective parameters, the average correlation of the estimated mixed-phase wavelets with the original ones is about 87%. Moreover, the effectiveness of the proposed approach was examined on a synthetic nonstationary seismic section with variable Q factor values alongside the time and offset axis. Eventually, the cumulant matching method was applied on a cross line of the migrated data from a 3D data set of an oilfield in the Persian Gulf. Also, the effect of the wrong Q estimation on the estimated mixed-phase wavelet was considered on the real data set. It is concluded that the accuracy of the estimated wavelet relied on the estimated Q and more than 10% error in the estimated value

  3. Wavelet Leaders: A new method to estimate the multifractal singularity spectra (United States)

    Serrano, E.; Figliola, A.


    Wavelet Leaders is a novel alternative based on wavelet analysis for estimating the Multifractal Spectrum. It was proposed by Jaffard and co-workers improving the usual wavelet methods. In this work, we analyze and compare it with the well known Multifractal Detrended Fluctuation Analysis. The latter is a comprehensible and well adapted method for natural and weakly stationary signals. Alternatively, Wavelet Leaders exploits the wavelet self-similarity structures combined with the Multiresolution Analysis scheme. We give a brief introduction on the multifractal formalism and the particular implementation of the above methods and we compare their effectiveness. We expose several cases: Cantor measures, Binomial Multiplicative Cascades and also natural series from a tonic-clonic epileptic seizure. We analyze the results and extract the conclusions.

  4. Arbitrary-order Hilbert spectral analysis for time series possessing scaling statistics: a comparison study with detrended fluctuation analysis and wavelet leaders

    CERN Document Server

    Huang, Y X; Hermand, J -P; Gagne, Y; Lu, Z M; Liu, Y L; 10.1103/PhysRevE.84.016208


    In this paper we present an extended version of Hilbert-Huang transform, namely arbitrary-order Hilbert spectral analysis, to characterize the scale-invariant properties of a time series directly in an amplitude-frequency space. We first show numerically that due to a nonlinear distortion, traditional methods require high-order harmonic components to represent nonlinear processes, except for the Hilbert-based method. This will lead to an artificial energy flux from the low-frequency (large scale) to the high-frequency (small scale) part. Thus the power law, if it exists, is contaminated. We then compare the Hilbert method with structure functions (SF), detrended fluctuation analysis (DFA), and wavelet leader (WL) by analyzing fractional Brownian motion and synthesized multifractal time series. For the former simulation, we find that all methods provide comparable results. For the latter simulation, we perform simulations with an intermittent parameter {\\mu} = 0.15. We find that the SF underestimates scaling e...

  5. Discovering Wavelets

    CERN Document Server

    Aboufadel, Edward


    An accessible and practical introduction to wavelets. With applications in image processing, audio restoration, seismology, and elsewhere, wavelets have been the subject of growing excitement and interest over the past several years. Unfortunately, most books on wavelets are accessible primarily to research mathematicians. Discovering Wavelets presents basic and advanced concepts of wavelets in a way that is accessible to anyone with only a fundamental knowledge of linear algebra. The basic concepts of wavelet theory are introduced in the context of an explanation of how the FBI uses wavelets

  6. Log wavelet leaders cumulant based multifractal analysis of EVI fMRI time series: evidence of scaling in ongoing and evoked brain activity

    Energy Technology Data Exchange (ETDEWEB)

    Ciuciu, P.; Rabrait, C. [CEA, Neuro Spin, Gif Sur Yvette (France); Abry, P.; Wendt, H. [Ecole Normale Super Lyon, Phys Lab, CNRS, UMR 5672, Lyon (France)


    Classical within-subject analysis in functional magnetic resonance imaging (fMRI) relies on a detection step to localize which parts of the brain are activated by a given stimulus type. This is usually achieved using model-based approaches. Here, we propose an alternative exploratory analysis. The originality of this contribution is twofold. First, we propose a synthetic, consistent, and comparative overview of the various stochastic processes and estimation procedures used to model and analyze scale invariance. Notably, it is explained how multifractal models are more versatile to adjust the scaling properties of fMRI data but require more elaborated analysis procedures. Second, we bring evidence of the existence of actual scaling in fMRI time series that are clearly disentangled from putative superimposed non-stationarities. By nature, scaling analysis requires the use of long enough signals with high frequency sampling rate. To this end, we make use of a localized 3-D echo volume imaging (EVI) technique, which has recently emerged in fMRI because it allows very fast acquisitions of successive brain volumes. High temporal resolution EVI fMRI data have been acquired both in resting state and during a slow event-related visual paradigm. A voxel-based systematic multifractal analysis has been performed over both kinds of data. Combining multifractal attribute estimates together with paired statistical tests, we observe significant scaling parameter changes between ongoing and evoked brain activity, which clearly validate an increase in long memory and suggest a global multi-fractality decrease effect under activation. (authors)

  7. Wavelet basics

    CERN Document Server

    Chan, Y T


    Since the study of wavelets is a relatively new area, much of the research coming from mathematicians, most of the literature uses terminology, concepts and proofs that may, at times, be difficult and intimidating for the engineer. Wavelet Basics has therefore been written as an introductory book for scientists and engineers. The mathematical presentation has been kept simple, the concepts being presented in elaborate detail in a terminology that engineers will find familiar. Difficult ideas are illustrated with examples which will also aid in the development of an intuitive insight. Chapter 1 reviews the basics of signal transformation and discusses the concepts of duals and frames. Chapter 2 introduces the wavelet transform, contrasts it with the short-time Fourier transform and clarifies the names of the different types of wavelet transforms. Chapter 3 links multiresolution analysis, orthonormal wavelets and the design of digital filters. Chapter 4 gives a tour d'horizon of topics of current interest: wave...

  8. Wavelet applications in engineering electromagnetics

    National Research Council Canada - National Science Library

    Sarkar, Tapan; Salazar-Palma, Magdalena; Wicks, Michael C


    ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Road Map of the Book . . . . . . Introduction . . . . . . . . Why Use Wavelets? . . . . . . What Are Wavelets? . . . . . . What Is the Wavelet Transform? . . . Use...

  9. Adaptive Wavelet Transforms

    Energy Technology Data Exchange (ETDEWEB)

    Szu, H.; Hsu, C. [Univ. of Southwestern Louisiana, Lafayette, LA (United States)


    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.

  10. Some Results on the Wavelet Packet Decomposition of Nonstationary Processes

    Directory of Open Access Journals (Sweden)

    Sami Touati


    Full Text Available Wavelet/wavelet packet decomposition has become a very useful tool in describing nonstationary processes. Important examples of nonstationary processes encountered in practice are cyclostationary processes or almost-cyclostationary processes. In this paper, we study the statistical properties of the wavelet packet decomposition of a large class of nonstationary processes, including in particular cyclostationary and almost-cyclostationary processes. We first investigate in a general framework, the existence and some properties of the cumulants of wavelet packet coefficients. We then study more precisely the almost-cyclostationary case, and determine the asymptotic distributions of wavelet packet coefficients. Finally, we particularize some of our results in the cyclostationary case before providing some illustrative simulations.

  11. Multivariate wavelet frames

    CERN Document Server

    Skopina, Maria; Protasov, Vladimir


    This book presents a systematic study of multivariate wavelet frames with matrix dilation, in particular, orthogonal and bi-orthogonal bases, which are a special case of frames. Further, it provides algorithmic methods for the construction of dual and tight wavelet frames with a desirable approximation order, namely compactly supported wavelet frames, which are commonly required by engineers. It particularly focuses on methods of constructing them. Wavelet bases and frames are actively used in numerous applications such as audio and graphic signal processing, compression and transmission of information. They are especially useful in image recovery from incomplete observed data due to the redundancy of frame systems. The construction of multivariate wavelet frames, especially bases, with desirable properties remains a challenging problem as although a general scheme of construction is well known, its practical implementation in the multidimensional setting is difficult. Another important feature of wavelet is ...

  12. Wavelets, vibrations and scalings

    CERN Document Server

    Meyer, Yves


    Physicists and mathematicians are intensely studying fractal sets of fractal curves. Mandelbrot advocated modeling of real-life signals by fractal or multifractal functions. One example is fractional Brownian motion, where large-scale behavior is related to a corresponding infrared divergence. Self-similarities and scaling laws play a key role in this new area. There is a widely accepted belief that wavelet analysis should provide the best available tool to unveil such scaling laws. And orthonormal wavelet bases are the only existing bases which are structurally invariant through dyadic dilations. This book discusses the relevance of wavelet analysis to problems in which self-similarities are important. Among the conclusions drawn are the following: 1) A weak form of self-similarity can be given a simple characterization through size estimates on wavelet coefficients, and 2) Wavelet bases can be tuned in order to provide a sharper characterization of this self-similarity. A pioneer of the wavelet "saga", Meye...

  13. Wavelets in neuroscience

    CERN Document Server

    Hramov, Alexander E; Makarov, Valeri A; Pavlov, Alexey N; Sitnikova, Evgenia


    This book examines theoretical and applied aspects of wavelet analysis in neurophysics, describing in detail different practical applications of the wavelet theory in the areas of neurodynamics and neurophysiology and providing a review of fundamental work that has been carried out in these fields over the last decade. Chapters 1 and 2 introduce and review the relevant foundations of neurophysics and wavelet theory, respectively, pointing on one hand to the various current challenges in neuroscience and introducing on the other the mathematical techniques of the wavelet transform in its two variants (discrete and continuous) as a powerful and versatile tool for investigating the relevant neuronal dynamics. Chapter 3 then analyzes results from examining individual neuron dynamics and intracellular processes. The principles for recognizing neuronal spikes from extracellular recordings and the advantages of using wavelets to address these issues are described and combined with approaches based on wavelet neural ...

  14. Wavelets in scientific computing

    DEFF Research Database (Denmark)

    Nielsen, Ole Møller


    such a function well. These properties of wavelets have lead to some very successful applications within the field of signal processing. This dissertation revolves around the role of wavelets in scientific computing and it falls into three parts: Part I gives an exposition of the theory of orthogonal, compactly...

  15. Cumulants, free cumulants and half-shuffles. (United States)

    Ebrahimi-Fard, Kurusch; Patras, Frédéric


    Free cumulants were introduced as the proper analogue of classical cumulants in the theory of free probability. There is a mix of similarities and differences, when one considers the two families of cumulants. Whereas the combinatorics of classical cumulants is well expressed in terms of set partitions, that of free cumulants is described and often introduced in terms of non-crossing set partitions. The formal series approach to classical and free cumulants also largely differs. The purpose of this study is to put forward a different approach to these phenomena. Namely, we show that cumulants, whether classical or free, can be understood in terms of the algebra and combinatorics underlying commutative as well as non-commutative (half-)shuffles and (half-) unshuffles. As a corollary, cumulants and free cumulants can be characterized through linear fixed point equations. We study the exponential solutions of these linear fixed point equations, which display well the commutative, respectively non-commutative, character of classical and free cumulants.

  16. Wavelets and renormalization

    CERN Document Server

    Battle, G A


    WAVELETS AND RENORMALIZATION describes the role played by wavelets in Euclidean field theory and classical statistical mechanics. The author begins with a stream-lined introduction to quantum field theory from a rather basic point of view. Functional integrals for imaginary-time-ordered expectations are introduced early and naturally, while the connection with the statistical mechanics of classical spin systems is introduced in a later chapter.A vastly simplified (wavelet) version of the celebrated Glimm-Jaffe construction of the F 4 3 quantum field theory is presented. It is due to Battle and

  17. Wavelets in physics

    CERN Document Server

    Fang, Li-Zhi


    Recent advances have shown wavelets to be an effective, and even necessary, mathematical tool for theoretical physics. This book is a timely overview of the progress of this new frontier. It includes an introduction to wavelet analysis, and applications in the fields of high energy physics, astrophysics, cosmology and statistical physics. The topics are selected for the interests of physicists and graduate students of theoretical studies. It emphasizes the need for wavelets in describing and revealing structure in physical problems, which is not easily accomplishing by other methods.

  18. Wavelet analysis in neurodynamics (United States)

    Pavlov, Aleksei N.; Hramov, Aleksandr E.; Koronovskii, Aleksei A.; Sitnikova, Evgenija Yu; Makarov, Valeri A.; Ovchinnikov, Alexey A.


    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.

  19. Wavelets a primer

    CERN Document Server

    Blatter, Christian


    The Wavelet Transform has stimulated research that is unparalleled since the invention of the Fast Fourier Transform and has opened new avenues of applications in signal processing, image compression, radiology, cardiology, and many other areas. This book grew out of a short course for mathematics students at the ETH in Zurich; it provides a solid mathematical foundation for the broad range of applications enjoyed by the wavelet transform. Numerous illustrations and fully worked out examples enhance the book.

  20. The Soft Cumulative Constraint


    Petit, Thierry; Poder, Emmanuel


    This research report presents an extension of Cumulative of Choco constraint solver, which is useful to encode over-constrained cumulative problems. This new global constraint uses sweep and task interval violation-based algorithms.

  1. From Calculus to Wavelets: A New Mathematical Technique Wavelet ...

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 4. From Calculus to Wavelets: A New Mathematical Technique Wavelet Analysis Physical Properties. Gerald B Folland. General Article Volume 2 Issue 4 April 1997 pp 25-37 ...

  2. Lecture notes on wavelet transforms

    CERN Document Server

    Debnath, Lokenath


    This book provides a systematic exposition of the basic ideas and results of wavelet analysis suitable for mathematicians, scientists, and engineers alike. The primary goal of this text is to show how different types of wavelets can be constructed, illustrate why they are such powerful tools in mathematical analysis, and demonstrate their use in applications. It also develops the required analytical knowledge and skills on the part of the reader, rather than focus on the importance of more abstract formulation with full mathematical rigor.  These notes differs from many textbooks with similar titles in that a major emphasis is placed on the thorough development of the underlying theory before introducing applications and modern topics such as fractional Fourier transforms, windowed canonical transforms, fractional wavelet transforms, fast wavelet transforms, spline wavelets, Daubechies wavelets, harmonic wavelets and non-uniform wavelets. The selection, arrangement, and presentation of the material in these ...

  3. Target recognition by wavelet transform

    CERN Document Server

    Li Zheng Dong; He Wu Liang; Pei Chun Lan; Peng Wen; SongChen; Zheng Xiao Dong


    Wavelet transform has an important character of multi-resolution power, which presents pyramid structure, and this character coincides the way by which people distinguish object from coarse to fineness and from large to tiny. In addition to it, wavelet transform benefits to reducing image noise, simplifying calculation, and embodying target image characteristic point. A method of target recognition by wavelet transform is provided

  4. A Quantitative Analysis of an EEG Epileptic Record Based on MultiresolutionWavelet Coefficients

    Directory of Open Access Journals (Sweden)

    Mariel Rosenblatt


    Full Text Available The characterization of the dynamics associated with electroencephalogram (EEG signal combining an orthogonal discrete wavelet transform analysis with quantifiers originated from information theory is reviewed. In addition, an extension of this methodology based on multiresolution quantities, called wavelet leaders, is presented. In particular, the temporal evolution of Shannon entropy and the statistical complexity evaluated with different sets of multiresolution wavelet coefficients are considered. Both methodologies are applied to the quantitative EEG time series analysis of a tonic-clonic epileptic seizure, and comparative results are presented. In particular, even when both methods describe the dynamical changes of the EEG time series, the one based on wavelet leaders presents a better time resolution.

  5. Wavelet image compression

    CERN Document Server

    Pearlman, William A


    This book explains the stages necessary to create a wavelet compression system for images and describes state-of-the-art systems used in image compression standards and current research. It starts with a high level discussion of the properties of the wavelet transform, especially the decomposition into multi-resolution subbands. It continues with an exposition of the null-zone, uniform quantization used in most subband coding systems and the optimal allocation of bitrate to the different subbands. Then the image compression systems of the FBI Fingerprint Compression Standard and the JPEG2000 S

  6. Cumulative Poisson Distribution Program (United States)

    Bowerman, Paul N.; Scheuer, Ernest M.; Nolty, Robert


    Overflow and underflow in sums prevented. Cumulative Poisson Distribution Program, CUMPOIS, one of two computer programs that make calculations involving cumulative Poisson distributions. Both programs, CUMPOIS (NPO-17714) and NEWTPOIS (NPO-17715), used independently of one another. CUMPOIS determines cumulative Poisson distribution, used to evaluate cumulative distribution function (cdf) for gamma distributions with integer shape parameters and cdf for X (sup2) distributions with even degrees of freedom. Used by statisticians and others concerned with probabilities of independent events occurring over specific units of time, area, or volume. Written in C.

  7. Wavelets in functional data analysis

    CERN Document Server

    Morettin, Pedro A; Vidakovic, Brani


    Wavelet-based procedures are key in many areas of statistics, applied mathematics, engineering, and science. This book presents wavelets in functional data analysis, offering a glimpse of problems in which they can be applied, including tumor analysis, functional magnetic resonance and meteorological data. Starting with the Haar wavelet, the authors explore myriad families of wavelets and how they can be used. High-dimensional data visualization (using Andrews' plots), wavelet shrinkage (a simple, yet powerful, procedure for nonparametric models) and a selection of estimation and testing techniques (including a discussion on Stein’s Paradox) make this a highly valuable resource for graduate students and experienced researchers alike.

  8. Wavelets theory, algorithms, and applications

    CERN Document Server

    Montefusco, Laura


    Wavelets: Theory, Algorithms, and Applications is the fifth volume in the highly respected series, WAVELET ANALYSIS AND ITS APPLICATIONS. This volume shows why wavelet analysis has become a tool of choice infields ranging from image compression, to signal detection and analysis in electrical engineering and geophysics, to analysis of turbulent or intermittent processes. The 28 papers comprising this volume are organized into seven subject areas: multiresolution analysis, wavelet transforms, tools for time-frequency analysis, wavelets and fractals, numerical methods and algorithms, and applicat

  9. Wavelet Transform -50 ...

    Indian Academy of Sciences (India)

    University of Hyderabad. His current research interests are in the areas of quantum information ..... The enterprising reader can perform a multi-level decomposition and reconstruction to discover that the problems of overshoots and undershoots plaguing the Fourier transform are absent in discrete wavelet transform. 1kn&(ff.

  10. Boosted bosons and wavelets

    CERN Document Server

    Søgaard, Andreas

    For the LHC Run 2 and beyond, experiments are pushing both the energy and the intensity frontier so the need for robust and efficient pile-up mitigation tools becomes ever more pressing. Several methods exist, relying on uniformity of pile-up, local correlations of charged to neutral particles, and parton shower shapes, all in $y − \\phi$ space. Wavelets are presented as tools for pile-up removal, utilising their ability to encode position and frequency information simultaneously. This allows for the separation of individual hadron collision events by angular scale and thus for subtracting of soft, diffuse/wide-angle contributions while retaining the hard, small-angle components from the hard event. Wavelet methods may utilise the same assumptions as existing methods, the difference being the underlying, novel representation. Several wavelet methods are proposed and their effect studied in simple toy simulation under conditions relevant for the LHC Run 2. One full pile-up mitigation tool (‘wavelet analysis...

  11. Superstar Leaders


    Abhishek Goel; Neharika Vohra


    A common issue in organizations is handling larger than life leaders. These leaders often have "superstar" status in their field and the organization usually gets overwhelmed with their presence. Sometimes, narcissism in them can potentially hurt the organization in the long run. This case highlights a brilliant and charismatic leader in a healthcare institution who unknowingly becomes a bottleneck in the growth of its people and the organization. The case presents qualitative and quantitativ...

  12. Wavelets in medical imaging

    Energy Technology Data Exchange (ETDEWEB)

    Zahra, Noor e; Sevindir, Huliya A.; Aslan, Zafar; Siddiqi, A. H. [Sharda University, SET, Department of Electronics and Communication, Knowledge Park 3rd, Gr. Noida (India); University of Kocaeli, Department of Mathematics, 41380 Kocaeli (Turkey); Istanbul Aydin University, Department of Computer Engineering, 34295 Istanbul (Turkey); Sharda University, SET, Department of Mathematics, 32-34 Knowledge Park 3rd, Greater Noida (India)


    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.

  13. Wavelets in medical imaging (United States)

    Zahra, Noor e.; Sevindir, Hulya Kodal; Aslan, Zafer; Siddiqi, A. H.


    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.

  14. Everyday Leaders


    Vicki R. TenHaken


    For years business writers and speakers have focused on larger than life, charismatic Leaders, with a capital L. The implication is that the success of an organization is dependent on this one person and his or her ability to inspire everyone else to follow a unique vision. This focus on the Leader is at least a partial cause of the lack of trust we are witnessing in business organizations today. Leaders believe they must behave in some larger than life way. With the expectation that they mus...

  15. Influencing Leaders


    Alliston, John C.


    The Institute of Agricultural Management Leadership course first ran in 2002. The two objectives were to improve the leadership qualities of existing leaders, and to give time to consider how a clear forward vision of the industry could be achieved.

  16. Noise reduction by wavelet thresholding

    National Research Council Canada - National Science Library

    Jansen, Maarten


    .... I rather present new material and own insights in the que stions involved with wavelet based noise reduction . On the other hand , the presented material does cover a whole range of methodologies, and in that sense, the book may serve as an introduction into the domain of wavelet smoothing. Throughout the text, three main properties show up ever again: spar...

  17. The ssWavelets package (United States)

    Jeffrey H. Gove


    This package adds several classes, generics and associated methods as well as a few various functions to help with wavelet decomposition of sampling surfaces generated using sampSurf. As such, it can be thought of as an extension to sampSurf for wavelet analysis.

  18. Adaptive boxcar/wavelet transform (United States)

    Sezer, Osman G.; Altunbasak, Yucel


    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.

  19. Satellite image compression using wavelet (United States)

    Santoso, Alb. Joko; Soesianto, F.; Dwiandiyanto, B. Yudi


    Image data is a combination of information and redundancies, the information is part of the data be protected because it contains the meaning and designation data. Meanwhile, the redundancies are part of data that can be reduced, compressed, or eliminated. Problems that arise are related to the nature of image data that spends a lot of memory. In this paper will compare 31 wavelet function by looking at its impact on PSNR, compression ratio, and bits per pixel (bpp) and the influence of decomposition level of PSNR and compression ratio. Based on testing performed, Haar wavelet has the advantage that is obtained PSNR is relatively higher compared with other wavelets. Compression ratio is relatively better than other types of wavelets. Bits per pixel is relatively better than other types of wavelet.

  20. Wavelet frames and their duals

    DEFF Research Database (Denmark)

    Lemvig, Jakob


    frames with good time localization and other attractive properties. Furthermore, the dual wavelet frames are constructed in such a way that we are guaranteed that both frames will have the same desirable features. The construction procedure works for any real, expansive dilation. A quasi-affine system....... The signals are then represented by linear combinations of the building blocks with coefficients found by an associated frame, called a dual frame. A wavelet frame is a frame where the building blocks are stretched (dilated) and translated versions of a single function; such a frame is said to have wavelet...... structure. The dilation of the wavelet building blocks in higher dimension is done via a square matrix which is usually taken to be integer valued. In this thesis we step away from the "usual" integer, expansive dilation and consider more general, expansive dilations. In most applications of wavelet frames...

  1. Estimation of Seismic Wavelets Based on the Multivariate Scale Mixture of Gaussians Model

    Directory of Open Access Journals (Sweden)

    Jing-Huai Gao


    Full Text Available This paper proposes a new method for estimating seismic wavelets. Suppose a seismic wavelet can be modeled by a formula with three free parameters (scale, frequency and phase. We can transform the estimation of the wavelet into determining these three parameters. The phase of the wavelet is estimated by constant-phase rotation to the seismic signal, while the other two parameters are obtained by the Higher-order Statistics (HOS (fourth-order cumulant matching method. In order to derive the estimator of the Higher-order Statistics (HOS, the multivariate scale mixture of Gaussians (MSMG model is applied to formulating the multivariate joint probability density function (PDF of the seismic signal. By this way, we can represent HOS as a polynomial function of second-order statistics to improve the anti-noise performance and accuracy. In addition, the proposed method can work well for short time series.

  2. Applications of Wavelet Neural Network Model to Building Settlement Prediction: A Case Study

    Directory of Open Access Journals (Sweden)

    Qulin TAN


    Full Text Available Deformation monitoring is a significant work for engineering safety, which is performed throughout the entire process of engineering design, construction and operation. Based on the theoretic analysis of wavelet and neural network, we applied the improved BP neural network model, auxiliary wavelet neural network model and embedded wavelet neural network model to the settlement prediction in one practical engineering monitoring project with MATLAB software programming. The cumulative and the interval settlement was predicted and compared with measured data. The overall performances of the three models were analyzed and compared. The results show that the accuracies of two kinds of wavelet neural network models are roughly the same, which prediction errors of monitoring points are less than 1mm, obviously superior to the single BP neural network model.

  3. An Introduction to Wavelet Theory and Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Miner, N.E.


    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.

  4. Iris Recognition Using Wavelet

    Directory of Open Access Journals (Sweden)

    Khaliq Masood


    Full Text Available Biometric systems are getting more attention in the present era. Iris recognition is one of the most secure and authentic among the other biometrics and this field demands more authentic, reliable and fast algorithms to implement these biometric systems in real time. In this paper, an efficient localization technique is presented to identify pupil and iris boundaries using histogram of the iris image. Two small portions of iris have been used for polar transformation to reduce computational time and to increase the efficiency of the system. Wavelet transform is used for feature vector generation. Rotation of iris is compensated without shifts in the iris code. System is tested on Multimedia University Iris Database and results show that proposed system has encouraging performance.

  5. Gamma Splines and Wavelets

    Directory of Open Access Journals (Sweden)

    Hannu Olkkonen


    Full Text Available In this work we introduce a new family of splines termed as gamma splines for continuous signal approximation and multiresolution analysis. The gamma splines are born by -times convolution of the exponential by itself. We study the properties of the discrete gamma splines in signal interpolation and approximation. We prove that the gamma splines obey the two-scale equation based on the polyphase decomposition. to introduce the shift invariant gamma spline wavelet transform for tree structured subscale analysis of asymmetric signal waveforms and for systems with asymmetric impulse response. Especially we consider the applications in biomedical signal analysis (EEG, ECG, and EMG. Finally, we discuss the suitability of the gamma spline signal processing in embedded VLSI environment.

  6. From Fourier analysis to wavelets

    CERN Document Server

    Gomes, Jonas


    This text introduces the basic concepts of function spaces and operators, both from the continuous and discrete viewpoints.  Fourier and Window Fourier Transforms are introduced and used as a guide to arrive at the concept of Wavelet transform.  The fundamental aspects of multiresolution representation, and its importance to function discretization and to the construction of wavelets is also discussed. Emphasis is given on ideas and intuition, avoiding the heavy computations which are usually involved in the study of wavelets.  Readers should have a basic knowledge of linear algebra, calculus, and some familiarity with complex analysis.  Basic knowledge of signal and image processing is desirable. This text originated from a set of notes in Portuguese that the authors wrote for a wavelet course on the Brazilian Mathematical Colloquium in 1997 at IMPA, Rio de Janeiro.

  7. A new fractional wavelet transform (United States)

    Dai, Hongzhe; Zheng, Zhibao; Wang, Wei


    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.

  8. Wavelet transforms and their applications

    CERN Document Server

    Debnath, Lokenath


    This textbook is an introduction to wavelet transforms and accessible to a larger audience with diverse backgrounds and interests in mathematics, science, and engineering. Emphasis is placed on the logical development of fundamental ideas and systematic treatment of wavelet analysis and its applications to a wide variety of problems as encountered in various interdisciplinary areas. Numerous standard and challenging topics, applications, and exercises are included in this edition, which will stimulate research interest among senior undergraduate and graduate students. The book contains a large number of examples, which are either directly associated with applications or formulated in terms of the mathematical, physical, and engineering context in which wavelet theory arises. Topics and Features of the Second Edition: ·         Expanded and revised the historical introduction by including many new topics such as the fractional Fourier transform, and the construction of wavelet bases in various spaces ...

  9. Cumulative Timers for Microprocessors (United States)

    Battle, John O.


    It has been proposed to equip future microprocessors with electronic cumulative timers, for essentially the same reasons for which land vehicles are equipped with odometers (total-distance-traveled meters) and aircraft are equipped with Hobbs meters (total-engine-operating time meters). Heretofore, there has been no way to determine the amount of use to which a microprocessor (or a product containing a microprocessor) has been subjected. The proposed timers would count all microprocessor clock cycles and could only be read by means of microprocessor instructions but, like odometers and Hobbs meters, could never be reset to zero without physically damaging the chip.

  10. When Leaders Talk to Leaders


    Hart, Anton


    Presentations by three Canadian executives who influence healthcare policy and practice were reviewed to identify the kinds of sources these leaders use to draw their conclusions. All three speakers examined policies, practices and outcomes. Presentations were selected to cover activities in three provinces in three different calendar years, to avoid duplication or undue influence of a particular event or release of information. All three speakers drew heavily on data from government sources,...

  11. Wavelet analysis of bioimpendancometric data (United States)

    Dumler, A.; Zubarev, M.; Muraviev, N.; Mamatova, A.; Salnikova, N.; Podtaev, S.; Stepanov, R.; Frick, P.


    Up-to-date bioimpedancometric methods offer a wide spectrum of data that can be used for complex analysis of cardiovascular system state. Still, the use of appropriate mathematical approaches for data processing and calculation of main parameters is essential for confident diagnosis. The data processing problems are mainly connected with unavoidable noise sources, device noises, necessity to differentiate the registered data, pattern recognition of the structures responsible for specific fragments of the heart cycle and for the integral characteristics. In this work wavelet analysis is offered to resolve the various upcoming problems. Approaches based on decomposition of the analyzed signal on the base of special functions - wavelets - allow filtration of noises, artefacts and trends caused by side processes. They offer a wide spectrum of spectral and correlation analysis of synchronously recorded signals (for polyrheocardiograf those are impedance signals, cardiogram and phonocardiogram). Wavelet decomposition allows to distinguish high-frequency device noise from low-frequency variations caused by breathing, for example. Use of original wavelet differentiation algorithm allows to combine filtration and calculation of the derivatives of rheocardiogram. Time-spectral representation of the data on the surface forms the wavelet-portrait that gives images with relief markers of cardiac cycle phases. Utilization of the offered mathematical method raises the self-descriptiveness of impedancometric examination of cardiovascular system and makes more accurate the definition of traditional hemodynamic parameters.

  12. Cumulative environmental effects. Summary

    Energy Technology Data Exchange (ETDEWEB)



    This report presents a compilation of knowledge about the state of the environment and human activity in the Norwegian part of the North Sea and Skagerrak. The report gives an overview of pressures and impacts on the environment from normal activity and in the event of accidents. This is used to assess the cumulative environmental effects, which factors have most impact and where the impacts are greatest, and to indicate which problems are expected to be most serious in the future. The report is intended to provide relevant information that can be used in the management of the marine area in the future. It also provides input for the identification of environmental targets and management measures for the North Sea and Skagerrak.(Author)

  13. LEADER 2

    DEFF Research Database (Denmark)

    Daniels, G H; Hegedüs, L; Marso, S P


    AIMS: To report preliminary data on baseline serum calcitonin concentrations and associated clinical characteristics in a global population with type 2 diabetes before liraglutide or placebo randomization. METHODS: The ongoing LEADER trial has enrolled 9340 people with type 2 diabetes and at high...... committee of thyroid experts will oversee calcitonin monitoring throughout the trial and will review all calcitonin concentrations ≥20 ng/l. RESULTS: The mean age of participants was 64.3 ± 7.2 years, 64.3% were men, and mean the body mass index was 32.5 ± 6.3 kg/m(2) . The median (interquartile range...... with higher serum calcitonin concentrations that were statistically significant. A 20 ml/min/1.73 m(2) decrease in estimated GFR (eGFR) was associated with a 14% increase in serum calcitonin in women and an 11% increase in men. CONCLUSIONS: In the LEADER population, the prevalence of elevated serum calcitonin...

  14. Oversampling of wavelet frames for real dilations

    DEFF Research Database (Denmark)

    Bownik, Marcin; Lemvig, Jakob


    We generalize the Second Oversampling Theorem for wavelet frames and dual wavelet frames from the setting of integer dilations to real dilations. We also study the relationship between dilation matrix oversampling of semi-orthogonal Parseval wavelet frames and the additional shift invariance gain...

  15. On Fractals, Fractional Splines and Wavelets (United States)


    this picture. QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. From Goldberger, Rigney and West Heart Arterial tree Dendritic...this picture. Mandelbrot meets Mondrian 27 FRACTIONAL WAVELETS Basic ingredients Constructing fractional wavelets Fractional B-spline wavelets Multi

  16. Wavelets for sign language translation (United States)

    Wilson, Beth J.; Anspach, Gretel


    Wavelet techniques are applied to help extract the relevant parameters of sign language from video images of a person communicating in American Sign Language or Signed English. The compression and edge detection features of two-dimensional wavelet analysis are exploited to enhance the algorithms under development to classify the hand motion, hand location with respect to the body, and handshape. These three parameters have different processing requirements and complexity issues. The results are described for applying various quadrature mirror filter designs to a filterbank implementation of the desired wavelet transform. The overall project is to develop a system that will translate sign language to English to facilitate communication between deaf and hearing people.

  17. Wavelet-based associative memory (United States)

    Jones, Katharine J.


    Faces provide important characteristics of a person"s identification. In security checks, face recognition still remains the method in continuous use despite other approaches (i.e. fingerprints, voice recognition, pupil contraction, DNA scanners). With an associative memory, the output data is recalled directly using the input data. This can be achieved with a Nonlinear Holographic Associative Memory (NHAM). This approach can also distinguish between strongly correlated images and images that are partially or totally enclosed by others. Adaptive wavelet lifting has been used for Content-Based Image Retrieval. In this paper, adaptive wavelet lifting will be applied to face recognition to achieve an associative memory.

  18. Wavelet Analysis for Molecular Dynamics (United States)


    2480. 4. Ismail AE, Rutledge GC, Stephanopoulos G. Topological coarse graining of polymer chains using wavelet-accelerated Monte Carlo. I. Freely...accelerated Monte Carlo. II. Self-avoiding chains. J Chem Phys. 2005;122:234902. 6. Coifman R, Maggioni M. Diffusion wavelets. Appl Comput Harm Anal...INFORMATION CTR DTIC OCA 2 (PDF) DIRECTOR US ARMY RESEARCH LAB RDRL CIO LL IMAL HRA MAIL & RECORDS MGMT 1 (PDF) GOVT PRINTG OFC A MALHOTRA 1 (PDF) DIR USARL RDRL WML B B RICE 21 INTENTIONALLY LEFT BLANK. 22

  19. A wavelet analysis of co-movements in Asian gold markets (United States)

    Das, Debojyoti; Kannadhasan, M.; Al-Yahyaee, Khamis Hamed; Yoon, Seong-Min


    This study assesses the cross-country co-movements of gold spot returns among the major gold consuming countries in Asia using wavelet-based analysis for a dataset spanning over 26 years. Wavelet-based analysis is used since it allows measuring co-movements in a time-frequency space. The results suggest intense and positive co-movements in Asia after the Asian financial crisis of 1997 at all frequencies. In addition, the Asian gold spot markets depict a state of impending perfect market integration. Finally, Thailand emerges as the potential market leader in all wavelet scales except one, which is led by India. The study has important implications for international diversification of a single-asset (gold) portfolio.

  20. Practical wavelet signal processing for automated testing

    CERN Document Server

    Berry, S


    Wavelets are very versatile signal-processing tools that can be used in automated testing for noise reduction, edge detection, focus determination of video camera, and multi-scale frequency/time domain analysis of signals. This paper presents an overview of wavelets and discusses how examples of the use of wavelets in electrical and optical testing are explored. Tools and routines for using wavelets are discussed for several programming languages and software packages including C/ATLAS, C, WAVELAB, MATLAB and the MATLAB Wavelet toolbox. (15 refs).

  1. [Antimicrobial susceptibility cumulative reports]. (United States)

    Canut-Blasco, Andrés; Calvo, Jorge; Rodríguez-Díaz, Juan Carlos; Martínez-Martínez, Luis


    Cumulative reports on antimicrobial susceptibility tests data are important for selecting empirical treatments, as an educational tool in programs on antimicrobial use, and for establishing breakpoints defining clinical categories. These reports should be based on data validated by clinical microbiologists using diagnostic samples (not surveillance samples). In order to avoid a bias derived from including several isolates obtained from the same patient, it is recommended that, for a defined period, only the first isolate is counted. A minimal number of isolates per species should be presented: a figure of >=30 isolates is statistically acceptable. The report is usually presented in a table format where, for each cell, information on clinically relevant microorganisms-antimicrobial agents is presented. Depending on particular needs, multiple tables showing data related to patients, samples, services or special pathogens can be prepared. Copyright © 2015 Elsevier España, S.L.U. and Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

  2. Optimal Wavelets for Speech Signal Representations

    Directory of Open Access Journals (Sweden)

    Shonda L. Walker


    Full Text Available It is well known that in many speech processing applications, speech signals are characterized by their voiced and unvoiced components. Voiced speech components contain dense frequency spectrum with many harmonics. The periodic or semi-periodic nature of voiced signals lends itself to Fourier Processing. Unvoiced speech contains many high frequency components and thus resembles random noise. Several methods for voiced and unvoiced speech representations that utilize wavelet processing have been developed. These methods seek to improve the accuracy of wavelet-based speech signal representations using adaptive wavelet techniques, superwavelets, which uses a linear combination of adaptive wavelets, gaussian methods and a multi-resolution sinusoidal transform approach to mention a few. This paper addresses the relative performance of these wavelet methods and evaluates the usefulness of wavelet processing in speech signal representations. In addition, this paper will also address some of the hardware considerations for the wavelet methods presented.

  3. Army Leader Transitions Handbook (United States)

    2008-01-01 LEADER TRANSITION MODEL Leader Transitions Handbook 1 The Army Leader Transitions Handbook is designed to help leaders plan and...D-1) Managing transitions is a leadership responsibility. Leader transitions within the Army are significant events for any organization due to...current. Administrative skills - Brush up on personnel management , especially leader development. Know UCMJ, promotions, administrative discharge

  4. Online Wavelet Complementary velocity Estimator. (United States)

    Righettini, Paolo; Strada, Roberto; KhademOlama, Ehsan; Valilou, Shirin


    In this paper, we have proposed a new online Wavelet Complementary velocity Estimator (WCE) over position and acceleration data gathered from an electro hydraulic servo shaking table. This is a batch estimator type that is based on the wavelet filter banks which extract the high and low resolution of data. The proposed complementary estimator combines these two resolutions of velocities which acquired from numerical differentiation and integration of the position and acceleration sensors by considering a fixed moving horizon window as input to wavelet filter. Because of using wavelet filters, it can be implemented in a parallel procedure. By this method the numerical velocity is estimated without having high noise of differentiators, integration drifting bias and with less delay which is suitable for active vibration control in high precision Mechatronics systems by Direct Velocity Feedback (DVF) methods. This method allows us to make velocity sensors with less mechanically moving parts which makes it suitable for fast miniature structures. We have compared this method with Kalman and Butterworth filters over stability, delay and benchmarked them by their long time velocity integration for getting back the initial position data. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Wavelet library for constrained devices (United States)

    Ehlers, Johan Hendrik; Jassim, Sabah A.


    The wavelet transform is a powerful tool for image and video processing, useful in a range of applications. This paper is concerned with the efficiency of a certain fast-wavelet-transform (FWT) implementation and several wavelet filters, more suitable for constrained devices. Such constraints are typically found on mobile (cell) phones or personal digital assistants (PDA). These constraints can be a combination of; limited memory, slow floating point operations (compared to integer operations, most often as a result of no hardware support) and limited local storage. Yet these devices are burdened with demanding tasks such as processing a live video or audio signal through on-board capturing sensors. In this paper we present a new wavelet software library, HeatWave, that can be used efficiently for image/video processing/analysis tasks on mobile phones and PDA's. We will demonstrate that HeatWave is suitable for realtime applications with fine control and range to suit transform demands. We shall present experimental results to substantiate these claims. Finally this library is intended to be of real use and applied, hence we considered several well known and common embedded operating system platform differences; such as a lack of common routines or functions, stack limitations, etc. This makes HeatWave suitable for a range of applications and research projects.

  6. A Wavelet Perspective on the Allan Variance. (United States)

    Percival, Donald B


    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.

  7. Adaptive fuzzy wavelet network control of second order multi-agent systems with unknown nonlinear dynamics. (United States)

    Taheri, Mehdi; Sheikholeslam, Farid; Najafi, Majddedin; Zekri, Maryam


    In this paper, consensus problem is considered for second order multi-agent systems with unknown nonlinear dynamics under undirected graphs. A novel distributed control strategy is suggested for leaderless systems based on adaptive fuzzy wavelet networks. Adaptive fuzzy wavelet networks are employed to compensate for the effect of unknown nonlinear dynamics. Moreover, the proposed method is developed for leader following systems and leader following systems with state time delays. Lyapunov functions are applied to prove uniformly ultimately bounded stability of closed loop systems and to obtain adaptive laws. Three simulation examples are presented to illustrate the effectiveness of the proposed control algorithms. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  8. Algorithm Calculates Cumulative Poisson Distribution (United States)

    Bowerman, Paul N.; Nolty, Robert C.; Scheuer, Ernest M.


    Algorithm calculates accurate values of cumulative Poisson distribution under conditions where other algorithms fail because numbers are so small (underflow) or so large (overflow) that computer cannot process them. Factors inserted temporarily to prevent underflow and overflow. Implemented in CUMPOIS computer program described in "Cumulative Poisson Distribution Program" (NPO-17714).

  9. Wavelet-linear genetic programming: A new approach for modeling monthly streamflow (United States)

    Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur


    The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.

  10. A simple structure wavelet transform circuit employing function link neural networks and SI filters (United States)

    Mu, Li; Yigang, He


    Signal processing by means of analog circuits offers advantages from a power consumption viewpoint. Implementing wavelet transform (WT) using analog circuits is of great interest when low-power consumption becomes an important issue. In this article, a novel simple structure WT circuit in analog domain is presented by employing functional link neural network (FLNN) and switched-current (SI) filters. First, the wavelet base is approximated using FLNN algorithms for giving a filter transfer function that is suitable for simple structure WT circuit implementation. Next, the WT circuit is constructed with the wavelet filter bank, whose impulse response is the approximated wavelet and its dilations. The filter design that follows is based on a follow-the-leader feedback (FLF) structure with multiple output bilinear SI integrators and current mirrors as the main building blocks. SI filter is well suited for this application since the dilation constant across different scales of the transform can be precisely implemented and controlled by the clock frequency of the circuit with the same system architecture. Finally, to illustrate the design procedure, a seventh-order FLNN-approximated Gaussian wavelet is implemented as an example. Simulations have successfully verified that the designed simple structure WT circuit has low sensitivity, low-power consumption and litter effect to the imperfections.

  11. Cross wavelet analysis: significance testing and pitfalls

    Directory of Open Access Journals (Sweden)

    D. Maraun


    Full Text Available In this paper, we present a detailed evaluation of cross wavelet analysis of bivariate time series. We develop a statistical test for zero wavelet coherency based on Monte Carlo simulations. If at least one of the two processes considered is Gaussian white noise, an approximative formula for the critical value can be utilized. In a second part, typical pitfalls of wavelet cross spectra and wavelet coherency are discussed. The wavelet cross spectrum appears to be not suitable for significance testing the interrelation between two processes. Instead, one should rather apply wavelet coherency. Furthermore we investigate problems due to multiple testing. Based on these results, we show that coherency between ENSO and NAO is an artefact for most of the time from 1900 to 1995. However, during a distinct period from around 1920 to 1940, significant coherency between the two phenomena occurs.

  12. Modeling Network Traffic in Wavelet Domain

    Directory of Open Access Journals (Sweden)

    Sheng Ma


    Full Text Available This work discovers that although network traffic has the complicated short- and long-range temporal dependence, the corresponding wavelet coefficients are no longer long-range dependent. Therefore, a "short-range" dependent process can be used to model network traffic in the wavelet domain. Both independent and Markov models are investigated. Theoretical analysis shows that the independent wavelet model is sufficiently accurate in terms of the buffer overflow probability for Fractional Gaussian Noise traffic. Any model, which captures additional correlations in the wavelet domain, only improves the performance marginally. The independent wavelet model is then used as a unified approach to model network traffic including VBR MPEG video and Ethernet data. The computational complexity is O(N for developing such wavelet models and generating synthesized traffic of length N, which is among the lowest attained.

  13. Wavelet analysis of epileptic spikes

    CERN Document Server

    Latka, M; Kozik, A; West, B J; Latka, Miroslaw; Was, Ziemowit; Kozik, Andrzej; West, Bruce J.


    Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous, pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.

  14. Discrete frequency slice wavelet transform (United States)

    Yan, Zhonghong; Tao, Ting; Jiang, Zhongwei; Wang, Haibin


    This paper introduces a new kind of Time-Frequency Representation (TFR) method called Discrete Frequency Slice Wavelet Transform (DFSWT). It is an improved version of Frequency Slice Wavelet Transform (FSWT). The previous researches on FSWT show that it is a new efficient TFR in an easy way without strict limitation as traditional wavelet theory. DFSWT as well as FSWT are defined directly in frequency domain, and still keep its properties in time-frequency domain as FSWT decomposition, reconstruction and filter design, etc. However, the original signal is decomposed and reconstructed on a Chosen Frequency Domains (CFD) as need of application. CFD means that the decomposition and reconstruction are not completed on all frequency components. At first, it is important to discuss the necessary condition of CFD to reconstruct the original signal. And then based on norm l2, an optimization algorithm is introduced to reconstruct the original signal even accurately. Finally, for a test example, the TFR analysis of a real life signal is shown. Some conclusions are drawn that the concept of CFD is very useful to application, and the DFSWT can become a simple and easy tool of TFR method, and also provide a new idea of low speed sampling of high frequency signal in applications.

  15. Wavelets for Sparse Representation of Music

    DEFF Research Database (Denmark)

    Endelt, Line Ørtoft; Harbo, Anders La-Cour


    to the number of vanishing moments of the mother wavelet, and to the smoothness of the signal. In this paper we present the result of applying two classical families of wavelets to a series of musical signals. The purpose is to determine a general relation between the number of vanishing moments of the wavelet......We are interested in obtaining a sparse representation of music signals by means of a discrete wavelet transform (DWT). That means we want the energy in the representation to be concentrated in few DWT coefficients. It is well-known that the decay of the DWT coefficients is strongly related...

  16. Electric Equipment Diagnosis based on Wavelet Analysis (United States)

    Stavitsky, Sergey A.; Palukhin, Nikolay E.; Kobenko, Juri V.; Riabova, Elena S.


    Due to electric equipment development and complication it is necessary to have a precise and intense diagnosis. Nowadays there are two basic ways of diagnosis: analog signal processing and digital signal processing. The latter is more preferable. The basic ways of digital signal processing (Fourier transform and Fast Fourier transform) include one of the modern methods based on wavelet transform. This research is dedicated to analyzing characteristic features and advantages of wavelet transform. This article shows the ways of using wavelet analysis and the process of test signal converting. In order to carry out this analysis, computer software Mathcad was used and 2D wavelet spectrum for a complex function was created.

  17. Image Retrieval Based on Wavelet Features (United States)

    Murtagh, F.


    A dominant (additive, stationary) Gaussian noise component in image data will ensure that wavelet coefficients are of Gaussian distribution, and in such a case Shannon entropy quantifies the wavelet transformed data well. But we find that both Gaussian and long tailed distributions may well hold in practice for wavelet coefficients. We investigate entropy-related features based on different wavelet transforms and the newly developed curvelet transform. Using a materials grading case study, we find that second, third, fourth order moments allow 100% successful test set discrimination.

  18. Leaders of the profession and 'professional' leaders

    DEFF Research Database (Denmark)

    Bøje, Jakob Ditlev; Frederiksen, Lars Frode

    In this article, we will focus on the construction of professional identities. More specifically, the construction of school leaders’ professional identities – between what can be called leaders of the profession and ‘professional’ leaders. That is, the first among equals (the vanguard...... of the professional complex according to a Parsonian perspective) and a more distinct leader identity associated with business, management, and accountancy. We will attempt to go beyond some of the manifest expectations of school leaders, including expectations of their training programmes, and show how being...... a secondary habitus (as teacher)...

  19. Library Leaders: Attributes Compared to Corporate Leaders. (United States)

    Sheldon, Brooke E.


    Discusses attributes of library leaders that are based on a study of library leaders from academic, public, and school libraries; library school deans; and national library association executives. Four recurring characteristics are highlighted: intensity; communication and listening skills; consistency and the ability to develop trust; and…

  20. Infinite matrices, wavelet coefficients and frames

    Directory of Open Access Journals (Sweden)

    N. A. Sheikh


    Full Text Available We study the action of A on f∈L2(ℝ and on its wavelet coefficients, where A=(almjklmjk is a double infinite matrix. We find the frame condition for A-transform of f∈L2(ℝ whose wavelet series expansion is known.

  1. Application of wavelets in speech processing

    CERN Document Server

    Farouk, Mohamed Hesham


    This book provides a survey on wide-spread of employing wavelets analysis  in different applications of speech processing. The author examines development and research in different application of speech processing. The book also summarizes the state of the art research on wavelet in speech processing.

  2. Lead the way, Leader. (United States)

    Hanna, L A


    Effective leaders show objectivity, creativity, and knowledge. They develop personal leadership styles from existing models and use their strength to motivate staff, accomplish organizational goals, and develop future leaders.

  3. Parsimonious Wavelet Kernel Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Wang Qin


    Full Text Available In this study, a parsimonious scheme for wavelet kernel extreme learning machine (named PWKELM was introduced by combining wavelet theory and a parsimonious algorithm into kernel extreme learning machine (KELM. In the wavelet analysis, bases that were localized in time and frequency to represent various signals effectively were used. Wavelet kernel extreme learning machine (WELM maximized its capability to capture the essential features in “frequency-rich” signals. The proposed parsimonious algorithm also incorporated significant wavelet kernel functions via iteration in virtue of Householder matrix, thus producing a sparse solution that eased the computational burden and improved numerical stability. The experimental results achieved from the synthetic dataset and a gas furnace instance demonstrated that the proposed PWKELM is efficient and feasible in terms of improving generalization accuracy and real time performance.


    Maronge, Jacob M; Zhai, Yi; Wiens, Douglas P; Fang, Zhide


    In this article we investigate the optimal design problem for some wavelet regression models. Wavelets are very flexible in modeling complex relations, and optimal designs are appealing as a means of increasing the experimental precision. In contrast to the designs for the Haar wavelet regression model (Herzberg and Traves 1994; Oyet and Wiens 2000), the I-optimal designs we construct are different from the D-optimal designs. We also obtain c-optimal designs. Optimal (D- and I-) quadratic spline wavelet designs are constructed, both analytically and numerically. A case study shows that a significant saving of resources may be realized by employing an optimal design. We also construct model robust designs, to address response misspecification arising from fitting an incomplete set of wavelets.


    Bowerman, P. N.


    The Cumulative Poisson distribution program, CUMPOIS, is one of two programs which make calculations involving cumulative poisson distributions. Both programs, CUMPOIS (NPO-17714) and NEWTPOIS (NPO-17715), can be used independently of one another. CUMPOIS determines the approximate cumulative binomial distribution, evaluates the cumulative distribution function (cdf) for gamma distributions with integer shape parameters, and evaluates the cdf for chi-square distributions with even degrees of freedom. It can be used by statisticians and others concerned with probabilities of independent events occurring over specific units of time, area, or volume. CUMPOIS calculates the probability that n or less events (ie. cumulative) will occur within any unit when the expected number of events is given as lambda. Normally, this probability is calculated by a direct summation, from i=0 to n, of terms involving the exponential function, lambda, and inverse factorials. This approach, however, eventually fails due to underflow for sufficiently large values of n. Additionally, when the exponential term is moved outside of the summation for simplification purposes, there is a risk that the terms remaining within the summation, and the summation itself, will overflow for certain values of i and lambda. CUMPOIS eliminates these possibilities by multiplying an additional exponential factor into the summation terms and the partial sum whenever overflow/underflow situations threaten. The reciprocal of this term is then multiplied into the completed sum giving the cumulative probability. The CUMPOIS program is written in C. It was developed on an IBM AT with a numeric co-processor using Microsoft C 5.0. Because the source code is written using standard C structures and functions, it should compile correctly on most C compilers. The program format is interactive, accepting lambda and n as inputs. It has been implemented under DOS 3.2 and has a memory requirement of 26K. CUMPOIS was

  6. Wavelets and the Lifting Scheme

    DEFF Research Database (Denmark)

    la Cour-Harbo, Anders; Jensen, Arne

    The objective of this article is to give a concise introduction to the discrete wavelet transform (DWT) based on a technique called lifting. The lifting technique allows one to give an elementary, but rigorous, definition of the DWT, with modest requirements on the reader. A basic knowledge of li...... of linear algebra and signal processing will suffice. The lifting based definition is equivalent to the usual filer bank based definition of the DWT. The article does not discuss applications in any detail. The reader is referred to other articles in this collection....

  7. Wavelets and the lifting scheme

    DEFF Research Database (Denmark)

    la Cour-Harbo, Anders; Jensen, Arne


    The objective of this article is to give a concise introduction to the discrete wavelet transform (DWT) based on a technique called lifting. The lifting technique allows one to give an elementary, but rigorous, definition of the DWT, with modest requirements on the reader. A basic knowledge of li...... of linear algebra and signal processing will suffice. The lifting based definition is equivalent to the usual filer bank based definition of the DWT. The article does not discuss applications in any detail. The reader is referred to other articles in this collection....

  8. Wavelets and the lifting scheme

    DEFF Research Database (Denmark)

    la Cour-Harbo, Anders; Jensen, Arne


    The objective of this article is to give a concise introduction to the discrete wavelet transform (DWT) based on a technique called lifting. The lifting technique allows one to give an elementary, but rigorous, definition of the DWT, with modest requirements on the reader. A basic knowledge of li...... of linear algebra and signal processing will suffice. The lifting based definition is equivalent to the usual filer bank based definition of the DWT. The article does not discuss applications in any detail. The reader is referred to other articles in this collection....

  9. Complex Wavelet Based Modulation Analysis

    DEFF Research Database (Denmark)

    Luneau, Jean-Marc; Lebrun, Jérôme; Jensen, Søren Holdt


    Low-frequency modulation of sound carry important information for speech and music. The modulation spectrum i commonly obtained by spectral analysis of the sole temporal envelopes of the sub-bands out of a time-frequency analysis. Processing in this domain usually creates undesirable distortions...... polynomial trends. Moreover an analytic Hilbert-like transform is possible with complex wavelets implemented as an orthogonal filter bank. By working in an alternative transform domain coined as “Modulation Subbands”, this transform shows very promising denoising capabilities and suggests new approaches for joint...

  10. Seamless multiresolution isosurfaces using wavelets

    Energy Technology Data Exchange (ETDEWEB)

    Udeshi, T.; Hudson, R.; Papka, M. E.


    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.

  11. Wavelet analysis of multifractal functions (United States)

    Jaffard, Stephane


    Multifractal signals are characterized by a local Holder exponent that may change completely from point to point. We show that wavelet methods are an extremely efficient tool for determining the exact Holder exponent of a function, or at least, for getting some information about this Holder exponent, such as the Spectrum of Singularities. We construct functions that have a given Holder exponent in a deterministic setting and also in a probabilistic setting (we then obtain the Multifractional Brownian Motion); we also study the Multifractal Formalism for Functions and give some results about its validity.

  12. Leading Strategic Leader Teams (United States)


    develop teams which provide them capacity and diversity to make sound decisions.1 Strategic leader and top management teams exist throughout...looks at whether a leader should use a team to make a decision; it does not look at how to manage a team process to produce desired outcomes. Yet, the...choices on how to operate his/her team. Leaders of strategic leader teams must recognize and understand how they can manage the processes utilized

  13. Fundamentals for New Leaders (United States)


    hard drivers (similar to Indian leaders ) and have a much more “push-oriented” approach to change management .7 The executive editor of Business...perception of people about the organization and its leaders , directly attributed to the leadership and management style of the leaders , based on the skills...newborn leader or manager taking charge. Combined together, things like preparing properly, assessing correctly, and acting accordingly ensure the

  14. Electrocardiogram de-noising based on forward wavelet transform ...

    Indian Academy of Sciences (India)

    cation of the Forward Wavelet Transform Translation Invariant (FWT_TI) to each. Bionic Wavelet ... wavelet coefficients obtained from the application of the Bionic Wavelet Transform (BWT) to the noisy ECG signal. ...... Han J Y, Lee S K and Park H B 2009 Denoising ECG using Translation Invariant Multiwavelet. Int. J. Electr.

  15. The good leader. (United States)

    Bottles, K


    What are the traits of successful leaders and can they be applied to those of us in health care? Leaders must deal with conflict to get a group of people to move in the same direction. Successful leaders learn to have difficult conversations that increase understanding and morale and creatively deal with the inevitable interpersonal conflicts present in every organization made up of people. Another useful trait for a leader during uncertain and chaotic times is the ability to see things as they really are, rather than as we wish or believe them to be. Successful leaders are also usually optimists who level with their co-workers.

  16. Wavelet subspaces invariant under groups of translation operators

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    One can always construct a wavelet from an MRA (see, for instance, Ch. 2 in [5]), but not every wavelet can be obtained in this manner. The first example of a wavelet which cannot be obtained from an MRA was given by Journé. In [1] we characterized a large class of wavelets, which also includes Journé's wavelet, and ...

  17. Applications of a fast, continuous wavelet transform

    Energy Technology Data Exchange (ETDEWEB)

    Dress, W.B.


    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.

  18. Application of the cross wavelet transform and wavelet coherence to geophysical time series

    Directory of Open Access Journals (Sweden)

    A. Grinsted


    Full Text Available Many scientists have made use of the wavelet method in analyzing time series, often using popular free software. However, at present there are no similar easy to use wavelet packages for analyzing two time series together. We discuss the cross wavelet transform and wavelet coherence for examining relationships in time frequency space between two time series. We demonstrate how phase angle statistics can be used to gain confidence in causal relationships and test mechanistic models of physical relationships between the time series. As an example of typical data where such analyses have proven useful, we apply the methods to the Arctic Oscillation index and the Baltic maximum sea ice extent record. Monte Carlo methods are used to assess the statistical significance against red noise backgrounds. A software package has been developed that allows users to perform the cross wavelet transform and wavelet coherence (

  19. Cumulative risk, cumulative outcome: a 20-year longitudinal study.

    Directory of Open Access Journals (Sweden)

    Leslie Atkinson

    Full Text Available Cumulative risk (CR models provide some of the most robust findings in the developmental literature, predicting numerous and varied outcomes. Typically, however, these outcomes are predicted one at a time, across different samples, using concurrent designs, longitudinal designs of short duration, or retrospective designs. We predicted that a single CR index, applied within a single sample, would prospectively predict diverse outcomes, i.e., depression, intelligence, school dropout, arrest, smoking, and physical disease from childhood to adulthood. Further, we predicted that number of risk factors would predict number of adverse outcomes (cumulative outcome; CO. We also predicted that early CR (assessed at age 5/6 explains variance in CO above and beyond that explained by subsequent risk (assessed at ages 12/13 and 19/20. The sample consisted of 284 individuals, 48% of whom were diagnosed with a speech/language disorder. Cumulative risk, assessed at 5/6-, 12/13-, and 19/20-years-old, predicted aforementioned outcomes at age 25/26 in every instance. Furthermore, number of risk factors was positively associated with number of negative outcomes. Finally, early risk accounted for variance beyond that explained by later risk in the prediction of CO. We discuss these findings in terms of five criteria posed by these data, positing a "mediated net of adversity" model, suggesting that CR may increase some central integrative factor, simultaneously augmenting risk across cognitive, quality of life, psychiatric and physical health outcomes.

  20. Adapted wavelet analysis from theory to software

    CERN Document Server

    Wickerhauser, Mladen Victor


    This detail-oriented text is intended for engineers and applied mathematicians who must write computer programs to perform wavelet and related analysis on real data. It contains an overview of mathematical prerequisites and proceeds to describe hands-on programming techniques to implement special programs for signal analysis and other applications. From the table of contents: - Mathematical Preliminaries - Programming Techniques - The Discrete Fourier Transform - Local Trigonometric Transforms - Quadrature Filters - The Discrete Wavelet Transform - Wavelet Packets - The Best Basis Algorithm - Multidimensional Library Trees - Time-Frequency Analysis - Some Applications - Solutions to Some of the Exercises - List of Symbols - Quadrature Filter Coefficients

  1. Discretization of quaternionic continuous wavelet transforms (United States)

    Askari Hemmat, A.; Thirulogasanthar, K.; Krzyżak, A.


    A scheme to form a basis and a frame for a Hilbert space of quaternion valued square integrable function from a basis and a frame, respectively, of a Hilbert space of complex valued square integrable functions is introduced. Using the discretization techniques for 2D-continuous wavelet transform of the SIM(2) group, the quaternionic continuous wavelet transform, living in a complex valued Hilbert space of square integrable functions, of the quaternion wavelet group is discretized, and thereby, a discrete frame for quaternion valued Hilbert space of square integrable functions is obtained.

  2. Significance tests for the wavelet cross spectrum and wavelet linear coherence

    Directory of Open Access Journals (Sweden)

    Z. Ge


    Full Text Available This work attempts to develop significance tests for the wavelet cross spectrum and the wavelet linear coherence as a follow-up study on Ge (2007. Conventional approaches that are used by Torrence and Compo (1998 based on stationary background noise time series were used here in estimating the sampling distributions of the wavelet cross spectrum and the wavelet linear coherence. The sampling distributions are then used for establishing significance levels for these two wavelet-based quantities. In addition to these two wavelet quantities, properties of the phase angle of the wavelet cross spectrum of, or the phase difference between, two Gaussian white noise series are discussed. It is found that the tangent of the principal part of the phase angle approximately has a standard Cauchy distribution and the phase angle is uniformly distributed, which makes it impossible to establish significance levels for the phase angle. The simulated signals clearly show that, when there is no linear relation between the two analysed signals, the phase angle disperses into the entire range of [−π,π] with fairly high probabilities for values close to ±π to occur. Conversely, when linear relations are present, the phase angle of the wavelet cross spectrum settles around an associated value with considerably reduced fluctuations. When two signals are linearly coupled, their wavelet linear coherence will attain values close to one. The significance test of the wavelet linear coherence can therefore be used to complement the inspection of the phase angle of the wavelet cross spectrum. The developed significance tests are also applied to actual data sets, simultaneously recorded wind speed and wave elevation series measured from a NOAA buoy on Lake Michigan. Significance levels of the wavelet cross spectrum and the wavelet linear coherence between the winds and the waves reasonably separated meaningful peaks from those generated by randomness in the data set. As

  3. Significance tests for the wavelet cross spectrum and wavelet linear coherence

    Directory of Open Access Journals (Sweden)

    Z. Ge


    Full Text Available This work attempts to develop significance tests for the wavelet cross spectrum and the wavelet linear coherence as a follow-up study on Ge (2007. Conventional approaches that are used by Torrence and Compo (1998 based on stationary background noise time series were used here in estimating the sampling distributions of the wavelet cross spectrum and the wavelet linear coherence. The sampling distributions are then used for establishing significance levels for these two wavelet-based quantities. In addition to these two wavelet quantities, properties of the phase angle of the wavelet cross spectrum of, or the phase difference between, two Gaussian white noise series are discussed. It is found that the tangent of the principal part of the phase angle approximately has a standard Cauchy distribution and the phase angle is uniformly distributed, which makes it impossible to establish significance levels for the phase angle. The simulated signals clearly show that, when there is no linear relation between the two analysed signals, the phase angle disperses into the entire range of [−π,π] with fairly high probabilities for values close to ±π to occur. Conversely, when linear relations are present, the phase angle of the wavelet cross spectrum settles around an associated value with considerably reduced fluctuations. When two signals are linearly coupled, their wavelet linear coherence will attain values close to one. The significance test of the wavelet linear coherence can therefore be used to complement the inspection of the phase angle of the wavelet cross spectrum.

    The developed significance tests are also applied to actual data sets, simultaneously recorded wind speed and wave elevation series measured from a NOAA buoy on Lake Michigan. Significance levels of the wavelet cross spectrum and the wavelet linear coherence between the winds and the waves reasonably separated meaningful peaks from those generated by randomness in the

  4. Wavelet primal sketch representation using Marr wavelet pyramid and its reconstruction (United States)

    Van De Ville, Dimitri; Unser, Michael


    Based on the class of complex gradient-Laplace operators, we show the design of a non-separable two-dimensional wavelet basis from a single and analytically defined generator wavelet function. The wavelet decomposition is implemented by an efficient FFT-based filterbank. By allowing for slight redundancy, we obtain the Marr wavelet pyramid decomposition that features improved translation-invariance and steerability. The link with Marr's theory of early vision is due to the replication of the essential processing steps (Gaussian smoothing, Laplacian, orientation detection). Finally, we show how to find a compact multiscale primal sketch of the image, and how to reconstruct an image from it.

  5. Time-frequency wavelet analysis of the interrelationship between the global macro assets and the fear indexes (United States)

    Abid, Fathi; Kaffel, Bilel


    Understanding the interrelationships of the global macro assets is crucial for global macro investing. This paper investigates the local variance and the interconnection between the stock, gold, oil, Forex and the implied volatility markets in the time/frequency domains using the wavelet methodology, including the wavelet power spectrum, the wavelet squared coherence and phase difference, the wavelet multiple correlation and cross-correlation. The univariate analysis reveals that, in some crisis periods, underlying asset markets present the same pattern in terms of the wavelet power spectrum indicating high volatility for the medium scale, and that for the other market stress periods, volatility behaves differently. Moreover, unlike the underlying asset markets, the implied volatility markets are characterized by high power regions across the entire period, even in the absence of economic events. Bivariate results show a bidirectional relationship between the underlying assets and their corresponding implied volatility indexes, and a steady co-movement between the stock index and its corresponding fear index. Multiple correlation analysis indicates a strong correlation between markets at high scales with evidence of a nearly perfect integration for a period longer than a year. In addition, the hedging strategies based on the volatility index lead to an increase in portfolio correlation. On the other hand, the results from multiple cross-correlations reveal that the lead-lag effect starts from the medium scale and that the VIX (stock market volatility index) index is the potential leader or follower of the other markets.

  6. Electro-cumulation CNF project

    CERN Document Server

    Grishin, V G


    bound or free ion current within solid substances; non-plain symmetry; cumulation of the ion interaction. Experimental result: an Ice SuperPolarization. Cold nuclear fusion ? At . Keywords: ion, current, solid, symmetry, cumulation, cold nuclear fusion, polarization, depolarization, ionic conductor, superionic conductor, ice, crystal, strain, V-center, V-centre, doped crystal, interstitial impurity, intrinsic color center, high pressure technology, Bridgman, experiment, crowdion, dielectric, proton, layer, defect, lattice, dynamics, electromigration, mobility, muon catalysis, concentration, doping, dopant, conductivity, pycnonuclear reaction, permittivity, dielectric constant, point defects, interstitials, polarizability, imperfection, defect centers, glass, epitaxy, sodium hydroxide, metallic substrate, crystallization, point, tip, susceptibility, ferroelectric, ordering, force, correlation, collective, shift, distortion, coalescence, crowdions, electrolysis.

  7. Evolutionary neuroscience of cumulative culture. (United States)

    Stout, Dietrich; Hecht, Erin E


    Culture suffuses all aspects of human life. It shapes our minds and bodies and has provided a cumulative inheritance of knowledge, skills, institutions, and artifacts that allows us to truly stand on the shoulders of giants. No other species approaches the extent, diversity, and complexity of human culture, but we remain unsure how this came to be. The very uniqueness of human culture is both a puzzle and a problem. It is puzzling as to why more species have not adopted this manifestly beneficial strategy and problematic because the comparative methods of evolutionary biology are ill suited to explain unique events. Here, we develop a more particularistic and mechanistic evolutionary neuroscience approach to cumulative culture, taking into account experimental, developmental, comparative, and archaeological evidence. This approach reconciles currently competing accounts of the origins of human culture and develops the concept of a uniquely human technological niche rooted in a shared primate heritage of visuomotor coordination and dexterous manipulation.

  8. Applying wavelet entropy principle in fault classification

    Energy Technology Data Exchange (ETDEWEB)

    El Safty, S.; El-Zonkoly, A. [Arab Academy for Science and Technology, Miami, Alexandria, P.O.1029 (Egypt)


    The ability to detect and classify the type of fault plays a great role in the protection of power system. This procedure is required to be precise with no time consumption. In this paper detection of fault type has been implemented using wavelet analysis together with wavelet entropy principle. The simulation of power system is carried out using PSCAD/EMTDC. Different types of faults were studied obtaining various current waveforms. These current waveforms were decomposed using wavelet analysis into different approximation and details. The wavelet entropies of such decompositions are analyzed reaching a successful methodology for fault classification. The suggested approach is tested using different fault types and proven successful identification for the type of fault. (author)

  9. Image Registration Using Redundant Wavelet Transforms

    National Research Council Canada - National Science Library

    Brown, Richard


    .... In our research, we present a fundamentally new wavelet-based registration algorithm utilizing redundant transforms and a masking process to suppress the adverse effects of noise and improve processing efficiency...

  10. Wavelets theory and applications for manufacturing

    CERN Document Server

    Gao, Robert X


    With the aim of facilitating signal processing in manufacturing, this book presents a systematic description of the fundamentals on wavelet transform and the ways of applying it to the condition monitoring and health diagnosis of rotating machine components.

  11. Framelets and wavelets algorithms, analysis, and applications

    CERN Document Server

    Han, Bin


    Marking a distinct departure from the perspectives of frame theory and discrete transforms, this book provides a comprehensive mathematical and algorithmic introduction to wavelet theory. As such, it can be used as either a textbook or reference guide. As a textbook for graduate mathematics students and beginning researchers, it offers detailed information on the basic theory of framelets and wavelets, complemented by self-contained elementary proofs, illustrative examples/figures, and supplementary exercises. Further, as an advanced reference guide for experienced researchers and practitioners in mathematics, physics, and engineering, the book addresses in detail a wide range of basic and advanced topics (such as multiwavelets/multiframelets in Sobolev spaces and directional framelets) in wavelet theory, together with systematic mathematical analysis, concrete algorithms, and recent developments in and applications of framelets and wavelets. Lastly, the book can also be used to teach on or study selected spe...

  12. Coherent states, wavelets, and their generalizations

    CERN Document Server

    Ali, Syed Twareque; Gazeau, Jean-Pierre


    This second edition is fully updated, covering in particular new types of coherent states (the so-called Gazeau-Klauder coherent states, nonlinear coherent states, squeezed states, as used now routinely in quantum optics) and various generalizations of wavelets (wavelets on manifolds, curvelets, shearlets, etc.). In addition, it contains a new chapter on coherent state quantization and the related probabilistic aspects. As a survey of the theory of coherent states, wavelets, and some of their generalizations, it emphasizes mathematical principles, subsuming the theories of both wavelets and coherent states into a single analytic structure. The approach allows the user to take a classical-like view of quantum states in physics.   Starting from the standard theory of coherent states over Lie groups, the authors generalize the formalism by associating coherent states to group representations that are square integrable over a homogeneous space; a further step allows one to dispense with the group context altoget...

  13. Electric Equipment Diagnosis based on Wavelet Analysis

    Directory of Open Access Journals (Sweden)

    Stavitsky Sergey A.


    Full Text Available Due to electric equipment development and complication it is necessary to have a precise and intense diagnosis. Nowadays there are two basic ways of diagnosis: analog signal processing and digital signal processing. The latter is more preferable. The basic ways of digital signal processing (Fourier transform and Fast Fourier transform include one of the modern methods based on wavelet transform. This research is dedicated to analyzing characteristic features and advantages of wavelet transform. This article shows the ways of using wavelet analysis and the process of test signal converting. In order to carry out this analysis, computer software Mathcad was used and 2D wavelet spectrum for a complex function was created.

  14. Modelling spatial density using continuous wavelet transforms

    Indian Academy of Sciences (India)

    Space debris; wavelets; Mexican hat; Laplace distribution; random search; parameter estimation. ... Digital Mapping and Modelling Division, Advanced Data Processing Research Institute, Secunderabad 500 009, India; Department of Mathematics, Osmania University, Hyderabad 500 007, India; Applied Mathematics ...

  15. Wavelet based approach for facial expression recognition

    Directory of Open Access Journals (Sweden)

    Zaenal Abidin


    Full Text Available Facial expression recognition is one of the most active fields of research. Many facial expression recognition methods have been developed and implemented. Neural networks (NNs have capability to undertake such pattern recognition tasks. The key factor of the use of NN is based on its characteristics. It is capable in conducting learning and generalizing, non-linear mapping, and parallel computation. Backpropagation neural networks (BPNNs are the approach methods that mostly used. In this study, BPNNs were used as classifier to categorize facial expression images into seven-class of expressions which are anger, disgust, fear, happiness, sadness, neutral and surprise. For the purpose of feature extraction tasks, three discrete wavelet transforms were used to decompose images, namely Haar wavelet, Daubechies (4 wavelet and Coiflet (1 wavelet. To analyze the proposed method, a facial expression recognition system was built. The proposed method was tested on static images from JAFFE database.

  16. Finite-Resolution Effects in p -Leader Multifractal Analysis (United States)

    Leonarduzzi, Roberto; Wendt, Herwig; Abry, Patrice; Jaffard, Stephane; Melot, Clothilde


    Multifractal analysis has become a standard signal processing tool,for which a promising new formulation, the p-leader multifractal formalism, has recently been proposed. It relies on novel multiscale quantities, the p-leaders, defined as local l^p norms of sets of wavelet coefficients located at infinitely many fine scales. Computing such infinite sums from actual finite-resolution data requires truncations to the finest available scale, which results in biased p-leaders and thus in inaccurate estimates of multifractal properties. A systematic study of such finite-resolution effects leads to conjecture an explicit and universal closed-form correction that permits an accurate estimation of scaling exponents. This conjecture is formulated from the theoretical study of a particular class of models for multifractal processes, the wavelet-based cascades. The relevance and generality of the proposed conjecture is assessed by numerical simulations conducted over a large variety of multifractal processes. Finally, the relevance of the proposed corrected estimators is demonstrated on the analysis of heart rate variability data.

  17. Authenticating the Leader

    DEFF Research Database (Denmark)

    Garmann Johnsen, Christian


    In the wake of a series of corporate scandals, there has been a growing call for authentic leadership in order to ensure ethical conduct in contemporary organizations. Authentic leadership, however, depends upon the ability to draw a distinction between the authentic and inauthentic leader....... This paper uses Deleuze’s discussion of Platonism as a point of departure for critically scrutinizing the problem of authenticating the leader - drawing a distinction between authentic and inauthentic leaders. This will be done through a reading of Bill George’s book Authentic Leadership. Informed by Deleuze......’s inverted Platonism, the paper challenges the practice by which authentic leaders are distinguished from inauthentic leaders. In conclusion, the paper suggests that an adequate concept of authentic leadership should consider how ethics can occur when the authentic leader is able to critically reflect his...

  18. Applications of a fast continuous wavelet transform (United States)

    Dress, William B.


    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

  19. Subordinates as Threats to Leaders


    Glazer, Amihai; Segendorff, Björn


    A leader of an organization may view a subordinate as threatening or weakening the leader's position. The threat may increase with the subordinate's ability and reduce the rents the leader wins. In particular, a leader who trains his subordinate reduces the cost to the owner of a firm in replacing the leader, and so reduces the leader's bargaining power. The leader therefore provides inefficiently low training for the subordinate.

  20. Successful Transformational Radiology Leaders. (United States)

    Douget, Karen


    Transformational radiology leaders elevate subordinates, expand self-awareness, develop lasting relationships, strive to exceed expectations, and uphold the vision and goals of the organization. In order for radiology leaders to become more transformational in their leadership style there are four fundamental elements they must learn: idealized influence, individualized consideration, inspirational motivation, and intellectual stimulation. Leaders can utilize personality and self-assessments to learn more about themselves, identify areas of strengths and weaknesses, and learn to be more effective when leading employees.

  1. Revolutionizing Army Leader Development (United States)


    represents a tremendous gap in the Army leader development strategy and can easily be traced back to outdated personnel management models, systems and...St ra te gy R es ea rc h Pr oj ec t REVOLUTIONIZING ARMY LEADER DEVELOPMENT BY COLONEL SHAWN E. REED United States Army DISTRIBUTION...From - To) 4. TITLE AND SUBTITLE Revolutionizing Army Leader Development 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM

  2. The NFP Strategic Leader (United States)


    32 Parameters The NFP Strategic Leader R. CRAIG BULLIS Individual self-awareness is a strategic leader’s greatest asset,1 and the im-portance of...The article advances the case that effective strategic leader- ship requires behaviors aligned with the Intuitive, Feeling, and Perceiving ( NFP ...SUBTITLE The NFP Strategic Leader 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER



    Bratanov, Crina; Chirimbu, Sebastian


    Leadership is the ability to transform vision into reality, and the leader is the architect who manages to turn what was just a projection of the future vision of the organization in a tangible reality. A leader can be a manager, while the manager is always a leader. If management function is carrying out particular activities under formal authority, leadership is more than authority and power. Add leadership vision, daring, personal effort and amount of unique qualities, personal, boosting p...

  4. The wavelet response as a multiscale NDT method. (United States)

    Le Gonidec, Y; Conil, F; Gibert, D


    We analyze interfaces by using reflected waves in the framework of the wavelet transform. First, we introduce the wavelet transform as an efficient method to detect and characterize a discontinuity in the acoustical impedance profile of a material. Synthetic examples are shown for both an isolated reflector and multiscale clusters of nearby defects. In the second part of the paper we present the wavelet response method as a natural extension of the wavelet transform when the velocity profile to be analyzed can only be remotely probed by propagating wavelets through the medium (instead of being directly convolved as in the wavelet transform). The wavelet response is constituted by the reflections of the incident wavelets on the discontinuities and we show that both transforms are equivalent when multiple scattering is neglected. We end this paper by experimentally applying the wavelet response in an acoustic tank to characterize planar reflectors with finite thicknesses.

  5. Developing Global Transformational Leaders

    DEFF Research Database (Denmark)

    Ramsey, Jase R.; Rutti, Raina M.; Lorenz, Melanie P.


    Despite significant increases in training and development of global managers, little is known about the precursors of transformational leadership in Multilatinas. While prior cross-cultural literature suggests that being an autocratic leader is ideal in Multilatinas, using transformational...... of transformational leadership because they are better able to understand the differences of other cultures, and appropriately adjust their behavior....... leadership theory, we argue that global leaders of Multilatinas embrace a more humanistic approach to leadership because of the importance of relationships between leaders and their followers. Additionally, we argue that global leaders with high levels of cultural intelligence will have high levels...

  6. Adaptive strategies for cumulative cultural learning. (United States)

    Ehn, Micael; Laland, Kevin


    The demographic and ecological success of our species is frequently attributed to our capacity for cumulative culture. However, it is not yet known how humans combine social and asocial learning to generate effective strategies for learning in a cumulative cultural context. Here we explore how cumulative culture influences the relative merits of various pure and conditional learning strategies, including pure asocial and social learning, critical social learning, conditional social learning and individual refiner strategies. We replicate the Rogers' paradox in the cumulative setting. However, our analysis suggests that strategies that resolved Rogers' paradox in a non-cumulative setting may not necessarily evolve in a cumulative setting, thus different strategies will optimize cumulative and non-cumulative cultural learning. Copyright © 2012 Elsevier Ltd. All rights reserved.

  7. Evolutionary neuroscience of cumulative culture


    Stout, Dietrich; Hecht, Erin E.


    Culture suffuses all aspects of human life. It shapes our minds and bodies and has provided a cumulative inheritance of knowledge, skills, institutions, and artifacts that allows us to truly stand on the shoulders of giants. No other species approaches the extent, diversity, and complexity of human culture, but we remain unsure how this came to be. The very uniqueness of human culture is both a puzzle and a problem. It is puzzling as to why more species have not adopted this manifestly benefi...

  8. What Good Leaders Do. (United States)

    Cash, Jeanie


    According to California's National Distinguished Principal, good leaders celebrate creativity and capitalize on others' creativity while building schools on foundations of trust, commitment, and fun. Successful leaders are optimistic, generate trust, reward innovation, create a safety net for risk-taking behavior, delegate authority, and lead…

  9. How Leaders Really Emerge (United States)

    Guastello, Stephen J.


    Comments on the article by R. J. Hackman and R. Wageman (see record 2006-23492-007) which offered several research questions that should be productive for furthering leadership research. This comment summarizes some recent progress on one of those questions, "Not what are the traits of leaders, but how do leaders' personal attributes interact with…

  10. Leaders from Nursing's History. (United States)

    Fondiller, Shirley H.; And Others


    Looks at the lives and accomplishments of four leaders in professional nursing: (1) Loretta Ford, who championed the cause of nurse practitioners; (2) Mable Staupers, a pioneer in community health and nursing; (3) Janet Geister, a leader in private nursing; and (4) Isabel Stewart, who led the movement to standardize nursing education. (JOW)

  11. The Inspirational Leader (United States)

    Benigni, Mark D.; Hughes, Mark A


    Amid the focus on improved standardized test scores, differentiated instruction, value-added initiatives and improved teacher evaluation, one must not ignore an education leader's need to inspire and be inspired. But how do education leaders inspire their students and teachers during some of the most difficult economic times the nation has ever…

  12. Leader Training Conference Report. (United States)

    Michigan-Ohio Regional Educational Lab., Inc., Detroit.

    The purpose of this conference was to prepare key people in the field of education to function as inservice education leaders in their respective settings. It called for participants to learn what the MOREL inservice education program is and what it hopes to accomplish, to identify the role and functions of the inservice education leader, and to…

  13. Developing Successful Global Leaders (United States)

    Training, 2011


    Everyone seems to agree the world desperately needs strong leaders who can manage a global workforce and all the inherent challenges that go with it. That's a big part of the raison d'etre for global leadership development programs. But are today's organizations fully utilizing these programs to develop global leaders, and, if so, are they…

  14. Demands for School Leaders (United States)

    Bradley-Levine, Jill


    This article examines the ways that graduate courses in teacher leadership influenced the ways that teachers described the nature of leadership and their role as educational leaders. Using Foster's (1989) four demands for school leaders as a theoretical framework, participants' perceptions are examined to determine how teachers synthesized their…

  15. A paradox of cumulative culture. (United States)

    Kobayashi, Yutaka; Wakano, Joe Yuichiro; Ohtsuki, Hisashi


    Culture can grow cumulatively if socially learnt behaviors are improved by individual learning before being passed on to the next generation. Previous authors showed that this kind of learning strategy is unlikely to be evolutionarily stable in the presence of a trade-off between learning and reproduction. This is because culture is a public good that is freely exploited by any member of the population in their model (cultural social dilemma). In this paper, we investigate the effect of vertical transmission (transmission from parents to offspring), which decreases the publicness of culture, on the evolution of cumulative culture in both infinite and finite population models. In the infinite population model, we confirm that culture accumulates largely as long as transmission is purely vertical. It turns out, however, that introduction of even slight oblique transmission drastically reduces the equilibrium level of culture. Even more surprisingly, if the population size is finite, culture hardly accumulates even under purely vertical transmission. This occurs because stochastic extinction due to random genetic drift prevents a learning strategy from accumulating enough culture. Overall, our theoretical results suggest that introducing vertical transmission alone does not really help solve the cultural social dilemma problem. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Image wavelet decomposition and applications (United States)

    Treil, N.; Mallat, S.; Bajcsy, R.


    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.

  17. Multiresolution wavelet-ANN model for significant wave height forecasting.

    Digital Repository Service at National Institute of Oceanography (India)

    Deka, P.C.; Mandal, S.; Prahlada, R.

    Hybrid wavelet artificial neural network (WLNN) has been applied in the present study to forecast significant wave heights (Hs). Here Discrete Wavelet Transformation is used to preprocess the time series data (Hs) prior to Artificial Neural Network...

  18. Wavelet transforms as solutions of partial differential equations

    Energy Technology Data Exchange (ETDEWEB)

    Zweig, G.


    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.

  19. Wavelet-frame-based microcalcification detection (United States)

    Chang, Charles C.; Wu, Hsien-Hsun S.; Liu, Jyh-Charn S.; Chui, Charles K.


    As the leading cause of death for adult women under 54 years of age in the United States, breast cancer accounts for 29% of all cancers in women. Early diagnosis of breast cancer is the most effective approach to reduce death rate. The rapid climbing of the health care cost further reiterates the importance of cost-effective, accurate screening tools for breast cancer. This paper proposes a wavelet frame based computer algorithm for screening of microcalcifications on digitized mammographical imagery. Despite its simplicity, the discrete wavelet transform (DWT) of compactly supported wavelets has been effectively used for detection of various types of signals. However, the shifting variant property of DWT makes it very unstable for detection of minute microcalcifications. Although increasing the sampling rate will improve the detection probability, this approach will drastically increase the size of mammographical images. The wavelet frame transform can be easily derived from the DWT algorithm by eliminating its down sampling step. The subtle difference between DWT and WF in down sampling is shown to be critical to the accuracy of microcalcifications detection. Without any down sampling, local image information at different scales is preserved. By joint thresholding of wavelet coefficients at different scales, one can accurately pin point suspected microcalcifications. A simple partitioning technique enables the detection algorithm to process image blocks independently. Four different partitioning techniques have been compared, and the method of repeating the end value on each partition boundary has the least significant impact on the detection accuracy.

  20. Nuclear data compression and reconstruction via discrete wavelet transform

    Energy Technology Data Exchange (ETDEWEB)

    Park, Young Ryong; Cho, Nam Zin [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)


    Discrete Wavelet Transforms (DWTs) are recent mathematics, and begin to be used in various fields. The wavelet transform can be used to compress the signal and image due to its inherent properties. We applied the wavelet transform compression and reconstruction to the neutron cross section data. Numerical tests illustrate that the signal compression using wavelet is very effective to reduce the data saving spaces. 7 refs., 4 figs., 3 tabs. (Author)


    Directory of Open Access Journals (Sweden)

    Crina Bratanov


    Full Text Available Leadership is the ability to transform vision into reality, and the leader is the architect who manages to turn what was just a projection of the future vision of the organization in a tangible reality. A leader can be a manager, while the manager is always a leader. If management function is carrying out particular activities under formal authority, leadership is more than authority and power. Add leadership vision, daring, personal effort and amount of unique qualities, personal, boosting process management.

  2. Fast generation of computer-generated holograms using wavelet shrinkage. (United States)

    Shimobaba, Tomoyoshi; Ito, Tomoyoshi


    Computer-generated holograms (CGHs) are generated by superimposing complex amplitudes emitted from a number of object points. However, this superposition process remains very time-consuming even when using the latest computers. We propose a fast calculation algorithm for CGHs that uses a wavelet shrinkage method, eliminating small wavelet coefficient values to express approximated complex amplitudes using only a few representative wavelet coefficients.

  3. A simple output voltage control scheme for single phase wavelet ...

    African Journals Online (AJOL)

    DR OKE

    Wavelet based techniques have been extensively used in various power engineering applications. Recently, wavelet has also been proposed to generate switching signal for single-phase pulse-width-modulated (PWM) dc-ac inverter. The main advantage of the wavelet modulated (WM) scheme is that a single synthesis ...

  4. Spatial Verification Using Wavelet Transforms: A Review

    CERN Document Server

    Weniger, Michael; Friederichs, Petra


    Due to the emergence of new high resolution numerical weather prediction (NWP) models and the availability of new or more reliable remote sensing data, the importance of efficient spatial verification techniques is growing. Wavelet transforms offer an effective framework to decompose spatial data into separate (and possibly orthogonal) scales and directions. Most wavelet based spatial verification techniques have been developed or refined in the last decade and concentrate on assessing forecast performance (i.e. forecast skill or forecast error) on distinct physical scales. Particularly during the last five years, a significant growth in meteorological applications could be observed. However, a comparison with other scientific fields such as feature detection, image fusion, texture analysis, or facial and biometric recognition, shows that there is still a considerable, currently unused potential to derive useful diagnostic information. In order to tab the full potential of wavelet analysis, we revise the stat...

  5. Applications of adaptive wavelets for speech (United States)

    Kadambe, Shubha L.; Srinivasan, Pramila


    Our objective is to demonstrate the applicability of adaptive wavelets for speech applications. In particular, we discuss two applications, namely, classification of unvoiced sounds and speaker identification. First, a method to classify unvoiced sounds using adaptive wavelets, which would help in developing a unified algorithm to classify phonemes (speech sounds), is described. Next, the applicability of adaptive wavelets to identify speakers using very short speech data (one pitch period) is exhibited. The described text-independent phoneme based speaker identification algorithm identifies a speaker by first modeling phonemes and then by clustering all the phonemes belonging to the same speaker into one class. For both applications, we use feed-forward neural network architecture. We demonstrate the performance of both unvoiced sounds classifier and speaker identification algorithms by using representative real speech examples.

  6. Improvement of electrocardiogram by empirical wavelet transform (United States)

    Chanchang, Vikanda; Kumchaiseemak, Nakorn; Sutthiopad, Malee; Luengviriya, Chaiya


    Electrocardiogram (ECG) is a crucial tool in the detection of cardiac arrhythmia. It is also often used in a routine physical exam, especially, for elderly people. This graphical representation of electrical activity of heart is obtained by a measurement of voltage at the skin; therefore, the signal is always contaminated by noise from various sources. For a proper interpretation, the quality of the ECG should be improved by a noise reduction. In this article, we present a study of a noise filtration in the ECG by using an empirical wavelet transform (EWT). Unlike the traditional wavelet method, EWT is adaptive since the frequency spectrum of the ECG is taken into account in the construction of the wavelet basis. We show that the signal-to-noise ratio increases after the noise filtration for different noise artefacts.

  7. Leader self-definition and leader self-serving behavior

    NARCIS (Netherlands)

    Rus, Diana; van Knippenberg, Daan; Wisse, Barbara

    The present research investigated the relationship between leader self-definition processes and leader self-serving behaviors. We hypothesized that self-definition as a leader interacts with social reference information (descriptive and injunctive) in predicting leader self-serving actions Six

  8. Leader as communicator. (United States)

    Haynor, Patricia M


    This article examines common communication factors that have an impact on leader effectiveness (language, listening, mode of delivery, and feedback) and the role of the organization, organizational culture, and group dynamics in the development of the leader as a communicator. Communication, like any skill, is a learned behavior that is honed over time. Communication is a two-way process with stimulus-response shaping future behavior. But, it is even more complex when used in an organizational setting because there are multilevel communications, multiple message, senders and receivers, and competing agendas. Leaders in today's complex health care organizations must be skilled communicators to earn trust and respect. Once trust and respect have been earned, others are willing to listen to the leader's vision and to help make it a reality because, done well, it demonstrates expertise, critical thinking, achievement, and mentoring abilities.

  9. Persuasion: A Leader's Edge

    National Research Council Canada - National Science Library

    McGuire, Mark


    .... Persuasive argument is a vital aspect of strategic leadership. Any leader faced with the inherent complexities of leading his or her organization through transformational change must be capable of persuading...

  10. Becoming a Facilitative Leader. (United States)

    Schwarz, Roger


    Leaders often contribute to the consequences they complain about by using an approach termed unilateral control. The Facilitative Leadership Approach, with its core values of valid information, free and informed choice, internal commitment, and compassion, can counteract this phenomenon. (JOW)

  11. Authenticating the Leader

    DEFF Research Database (Denmark)

    Johnsen, Christian Garmann

    of authentication within discourse of authentic leadership. If authentic leadership is to make any sense, it is necessary to be able to distinguish the authentic from the inauthentic leader – in other words, it is necessary to authenticate the leader. This paper uses Gilles Deleuze’s reading of Plato as the point......As authentic leadership, with its dictum of being true to the self, has become increasingly influential among practitioners and mainstream leadership scholars, critical writers have drawn attention to the negative consequences of this development. Yet, few scholars have investigated the problem...... of departure for discussing the problem of authentication – separating the authentic leader form the inauthentic one – in the leadership guru Bill George’s model of authentic leadership. By doing so, the paper offers a way of conceptualizing the problem of authenticating leaders, as well as challenging...

  12. Leading Strategic Leader Teams

    National Research Council Canada - National Science Library

    Burleson, Willard M


    .... Although only 1 to 2 percent of the Army's senior leaders will attain a command position of strategic leadership, they are assisted by others, not only by teams specifically designed and structured...

  13. How Successful Are Wavelets in Detecting Jumps?

    Directory of Open Access Journals (Sweden)

    Burak Alparslan Eroğlu


    Full Text Available We evaluate the performances of wavelet jump detection tests by using simulated high-frequency data, in which jumps and some other non-standard features are present. Wavelet-based jump detection tests have a clear advantage over the alternatives, as they are capable of stating the exact timing and number of jumps. The results indicate that, in addition to those advantages, these detection tests also preserve desirable power and size properties even in non-standard data environments, whereas their alternatives fail to sustain their desirable properties beyond standard data features.

  14. A wavelet "time-shift-detail" decomposition


    Levan, N.; Kubrusly, Carlos S.


    \\begin{abstract}We show that, with respect to an orthonormal wavelet $\\psi(.)\\in \\L^{2}(\\RR),$ any $f(.)\\in\\L^{2}(\\RR)$ is, on the one hand, the sum of its ``layers of details'' over all time-shifts, and on the other hand, the sum of its layers of details over all scales. The latter is well known and is a consequence of a wandering subspace decomposition of $\\L^{2}(\\RR)$ which, in turn, resulted from a wavelet Multiresolution Analysis (MRA). The former has not been discussed before. We show ...

  15. Modified wavelet transform for unbiased frequency representation (United States)

    Telfer, Brian A.; Szu, Harold H.


    A new wavelet transform normalization procedure is proposed for the construction of a weighted bank of matched filters. The standard normalization results in higher input frequencies producing larger wavelet transform magnitudes if the amplitude of the frequencies is held constant, while the new normalization produces equal responses. This is illustrated with an example of Gibb's overshooting phenomenon, and connections to neural networks are discussed. Another example is presented which illustrates a cocktail party effect. A derivation is given to show that an inverse transform still exists when using the new normalization.

  16. Wavelet methods in mathematical analysis and engineering

    CERN Document Server

    Damlamian, Alain


    This book gives a comprehensive overview of both the fundamentals of wavelet analysis and related tools, and of the most active recent developments towards applications. It offers a stateoftheart in several active areas of research where wavelet ideas, or more generally multiresolution ideas have proved particularly effective. The main applications covered are in the numerical analysis of PDEs, and signal and image processing. Recently introduced techniques such as Empirical Mode Decomposition (EMD) and new trends in the recovery of missing data, such as compressed sensing, are also presented.

  17. Filtering, Coding, and Compression with Malvar Wavelets (United States)


    2-10 2.4. The Malvar Wavelet Represented in Polyphase Form ...................... 2-11 3.1. (a) Real Part and (b) Imaginary Part of the Complex... Sleeping Pill", Using (a) 1 Point Overlap and (b) 50% (128 Point) Overlap ...... ............... 5-8 5.8. Reconstruction of the Same Sentence (From Sample...For example, if M=2 then 2-10 LICOMP_ U-Cc LCC-N SX,8) Y() Figure 2.4. The Malvar Wavelet Represented in Polyphase Form the signal would be broken

  18. New Algorithm For Calculating Wavelet Transforms

    Directory of Open Access Journals (Sweden)

    Piotr Lipinski


    Full Text Available In this article we introduce a new algorithm for computing Discrete Wavelet Transforms (DWT. The algorithm aims at reducing the number of multiplications, required to compute a DWT. The algorithm is general and can be used to compute a variety of wavelet transform (Daubechies and CDF. Here we focus on CDF 9/7 filters, which are used in JPEG2000 compression standard. We show that the algorithm outperforms convolution-based and lifting-based algorithms in terms of number of multiplications.

  19. Multiresolution signal decomposition transforms, subbands, and wavelets

    CERN Document Server

    Akansu, Ali N; Haddad, Paul R


    The uniqueness of this book is that it covers such important aspects of modern signal processing as block transforms from subband filter banks and wavelet transforms from a common unifying standpoint, thus demonstrating the commonality among these decomposition techniques. In addition, it covers such ""hot"" areas as signal compression and coding, including particular decomposition techniques and tables listing coefficients of subband and wavelet filters and other important properties.The field of this book (Electrical Engineering/Computer Science) is currently booming, which is, of course

  20. Narcissism and Toxic Leaders (United States)


    Examples of unconscious behaviors could include brushing one’s teeth , getting dressed, or even driving a car—an individual can day-dream about a meeting...enhance its positive attributes and raise awareness of its negative ones. By definition, narcissistic leaders have “an inflated sense of self- importance ...for leaders, especially in the military, there are aspects of narcissism that are appropriate (if controlled and self-regulated) and important for

  1. Leader Identity, Individual Differences, and Leader Self-Development (United States)


    SAMS, Ph.D. Research Program Manager Director Training and Leader Development Division Technical Review by Sena Garven, U.S. Army...Technical Report 1310 Leader Identity, Individual Differences, and Leader Self-development Melinda Key-Roberts, Stanley Halpin, and...TITLE AND SUBTITLE Leader Identity, Individual Differences, and Leader Self- development 5a.CONTRACT OR GRANT NUMBER 5b. PROGRAM ELEMENT NUMBER

  2. Developing Future Strategic Logistics Leaders (United States)


    A partnership between senior logistics leaders , PME developers, and personnel managers is essential to constructing and maintaining strategic...Commander in the area of leader development, while overseeing the implementation and daily management of logistic leader development. The current structure... managers is essential to constructing and maintaining strategic leader development frameworks. The risk of not making adjustments to logistics Professional

  3. Parallel object-oriented, denoising system using wavelet multiresolution analysis (United States)

    Kamath, Chandrika; Baldwin, Chuck H.; Fodor, Imola K.; Tang, Nu A.


    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.

  4. A New Texture Synthesis Algorithm Based on Wavelet Packet Tree

    Directory of Open Access Journals (Sweden)

    Hsi Chin Hsin


    Full Text Available This paper presents an efficient texture synthesis based on wavelet packet tree (TSWPT. It has the advantage of using a multiresolution representation with a greater diversity of bases functions for the nonlinear time series applications such as fractal images. The input image is decomposed into wavelet packet coefficients, which are rearranged and organized to form hierarchical trees called wavelet packet trees. A 2-step matching, that is, coarse matching based on low-frequency wavelet packet coefficients followed by fine matching based on middle-high-frequency wavelet packet coefficients, is proposed for texture synthesis. Experimental results show that the TSWPT algorithm is preferable, especially in terms of computation time.

  5. Cumulative trauma disorders: A review. (United States)

    Iqbal, Zaheen A; Alghadir, Ahmad H


    Cumulative trauma disorder (CTD) is a term for various injuries of the musculoskeletal and nervous systems that are caused by repetitive tasks, forceful exertions, vibrations, mechanical compression or sustained postures. Although there are many studies citing incidence of CTDs, there are fewer articles about its etiology, pathology and management. The aim of our study was to discuss the etiology, pathogenesis, prevention and management of CTDs. A literature search was performed using various electronic databases. The search was limited to articles in English language pertaining to randomized clinical trials, cohort studies and systematic reviews of CTDs. A total of 180 papers were identified to be relevant published since 1959. Out of these, 125 papers reported about its incidence and 50 about its conservative treatment. Workplace environment, same task repeatability and little variability, decreased time for rest, increase in expectations are major factors for developing CTDs. Prevention of its etiology and early diagnosis can be the best to decrease its incidence and severity. For effective management of CTDs, its treatment should be divided into Primordial, Primary, Secondary and Tertiary prevention.

  6. Cumulative human impacts on marine predators

    DEFF Research Database (Denmark)

    Maxwell, Sara M; Hazen, Elliott L; Bograd, Steven J


    Sanctuaries. High variation in underlying species and cumulative impact distributions means that neither alone is sufficient for effective spatial management. Instead, comprehensive management approaches accounting for both cumulative human impacts and trade-offs among multiple stressors must be applied......Stressors associated with human activities interact in complex ways to affect marine ecosystems, yet we lack spatially explicit assessments of cumulative impacts on ecologically and economically key components such as marine predators. Here we develop a metric of cumulative utilization and impact...... in planning the use of marine resources....

  7. On optimisation of wavelet algorithms for non-perfect wavelet compression of digital medical images

    CERN Document Server

    Ricke, J


    Aim: Optimisation of medical image compression. Evaluation of wavelet-filters for wavelet-compression. Results: Application of filters with different complexity results in significant variations in the quality of image reconstruction after compression specifically in low frequency information. Filters of high complexity proved to be advantageous despite of heterogenous results during visual analysis. For high frequency details, complexity of filters did not prove to be of significant impact on image after reconstruction.

  8. Quaternion Wavelet Analysis and Application in Image Denoising

    Directory of Open Access Journals (Sweden)

    Ming Yin


    Full Text Available The quaternion wavelet transform is a new multiscale analysis tool. Firstly, this paper studies the standard orthogonal basis of scale space and wavelet space of quaternion wavelet transform in spatial L2(R2, proves and presents quaternion wavelet’s scale basis function and wavelet basis function concepts in spatial scale space L2(R2;H, and studies quaternion wavelet transform structure. Finally, the quaternion wavelet transform is applied to image denoising, and generalized Gauss distribution is used to model QWT coefficients’ magnitude distribution, under the Bayesian theory framework, to recover the original coefficients from the noisy wavelet coefficients, and so as to achieve the aim of denoising. Experimental results show that our method is not only better than many of the current denoising methods in the peak signal to noise ratio (PSNR, but also obtained better visual effect.

  9. Application of wavelet transform to seismic data; Wavelet henkan no jishin tansa eno tekiyo

    Energy Technology Data Exchange (ETDEWEB)

    Nakagami, K.; Murayama, R.; Matsuoka, T. [Japan National Oil Corp., Tokyo (Japan)


    Introduced herein is the use of the wavelet transform in the field of seismic exploration. Among applications so far made, there are signal filtering, break point detection, data compression, and the solution of finite differential equations in the wavelet domain. In the field of data compression in particular, some examples of practical application have been introduced already. In seismic exploration, it is expected that the wavelet transform will separate signals and noises in data in a way different from the Fourier transform. The continuous wavelet transform displays time change in frequency easy to read, but is not suitable for the analysis and processing large quantities of data. On the other hand, the discrete wavelet transform, being an orthogonal transform, can handle large quantities of data. As compared with the conventional Fourier transform that handles only the frequency domain, the wavelet transform handles the time domain as well as the frequency domain, and therefore is more convenient in handling unsteady signals. 9 ref., 8 figs.

  10. Monthly Energy Consumption Forecasting Using Wavelet Analysis ...

    African Journals Online (AJOL)

    Monthly energy forecasts help heavy consumers of electric power to prepare adequate budget to pay their electricity bills and also draw the attention of management and stakeholders to electricity consumption levels so that energy efficiency measures are put in place to reduce cost. In this paper, a wavelet transform and ...

  11. Wavelet based multicarrier code division multiple access ...

    African Journals Online (AJOL)

    This paper presents the study on Wavelet transform based Multicarrier Code Division Multiple Access (MC-CDMA) system for a downlink wireless channel. The performance of the system is studied for Additive White Gaussian Noise Channel (AWGN) and slowly varying multipath channels. The bit error rate (BER) versus ...

  12. Wavelets: Applications to Image Compression-II

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 10; Issue 3. Wavelets: Applications to Image Compression – II. Sachin P Nanavati ... National PARAM Supercomputing Facility, Centre for Development of Advanced Computing (C-DAC). Pune University Campus, Ganesh Khind, Pune 411 007, India.

  13. Conductance calculations with a wavelet basis set

    DEFF Research Database (Denmark)

    Thygesen, Kristian Sommer; Bollinger, Mikkel; Jacobsen, Karsten Wedel


    . The linear-response conductance is calculated from the Green's function which is represented in terms of a system-independent basis set containing wavelets with compact support. This allows us to rigorously separate the central region from the contacts and to test for convergence in a systematic way...

  14. Wavelet Transform-A New Mathematical Microscope

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 9; Issue 3. Wavelet Transform - A New Mathematical Microscope. Sachin P Nanavati Prasanta K Panigrahi. General Article Volume 9 Issue 3 March 2004 pp 50-64. Fulltext. Click here to view fulltext PDF. Permanent link:

  15. Wave Forecasting Using Neuro Wavelet Technique

    Directory of Open Access Journals (Sweden)

    Pradnya Dixit


    Full Text Available In the present work a hybrid Neuro-Wavelet Technique is used for forecasting waves up to 6 hr, 12 hr, 18 hr and 24 hr in advance using hourly measured significant wave heights at an NDBC station 41004 near the east coast of USA. The NW Technique is employed by combining two methods, Discrete Wavelet Transform and Artificial Neural Networks. The hourly data of previously measured significant wave heights spanning over 2 years from 2010 and 2011 is used to calibrate and test the models. The discrete wavelet transform of NWT analyzes frequency of signal with respect to time at different scales. It decomposes time series into low (approximate and high (detail frequency components. The decomposition of approximate can be carried out up to desired multiple levels in order to provide more detail and approximate components which provides relatively smooth varying amplitude series. The neural network is trained with decorrelated approximate and detail wavelet coefficients. The outputs of networks during testing are reconstructed back using inverse DWT. The results were judged by drawing the wave plots, scatter plots and other error measures. The developed models show reasonable accuracy in prediction of significant wave heights from 6 to 24 hours. To compare the results traditional ANN models were also developed at the same location using the same data and for same time interval.

  16. monthly energy consumption forecasting using wavelet analysis

    African Journals Online (AJOL)


    Wavelet Transform (CWT) and Discrete Wave- let Transform (DWT) (Lee et al., 2000). CWT is mainly used for theoretical research, but. DWT is more popular in the field ... man brain processes information. ANNs are composed of simple elements or neurons oper- ating in parallel with connections or weights between them.

  17. Adaptive wavelet algorithms for solving operator equations

    NARCIS (Netherlands)

    Gantumur, T.


    This thesis treats various aspects of adaptive wavelet algorithms for solving operator equations. For a separable Hilbert space H, a linear functional f in H', and a boundedly invertible linear operator A:H->H', we consider the problem of finding u from H satisfying Au=f. Typically A is given by a

  18. Leaders produce leaders and managers produce followers (United States)

    Khoshhal, Khalid I.; Guraya, Salman Y.


    Objectives: To elaborate the desired qualities, traits, and styles of physician’s leadership with a deep insight into the recommended measures to inculcate leadership skills in physicians. Methods: The databases of MEDLINE, EMBASE, CINAHL, and the Cochrane Library were searched for the full-text English-language articles published during the period 2000-2015. Further search, including manual search of grey literature, was conducted from the bibliographic list of all included articles. Medical Subject Headings (MeSH) keywords “Leadership” AND “Leadership traits” AND “Leadership styles” AND “Physicians’ leadership” AND “Tomorrow’s doctors” were used for the literature search. This search followed a step-wise approach defined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The retrieved bibliographic list was analyzed and non-relevant material such as abstracts, conference proceedings, letters to editor, and short communications were excluded. Finally, 21 articles were selected for this review. Results: The literature search showed a number of leadership courses and formal training programs that can transform doctors to physician leaders. Leaders can inculcate confidence by integrating diverse views and listening; supporting skillful conversations through dialogue and helping others assess their influence and expertise. In addition to their clinical competence, physician leaders need to acquire the industry knowledge (clinical processes, health-care trends, budget), problem-solving skills, and emotional intelligence. Conclusion: This review emphasizes the need for embedding formal leadership courses in the medical curricula for fostering tomorrow doctors’ leadership and organizational skills. The in-house and off-campus training programs and workshops should be arranged for grooming the potential candidates for effective leadership. PMID:27652355

  19. Application of Shannon Wavelet Entropy and Shannon Wavelet Packet Entropy in Analysis of Power System Transient Signals

    Directory of Open Access Journals (Sweden)

    Jikai Chen


    Full Text Available In a power system, the analysis of transient signals is the theoretical basis of fault diagnosis and transient protection theory. Shannon wavelet entropy (SWE and Shannon wavelet packet entropy (SWPE are powerful mathematics tools for transient signal analysis. Combined with the recent achievements regarding SWE and SWPE, their applications are summarized in feature extraction of transient signals and transient fault recognition. For wavelet aliasing at adjacent scale of wavelet decomposition, the impact of wavelet aliasing is analyzed for feature extraction accuracy of SWE and SWPE, and their differences are compared. Meanwhile, the analyses mentioned are verified by partial discharge (PD feature extraction of power cable. Finally, some new ideas and further researches are proposed in the wavelet entropy mechanism, operation speed and how to overcome wavelet aliasing.

  20. Classification of mammographic microcalcifications using wavelets (United States)

    Chitre, Yateen S.; Dhawan, Atam P.; Moskowitz, Myron; Sarwal, Alok; Bonasso, Christine; Narayan, Suresh B.


    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.

  1. Cumulative Exams in the Introductory Psychology Course (United States)

    Lawrence, Natalie K.


    Many teachers require their students to take cumulative exams, but there are surprisingly few studies that examine the benefits of such exams. The purpose of this study was to determine whether introductory psychology students who take cumulative exams throughout the semester would have better long-term retention than students who take a…

  2. Cumulative Student Loan Debt in Minnesota, 2015 (United States)

    Williams-Wyche, Shaun


    To better understand student debt in Minnesota, the Minnesota Office of Higher Education (the Office) gathers information on cumulative student loan debt from Minnesota degree-granting institutions. These data detail the number of students with loans by institution, the cumulative student loan debt incurred at that institution, and the percentage…

  3. Today's Students, Tomorrow's Leaders (United States)

    Reese, Susan


    According to Warren Bennis, professor at the University of Southern California's Marshall School of Business and a recognized authority on organizational development, leadership and change, becoming a leader is synonymous with becoming oneself. It is precisely that simple, and it is also that difficult. In career and technical student…

  4. Salesperson, Catalyst, Manager, Leader. (United States)

    Worth, Michael J.; Asp, James W., II


    This article examines four roles of the college or university development officer: salesperson (when direct solicitation is seen as the officer's primary role); catalyst (or sales manager, adviser, expert, facilitator); manager (stressing the importance of the overall office functioning); and leader (who exerts a leadership role in the…

  5. The Change Leader. (United States)

    Fullan, Michael


    Argues that concept of principal as instructional leader is too limited to sustain school improvement. Advocates that principals serve as change agents who transform the teaching and learning culture of the school. Describes how principals can bring about sustainable change in the school culture. (PKP)

  6. Leader skills research


    Davidová, Renata


    The paper focuses on the basic characteristics of leading and approaches to leading people. The aim is to find out, which skills predestinate a person to become a leader. To detect, if there are any differences between leading people and university students in their leading skills and abilities. To stress the importance of developing these skills.

  7. World-Class Leaders (United States)

    Weinstein, Margery


    Future leaders' creativity and problem-solving skills have been honed in leadership courses, but that doesn't mean they are ready to use those skills to further a company's place in the world. With emerging markets in Asia, South America, and other areas of the world, a workforce needs to have an understanding of and interest in cultures beyond…

  8. Empowering Leaders & Learners (United States)

    Umphrey, Jan


    Trevor Greene, the 2013 MetLife/NASSP National High School Principal of the Year, empowers staff members and students to be the best teachers and learners they can be and provides the community resources to support them. In this article, Greene, principal of Toppenish High School in Washington, shares his biggest motivator as a school leader and…

  9. Senior Leader Career Management: Implications for Senior Leaders and Organizations (United States)

    Larkin, Jean


    This qualitative research study across three large consumer products organizations explored career management of senior leaders to gain an understanding of what is important to senior leaders in their careers and what strategies they are using for career management. It also investigated senior leaders' expectations of organizations for career…


    Directory of Open Access Journals (Sweden)

    Akimov Pavel Alekseevich


    Full Text Available Part 1 of this paper represents an introduction into the multi-resolution wavelet analysis. The wavelet-based analysis is an exciting new problem-solving tool used by mathematicians, scientists and engineers. In the paper, the authors try to present the fundamental elements of the multi-resolution wavelet analysis in a way that is accessible to an engineer, a scientist and an applied mathematician both as a theoretical approach and as a potential practical method of solving problems (particularly, boundary problems of structural mechanics and mathematical physics. The main goal of the contemporary wavelet research is to generate a set of basic functions (or general expansion functions and transformations that will provide an informative, efficient and useful description of a function or a signal. Another central idea is that of multi-resolution whereby decomposition of a signal represents the resolution of the detail. The multi-resolution decomposition seems to separate components of a signal in a way that is superior to most other methods of analysis, processing or compression. Due to the ability of the discrete wavelet transformation technique to decompose a signal at different independent scaling levels and to do it in a very flexible way, wavelets can be named "the microscopes of mathematics". Indeed, the use of the wavelet analysis and wavelet transformations requires a new point of view and a new method of interpreting representations.

  11. Research on ghost imaging method based on wavelet transform (United States)

    Li, Mengying; He, Ruiqing; Chen, Qian; Gu, Guohua; Zhang, Wenwen


    We present an algorithm of extracting the wavelet coefficients of object based on ghost imaging (GI) system. Through modification of the projected random patterns by using a series of templates, wavelet transform GI (WTGI) can directly measure the high frequency components of wavelet coefficients without needing the original image. In this study, we theoretically and experimentally perform the high frequency components of wavelet coefficients detection with an arrow and a letter A based on GI and WTGI. Comparing with the traditional method, the use of the algorithm proposed in this paper can significantly improve the quality of the image of wavelet coefficients in both cases. The special advantages of GI will make the wavelet coefficient detection based on WTGI very valuable in real applications.

  12. Wavelet-Based MPNLMS Adaptive Algorithm for Network Echo Cancellation

    Directory of Open Access Journals (Sweden)

    Hongyang Deng


    Full Text Available The μ-law proportionate normalized least mean square (MPNLMS algorithm has been proposed recently to solve the slow convergence problem of the proportionate normalized least mean square (PNLMS algorithm after its initial fast converging period. But for the color input, it may become slow in the case of the big eigenvalue spread of the input signal's autocorrelation matrix. In this paper, we use the wavelet transform to whiten the input signal. Due to the good time-frequency localization property of the wavelet transform, a sparse impulse response in the time domain is also sparse in the wavelet domain. By applying the MPNLMS technique in the wavelet domain, fast convergence for the color input is observed. Furthermore, we show that some nonsparse impulse responses may become sparse in the wavelet domain. This motivates the usage of the wavelet-based MPNLMS algorithm. Advantages of this approach are documented.

  13. Wavelet-Based MPNLMS Adaptive Algorithm for Network Echo Cancellation

    Directory of Open Access Journals (Sweden)

    Doroslovački Miloš


    Full Text Available The μ-law proportionate normalized least mean square (MPNLMS algorithm has been proposed recently to solve the slow convergence problem of the proportionate normalized least mean square (PNLMS algorithm after its initial fast converging period. But for the color input, it may become slow in the case of the big eigenvalue spread of the input signal's autocorrelation matrix. In this paper, we use the wavelet transform to whiten the input signal. Due to the good time-frequency localization property of the wavelet transform, a sparse impulse response in the time domain is also sparse in the wavelet domain. By applying the MPNLMS technique in the wavelet domain, fast convergence for the color input is observed. Furthermore, we show that some nonsparse impulse responses may become sparse in the wavelet domain. This motivates the usage of the wavelet-based MPNLMS algorithm. Advantages of this approach are documented.

  14. FPGA Implementations of Bireciprocal Lattice Wave Discrete Wavelet Filter Banks

    Directory of Open Access Journals (Sweden)

    Jassim M. Abdul-Jabbar


    Full Text Available In this paper, a special type of IIR filter banks; that is the bireciprocal lattice wave digital filter (BLWDF bank, is presented to simulate scaling and wavelet functions of six-level wavelet transform. 1st order all-pass sections are utilized for the realization of such filter banks in wave lattice structures. The resulting structures are a bireciprocal lattice wave discrete wavelet filter banks (BLW-DWFBs. Implementation of these BLW-DWFBs are accomplished on Spartan-3E FPGA kit. Implementation complexity and operating frequency characteristics of such discrete wavelet 5th order filter bank is proved to be comparable to the corresponding characteristics of the lifting scheme implementation of Bio. 5/3 wavelet filter bank. On the other hand, such IIR filter banks possess superior band discriminations and perfect roll-off frequency characteristics when compared to their Bio. 5/3 wavelet FIR counterparts.

  15. From cardinal spline wavelet bases to highly coherent dictionaries

    Energy Technology Data Exchange (ETDEWEB)

    Andrle, Miroslav; Rebollo-Neira, Laura [Aston University, Birmingham B4 7ET (United Kingdom)


    Wavelet families arise by scaling and translations of a prototype function, called the mother wavelet. The construction of wavelet bases for cardinal spline spaces is generally carried out within the multi-resolution analysis scheme. Thus, the usual way of increasing the dimension of the multi-resolution subspaces is by augmenting the scaling factor. We show here that, when working on a compact interval, the identical effect can be achieved without changing the wavelet scale but reducing the translation parameter. By such a procedure we generate a redundant frame, called a dictionary, spanning the same spaces as a wavelet basis but with wavelets of broader support. We characterize the correlation of the dictionary elements by measuring their 'coherence' and produce examples illustrating the relevance of highly coherent dictionaries to problems of sparse signal representation. (fast track communication)

  16. Strategic Military Leaders - Leading Tomorrow

    National Research Council Canada - National Science Library

    Kit, Ng W


    .... Four key leadership competencies stand out. We need strategic leaders who are good at doing the right things and doing things right leaders who have the mental agility to choose the correct goals to achieve, the social intelligence to inspire...

  17. Detecting Impulses in Mechanical Signals by Wavelets

    Directory of Open Access Journals (Sweden)

    Yang W-X


    Full Text Available The presence of periodical or nonperiodical impulses in vibration signals often indicates the occurrence of machine faults. This knowledge is applied to the fault diagnosis of such machines as engines, gearboxes, rolling element bearings, and so on. The development of an effective impulse detection technique is necessary and significant for evaluating the working condition of these machines, diagnosing their malfunctions, and keeping them running normally over prolong periods. With the aid of wavelet transforms, a wavelet-based envelope analysis method is proposed. In order to suppress any undesired information and highlight the features of interest, an improved soft threshold method has been designed so that the inspected signal is analyzed in a more exact way. Furthermore, an impulse detection technique is developed based on the aforementioned methods. The effectiveness of the proposed technique on the extraction of impulsive features of mechanical signals has been proved by both simulated and practical experiments.

  18. Wavelets and their applications past and future (United States)

    Coifman, Ronald R.


    As this is a conference on mathematical tools for defense, I would like to dedicate this talk to the memory of Louis Auslander, who through his insights and visionary leadership, brought powerful new mathematics into DARPA, he has provided the main impetus to the development and insertion of wavelet based processing in defense. My goal here is to describe the evolution of a stream of ideas in Harmonic Analysis, ideas which in the past have been mostly applied for the analysis and extraction of information from physical data, and which now are increasingly applied to organize and extract information and knowledge from any set of digital documents, from text to music to questionnaires. This form of signal processing on digital data, is part of the future of wavelet analysis.

  19. Combined wavelets-DCT image compression (United States)

    Ansari, Ahmad C.; Gertner, Izidor; Zeevi, Yehoshua Y.


    The mappings from multidimension to one dimension, or the inverse mappings, are theoretically described by space filling curves, i.e., Peano curves or Hilbert curves. The Peano Scan is an application of the Peano curve to the scanning of images, and it is used for analyzing, clustering, or compressing images, and for limiting the number of the colors used in an image. In this paper an efficient method for visual data compression is presented, combining generalized Peano Scan, wavelet decomposition, and adaptive subband coding technique. The Peano Scan is incorporated with the encoding scheme in order to cluster highly correlated pixels. Using wavelet decomposition, an adaptive subband coding technique is developed to encode each subband separately with an optimum algorithm. Discrete Cosine Transform (DCT) is applied on the low spatial frequency subband, and high spatial frequency subbands are encoded using Run Length encoding technique.

  20. Microbinary element for optical wavelet transform (United States)

    Huang, Gaogui; Feng, Wenyi; Yan, Yingbai; Jin, Guofan


    In order to simplify an opto-electronic hybrid system for texture segmentation based on the multi-channel filtering framework in the human visual theory, a micro-binary optical element (BOE) is designed and fabricated. The BOE has the functions of splitting, filtering and imaging simultaneously. The focal length of the BOE is 150mm and the diameter is 4mm. It contains sixteen Gabor wavelet filters with scales decreased by 2 orders and with our orientations separated every 45 degree, which can be used to perform a nearly complete decomposition with wavelet transform. The relief surface structure with minimum feature scale of 1.5micrometers is fabricated by using the photolithography and ion etching technique. In this paper, the functions of the BOE and the simulation of the filtering are described in detail, the experimental results and improvement of the element are given.

  1. ECG signal denoising via empirical wavelet transform. (United States)

    Singh, Omkar; Sunkaria, Ramesh Kumar


    This paper presents new methods for baseline wander correction and powerline interference reduction in electrocardiogram (ECG) signals using empirical wavelet transform (EWT). During data acquisition of ECG signal, various noise sources such as powerline interference, baseline wander and muscle artifacts contaminate the information bearing ECG signal. For better analysis and interpretation, the ECG signal must be free of noise. In the present work, a new approach is used to filter baseline wander and power line interference from the ECG signal. The technique utilized is the empirical wavelet transform, which is a new method used to compute the building modes of a given signal. Its performance as a filter is compared to the standard linear filters and empirical mode decomposition.The results show that EWT delivers a better performance.

  2. Transformer Protection Using the Wavelet Transform




    This paper introduces a novel approach for power transformer protection algorithm. Power system signals such as current and voltage have traditionally been analysed by the Fast Fourier Transform. This paper aims to prove that the Wavelet Transform is a reliable and computationally efficient tool for distinguishing between the inrush currents and fault currents. The simulated results presented clearly show that the proposed technique for power transformer protection facilitates the a...

  3. Wavelet Denoising within the Lifting Scheme Framework

    Directory of Open Access Journals (Sweden)

    M. P. Paskaš


    Full Text Available In this paper, we consider an example of the lifting scheme and present the results of the simple lifting scheme implementation using lazy transform. The paper is tutorial-oriented. The results are obtained by testing several common test signals for the signal denoising problem and using different threshold values. The lifting scheme represents an effective and flexible tool that can be used for introducing signal dependence into the problem by improving the wavelet properties.

  4. Digital Image Watermarking Algorithm Based on Wavelet Packet


    Geetha, A.; B.Vijayakumari; C.Nagavani; T.Pandiselvi


    In this paper, a method for Digital Image Watermarking based on the modification of certain subband of the wavelet packet decomposition was presented. A key is used for wavelet bases selection, watermark generation and selection of blocks for embedding the watermark bits. To efficiently embed the watermark within the images and provide the robustness for the watermark detection under attacks, watermark is embedded by quantizing the mean of the wavelet coefficient block. A method for exploitin...

  5. A Wavelet-based Algorithm for Vehicle Flow Information Extraction


    Ling-ling Li; Li-duan Liang; Lei Shi; Zhi Qiao


    This paper proposed an improved algorithm applied in video intelligent traffic control system for vehicle detection. The accuracy of original algorithm, which is based on the comparision of contrast and luminance distortion of present image with background, reduces greatly under bad weather because of false detection caused by noises in captured images. In this paper we chose Daubechies wavelet as mother wavelet to add a 2-dimension wavelet process before the algorithm, just after the image i...

  6. An introduction to random vibrations, spectral & wavelet analysis

    CERN Document Server

    Newland, D E


    One of the first engineering books to cover wavelet analysis, this classic text describes and illustrates basic theory, with a detailed explanation of the workings of discrete wavelet transforms. Computer algorithms are explained and supported by examples and a set of problems, and an appendix lists ten computer programs for calculating and displaying wavelet transforms.Starting with an introduction to probability distributions and averages, the text examines joint probability distributions, ensemble averages, and correlation; Fourier analysis; spectral density and excitation response relation

  7. On transforms between Gabor frames and wavelet frames

    DEFF Research Database (Denmark)

    Christensen, Ole; Goh, Say Song


    We describe a procedure that enables us to construct dual pairs of wavelet frames from certain dual pairs of Gabor frames. Applying the construction to Gabor frames generated by appropriate exponential Bsplines gives wavelet frames generated by functions whose Fourier transforms are compactly...... supported splines with geometrically distributed knot sequences. There is also a reverse transform, which yields pairs of dual Gabor frames when applied to certain wavelet frames....

  8. Hermitian Mindlin Plate Wavelet Finite Element Method for Load Identification


    Xiaofeng Xue; Xuefeng Chen; Xingwu Zhang; Baijie Qiao; Jia Geng


    A new Hermitian Mindlin plate wavelet element is proposed. The two-dimensional Hermitian cubic spline interpolation wavelet is substituted into finite element functions to construct frequency response function (FRF). It uses a system’s FRF and response spectrums to calculate load spectrums and then derives loads in the time domain via the inverse fast Fourier transform. By simulating different excitation cases, Hermitian cubic spline wavelets on the interval (HCSWI) finite elements are used t...

  9. Denoising solar radiation data using coiflet wavelets

    Energy Technology Data Exchange (ETDEWEB)

    Karim, Samsul Ariffin Abdul, E-mail:; Janier, Josefina B., E-mail:; Muthuvalu, Mohana Sundaram, E-mail: [Department of Fundamental and Applied Sciences, Faculty of Sciences and Information Technology, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak Darul Ridzuan (Malaysia); Hasan, Mohammad Khatim, E-mail: [Jabatan Komputeran Industri, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor (Malaysia); Sulaiman, Jumat, E-mail: [Program Matematik dengan Ekonomi, Universiti Malaysia Sabah, Beg Berkunci 2073, 88999 Kota Kinabalu, Sabah (Malaysia); Ismail, Mohd Tahir [School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM Minden, Penang (Malaysia)


    Signal denoising and smoothing plays an important role in processing the given signal either from experiment or data collection through observations. Data collection usually was mixed between true data and some error or noise. This noise might be coming from the apparatus to measure or collect the data or human error in handling the data. Normally before the data is use for further processing purposes, the unwanted noise need to be filtered out. One of the efficient methods that can be used to filter the data is wavelet transform. Due to the fact that the received solar radiation data fluctuates according to time, there exist few unwanted oscillation namely noise and it must be filtered out before the data is used for developing mathematical model. In order to apply denoising using wavelet transform (WT), the thresholding values need to be calculated. In this paper the new thresholding approach is proposed. The coiflet2 wavelet with variation diminishing 4 is utilized for our purpose. From numerical results it can be seen clearly that, the new thresholding approach give better results as compare with existing approach namely global thresholding value.

  10. Wavelet and statistical analysis for melanoma classification (United States)

    Nimunkar, Amit; Dhawan, Atam P.; Relue, Patricia A.; Patwardhan, Sachin V.


    The present work focuses on spatial/frequency analysis of epiluminesence images of dysplastic nevus and melanoma. A three-level wavelet decomposition was performed on skin-lesion images to obtain coefficients in the wavelet domain. A total of 34 features were obtained by computing ratios of the mean, variance, energy and entropy of the wavelet coefficients along with the mean and standard deviation of image intensity. An unpaired t-test for a normal distribution based features and the Wilcoxon rank-sum test for non-normal distribution based features were performed for selecting statistically correlated features. For our data set, the statistical analysis of features reduced the feature set from 34 to 5 features. For classification, the discriminant functions were computed in the feature space using the Mahanalobis distance. ROC curves were generated and evaluated for false positive fraction from 0.1 to 0.4. Most of the discrimination functions provided a true positive rate for melanoma of 93% with a false positive rate up to 21%.

  11. Detection of geomagnetic jerks using wavelet analysis (United States)

    Alexandrescu, Mioara; Gibert, Dominique; Hulot, Gauthier; Le MouëL, Jean-Louis; Saracco, Ginette


    Wavelet analysis is applied to detect and characterize singular events, or singularities, or jerks, in the time series made of the last century monthly mean values of the east component of the geomagnetic field from European observatories. After choosing a well-adapted wavelet function, the analysis is first performed on synthetic series including an "internal", or "main", signal made of smooth variation intervals separated by singular events with different "regularities", a white noise and an "external" signal made of the sum of a few harmonics of a long-period variation (11 years). The signatures of the main, noise, and harmonic signals are studied and compared, and the conditions in which the singular events can be clearly isolated in the composite signal are elucidated. Then we apply the method systematically to the real geomagnetic series (monthly means of Y from European observatories) and show that five arid only five remarkable events are found in 1901, 1913, 1925, 1969, and 1978. The characteristics of these singularities (in particular, homogeneity of some derived functions of the wavelet transform over a large range of timescales) demonstrate that these events have a single source (of course, internal). Also the events are more singular than was previously supposed (their "regularity" is closer to 1.5 than to 2., indicating that noninteger powers of time should be used in representing the time series between the jerks).

  12. Structural Pounding Detection by Using Wavelet Scalogram

    Directory of Open Access Journals (Sweden)

    Shutao Xing


    Full Text Available Structural pounding can cause considerable damage and even lead to collapse of structures. Most research focuses on modeling, parameter investigation, and mitigation approaches. With the development of structural health monitoring, the on-line detection of pounding becomes possible. The detection of pounding can provide useful information of potential damage of structures. This paper proposed using wavelet scalograms of dynamic response to detect pounding and examined the feasibility of this method. Numerical investigations were performed on a pounding system that consisted of a damped single-degree-of-freedom (SDOF structure and a rigid barrier. Hertz contact model was used to simulate pounding behavior. The responses and pounding forces of the system under harmonic and earthquake excitations were numerically solved. The wavelet scalograms of acceleration responses were used to identify poundings. It was found that the scalograms can indicate the occurrence of pounding and occurrence time very well. The severity of the poundings was also approximately estimated. Experimental studies were carried out, in which shake table tests were conducted on a bridge model that underwent pounding between its different components during ground motion excitation. The wavelet scalograms of the bridge responses indicated pounding occurrence quite well. Hence the conclusions from the numerical studies were verified experimentally.

  13. Pedestrian detection based on redundant wavelet transform (United States)

    Huang, Lin; Ji, Liping; Hu, Ping; Yang, Tiejun


    Intelligent video surveillance is to analysis video or image sequences captured by a fixed or mobile surveillance camera, including moving object detection, segmentation and recognition. By using it, we can be notified immediately in an abnormal situation. Pedestrian detection plays an important role in an intelligent video surveillance system, and it is also a key technology in the field of intelligent vehicle. So pedestrian detection has very vital significance in traffic management optimization, security early warn and abnormal behavior detection. Generally, pedestrian detection can be summarized as: first to estimate moving areas; then to extract features of region of interest; finally to classify using a classifier. Redundant wavelet transform (RWT) overcomes the deficiency of shift variant of discrete wavelet transform, and it has better performance in motion estimation when compared to discrete wavelet transform. Addressing the problem of the detection of multi-pedestrian with different speed, we present an algorithm of pedestrian detection based on motion estimation using RWT, combining histogram of oriented gradients (HOG) and support vector machine (SVM). Firstly, three intensities of movement (IoM) are estimated using RWT and the corresponding areas are segmented. According to the different IoM, a region proposal (RP) is generated. Then, the features of a RP is extracted using HOG. Finally, the features are fed into a SVM trained by pedestrian databases and the final detection results are gained. Experiments show that the proposed algorithm can detect pedestrians accurately and efficiently.

  14. Effectiveness of Wavelet Denoising on Electroencephalogram Signals

    Directory of Open Access Journals (Sweden)

    Md. Mamun


    Full Text Available Analyzing Electroencephalogram (EEG signal is a challenge due to the various artifacts used by Electromyogram, eye blink and Electrooculogram. The present de-noising techniques that are based on the frequency selective filtering suffers from a substantial loss of the EEG data. Noise removal using wavelet has the characteristic of preserving signal uniqueness even if noise is going to be minimized. To remove noise from EEG signal, this research employed discrete wavelet transform. Root mean square difference has been used to find the usefulness of the noise elimination. In this research, four different discrete wavelet functions have been used to remove noise from the Electroencephalogram signal gotten from two different types of patients (healthy and epileptic to show the effectiveness of DWT on EEG noise removal. The result shows that the WF orthogonal meyer is the best one for noise elimination from the EEG signal of epileptic subjects and the WF Daubechies 8 (db8 is the best one for noise elimination from the EEG signal on healthy subjects.

  15. Effectiveness of Wavelet Denoising on Electroencephalogram Signals

    Directory of Open Access Journals (Sweden)

    Md. Mamun


    Full Text Available Analyzing Electroencephalogram (EEG signal is a challenge due to the various artifacts used by Electromyogram,eye blink and Electrooculogram. The present de-noising techniques that are based on the frequency selective filteringsuffers from a substantial loss of the EEG data. Noise removal using wavelet has the characteristic of preservingsignal uniqueness even if noise is going to be minimized. To remove noise from EEG signal, this research employeddiscrete wavelet transform. Root mean square difference has been used to find the usefulness of the noiseelimination. In this research, four different discrete wavelet functions have been used to remove noise from theElectroencephalogram signal gotten from two different types of patients (healthy and epileptic to show theeffectiveness of DWT on EEG noise removal. The result shows that the WF orthogonal meyer is the best one fornoise elimination from the EEG signal of epileptic subjects and the WF Daubechies 8 (db8 is the best one for noiseelimination from the EEG signal on healthy subjects.

  16. Wavelets in Recognition of Bird Sounds

    Directory of Open Access Journals (Sweden)

    Juha T. Tanttu


    Full Text Available This paper presents a novel method to recognize inharmonic and transient bird sounds efficiently. The recognition algorithm consists of feature extraction using wavelet decomposition and recognition using either supervised or unsupervised classifier. The proposed method was tested on sounds of eight bird species of which five species have inharmonic sounds and three reference species have harmonic sounds. Inharmonic sounds are not well matched to the conventional spectral analysis methods, because the spectral domain does not include any visible trajectories that computer can track and identify. Thus, the wavelet analysis was selected due to its ability to preserve both frequency and temporal information, and its ability to analyze signals which contain discontinuities and sharp spikes. The shift invariant feature vectors calculated from the wavelet coefficients were used as inputs of two neural networks: the unsupervised self-organizing map (SOM and the supervised multilayer perceptron (MLP. The results were encouraging: the SOM network recognized 78% and the MLP network 96% of the test sounds correctly.

  17. Leaders and Leadership in Academe. (United States)

    Vroom, Victor H.


    Four contingency theories of leadership are explored and contrasted. Predictions of leader types and leader behaviors that would follow from each are counterposed. External functions of the leader and interactions with organizational members who are not subordinates are discussed. (Author/MLW)

  18. Can Teachers Really Be Leaders? (United States)

    Lieberman, Ann


    This is a wonderfully provocative question that might be answered simply: Yes, teachers can be leaders! Much more complicated and interesting, though, are the specifics of how teachers become leaders and the different ways teachers lead. Before considering how teachers become leaders, there is a need to understand the context within which teachers…

  19. Morphology-based wavelet features and multiple mother wavelet strategy for spike classification in EEG signals. (United States)

    Zhou, Jing; Schalkoff, Robert J; Dean, Brian C; Halford, Jonathan J


    New wavelet-derived features and strategies that can improve autonomous EEG classifier performance are presented. Various feature sets based on the morphological structure of wavelet subband coefficients are derived and evaluated. The performance of these new feature sets is superior to Guler's classic features in both sensitivity and specificity. In addition, the use of (scalp electrode) spatial information is also shown to improve EEG classification. Finally, a new strategy based upon concurrent use of several mother wavelets is shown to result in increased sensitivity and specificity. Various attempts at reducing feature vector dimension are shown. A non-parametric method, k-NNR, is implemented for classification and 10-fold cross-validation is used for assessment.

  20. Oil and gas program: cumulative effects

    National Research Council Canada - National Science Library

    Van Horn, W; Melancon, A; Sun, J


    The Outer Continental Shelf Lands Act (OCSLA) requires the Secretary of the Department of the Interior to submit an annual report to Congress assessing the cumulative environmental effects of mineral leasing and operations under the OCSLA...


    National Aeronautics and Space Administration — This data set consists of the Diviner Lunar Radiometer Experiment Global Cumulative Products also known as GCPs. The DLRE is a surface pushbroom mapper that measures...

  2. [Wavelet entropy analysis of spontaneous EEG signals in Alzheimer's disease]. (United States)

    Zhang, Meiyun; Zhang, Benshu; Chen, Ying


    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 (Pentropy 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 (Pentropy of EEG and the MMSE score were significantly correlated (r= 0. 601-0. 799, Pentropy 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.

  3. Wavelet-based moment invariants for pattern recognition (United States)

    Chen, Guangyi; Xie, Wenfang


    Moment invariants have received a lot of attention as features for identification and inspection of two-dimensional shapes. In this paper, two sets of novel moments are proposed by using the auto-correlation of wavelet functions and the dual-tree complex wavelet functions. It is well known that the wavelet transform lacks the property of shift invariance. A little shift in the input signal will cause very different output wavelet coefficients. The autocorrelation of wavelet functions and the dual-tree complex wavelet functions, on the other hand, are shift-invariant, which is very important in pattern recognition. Rotation invariance is the major concern in this paper, while translation invariance and scale invariance can be achieved by standard normalization techniques. The Gaussian white noise is added to the noise-free images and the noise levels vary with different signal-to-noise ratios. Experimental results conducted in this paper show that the proposed wavelet-based moments outperform Zernike's moments and the Fourier-wavelet descriptor for pattern recognition under different rotation angles and different noise levels. It can be seen that the proposed wavelet-based moments can do an excellent job even when the noise levels are very high.

  4. EEG Signal Decomposition and Improved Spectral Analysis Using Wavelet Transform

    National Research Council Canada - National Science Library

    Bhatti, Muhammad


    EEG (Electroencephalograph), as a noninvasive testing method, plays a key role in the diagnosing diseases, and is useful for both physiological research and medical applications. Wavelet transform (WT...

  5. Polynomial Representations for a Wavelet Model of Interest Rates

    Directory of Open Access Journals (Sweden)

    Dennis G. Llemit


    Full Text Available In this paper, we approximate a non – polynomial function which promises to be an essential tool in interest rates forecasting in the Philippines. We provide two numerical schemes in order to generate polynomial functions that approximate a new wavelet which is a modification of Morlet and Mexican Hat wavelets. The first is the Polynomial Least Squares method which approximates the underlying wavelet according to desired numerical errors. The second is the Chebyshev Polynomial approximation which generates the required function through a sequence of recursive and orthogonal polynomial functions. We seek to determine the lowest order polynomial representations of this wavelet corresponding to a set of error thresholds.

  6. Wavelet coherence model for diagnosis of Alzheimer disease. (United States)

    Sankari, Ziad; Adeli, Hojjat; Adeli, Anahita


    This article presents a wavelet coherence investigation of electroencephalograph (EEG) readings acquired from patients with Alzheimer disease (AD)  and healthy controls. Pairwise electrode wavelet coherence is calculated over each frequency band (delta, theta, alpha, and beta). For comparing the synchronization fraction of 2 EEG signals, a wavelet coherence fraction is proposed which is defined as the fraction of the signal time during which the wavelet coherence value is above a certain threshold. A one-way analysis of variance test shows a set of statistically significant differences in wavelet coherence between AD and controls. The wavelet coherence method is effective for studying cortical connectivity at a high temporal resolution. Compared with other conventional AD coherence studies, this study takes into account the time-frequency changes in coherence of EEG signals and thus provides more correlational details. A set of statistically significant differences was found in the wavelet coherence among AD and controls. In particular, temporocentral regions show a significant decrease in wavelet coherence in AD in the delta band, and the parietal and central regions show significant declines in cortical connectivity with most of their neighbors in the theta and alpha bands. This research shows that wavelet coherence can be used as a powerful tool to differentiate between healthy elderly individuals and probable AD patients.

  7. Discrete Wavelet Transform-Partial Least Squares Versus Derivative ...

    African Journals Online (AJOL)

    Discrete Wavelet Transform-Partial Least Squares Versus Derivative Ratio Spectrophotometry for Simultaneous Determination of Chlorpheniramine Maleate and Dexamethasone in the Presence of Parabens in Pharmaceutical Dosage Form.

  8. Human cumulative culture : a comparative perspective.


    Dean, L.; Vale, G.L.; Laland, K. N.; Flynn, E.G.; Kendal, R. L.


    Many animals exhibit social learning and behavioural traditions, but human culture exhibits unparalleled complexity and diversity, and is unambiguously cumulative in character. These similarities and differences have spawned a debate over whether animal traditions and human culture are reliant on homologous or analogous psychological processes. Human cumulative culture combines high-fidelity transmission of cultural knowledge with beneficial modifications to generate a ‘ratcheting’ in technol...

  9. The Effect of Cumulative Tests on the Final Exam (United States)

    Beagley, Jonathan E.; Capaldi, Mindy


    Mathematics teachers often give cumulative final exams, but little research has been done on the effects that cumulative exams given throughout the semester have on student grades and content knowledge. This study went beyond a cumulative final exam, and investigated the benefits of cumulative versus non-cumulative semester exams on students'…

  10. Cumulative cultural evolution: the role of teaching. (United States)

    Castro, Laureano; Toro, Miguel A


    In humans, cultural transmission occurs usually by cumulative inheritance, generating complex adaptive behavioral features. Cumulative culture requires key psychological processes (fundamentally imitation and teaching) that are absent or impoverished in non-human primates. In this paper we analyze the role that teaching has played in human cumulative cultural evolution. We assume that a system of cumulative culture generates increasingly adaptive behaviors, that are also more complex and difficult to imitate. Our thesis is that, as cultural traits become more complex, cumulative cultural transmission requires teaching to ensure accurate transmission from one generation to the next. In an increasingly complex cultural environment, we consider that individuals commit errors in imitation. We develop a model of cumulative cultural evolution in a changing environment and show that these errors hamper the process of cultural accumulation. We also show that a system of teaching between parents and offspring that increases the fidelity of imitation unblocks the accumulation and becomes adaptive whenever the gain in fitness compensates the cost of teaching. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Human cumulative culture: a comparative perspective. (United States)

    Dean, Lewis G; Vale, Gill L; Laland, Kevin N; Flynn, Emma; Kendal, Rachel L


    Many animals exhibit social learning and behavioural traditions, but human culture exhibits unparalleled complexity and diversity, and is unambiguously cumulative in character. These similarities and differences have spawned a debate over whether animal traditions and human culture are reliant on homologous or analogous psychological processes. Human cumulative culture combines high-fidelity transmission of cultural knowledge with beneficial modifications to generate a 'ratcheting' in technological complexity, leading to the development of traits far more complex than one individual could invent alone. Claims have been made for cumulative culture in several species of animals, including chimpanzees, orangutans and New Caledonian crows, but these remain contentious. Whilst initial work on the topic of cumulative culture was largely theoretical, employing mathematical methods developed by population biologists, in recent years researchers from a wide range of disciplines, including psychology, biology, economics, biological anthropology, linguistics and archaeology, have turned their attention to the experimental investigation of cumulative culture. We review this literature, highlighting advances made in understanding the underlying processes of cumulative culture and emphasising areas of agreement and disagreement amongst investigators in separate fields. © 2013 The Authors. Biological Reviews © 2013 Cambridge Philosophical Society.

  12. Antecedents of Leader Utilization of Staff Input in Decision-Making Teams. (United States)



    The purpose of this experiment was to explore the possibility that the inconsistent findings of Brehmer and Hagafors (1986, Organizational Behavior and Human Decision Processes, 38, 181-195), Sniezek and Buckley (1995, Organizational Behavior and Human Decision Processes, 62, 159-174), and leader-member exchange research regarding leaders' propensity to differentially and accurately weight staff input can be explained as a result of experience, the availability to the leader of staff member judgment confidence, and the cumulative past accuracy of each staff member. The availability to the team leader of staff member past judgment accuracy and staff member judgment confidence was provided in an environment in which differential staff weighting was the appropriate staff utilization strategy. Eighty-four leaders of four-person decision-making teams performed 63 decisions on a computerized decision-making task. Both experience and providing leaders with cumulative staff past accuracy information were related to greater staff weighting variability and greater staff weighting accuracy. Although positively related to staff weighting, staff confidence information did not improve leader weighting variability nor actual staff weighting accuracy. Copyright 1999 Academic Press.

  13. Leader as critical thinker. (United States)

    Lemire, Judith A


    A leader possess the critical-thinking knowledge and skills that provide the framework from which complex problem solving evolves. This article explores the leader as critical thinker, including a progressive plan for integrating critical-thinking concepts and associated teaching strategies into the RN to BSN and graduate curricula. To improve the critical thinking of nurses, educators must emphasize the cognitive and disposition aspects of critical thinking; promote active and sequential learning; role model critical thinking; design practical that focus on leadership and critical thinking; and conduct valid and consistent evaluations. The acquisition and application of critical thinking and problem-solving skills are progressive and refined through life-long learning and experience. This expertise begins with a sound knowledge base of the critical thinking composite and problem-solving strategies.

  14. Quantum Leader Election


    Ganz, Maor


    Leader election between n parties is known to be impossible classically. This work gives a simple algorithm that does it, based on the weak coin flipping protocol with arbitrarily small bias derived by Mochon in 2007, and recently published and simplified in Aharonov et al in 2016. A protocol with linear number of coin flipping rounds is quite simple to achieve; We further provide an improvement to logarithmic number of coin flipping rounds. This is a much improved journal version of a prepri...

  15. Follow the leader


    Szweda, Roy


    Capitalism is driven by technological revolutions, leading to alternating periods of regulation and deregulation in leading economies. Technologically backward countries face a different situation as they have to catch up with the leaders. Against this backdrop, Theo van de Klundert examines the relationship between capitalism and democracy, combining economic theory and historical description to analyse long-run economic development. Emphasis is placed on the interrelation between economic a...

  16. What makes a leader? (United States)

    Goleman, D


    Superb leaders have very different ways of directing a team, a division, or a company. Some are subdued and analytical; others are charismatic and go with their gut. And different of situations call for different types of leadership. Most mergers need a sensitive negotiator at the helm whereas many turnarounds require a more forceful kind of authority. Psychologist and noted author Daniel Goleman has found, however, that effective leaders are alike in one crucial way: they all have a high degree of what has come to be known as emotional intelligence. In fact, Goleman's research at nearly 200 large, global companies revealed that emotional intelligence--especially at the highest levels of a company--is the sine qua non for leadership. Without it, a person can have first-class training, an incisive mind, and an endless supply of good ideas, but he still won't make a great leader. The components of emotional intelligence--self-awareness, self-regulation, motivation, empathy, and social skill--can sound unbusinesslike. But exhibiting emotional intelligence at the workplace does not mean simply controlling your anger or getting along with people. Rather it means understanding your own and other people's emotional makeup well enough to move people in the direction of accomplishing your company's goals. In this article, the author discusses each component of emotional intelligence and shows through examples how to recognize it in potential leaders, how and why it leads to measurable business results, and how it can be learned. It takes time and, most of all, commitment. But the benefits that come from having a well-developed emotional intelligence, both for the individual and the organization, make it worth the effort.

  17. Cultivating Leaders of Indiana


    yaryyeva, Annagul; Sdunzik, Jennifer


    "Cultivating Leaders of Indiana" was developed to establish connections between the Purdue student body and the Frankfort community. By engaging high school students in workshops that focused on local, national, and global identities, the goal of the project was to encourage students to appreciate their individuality and to motivate them to translate their skills into a global perspective.Moreover, workshops centering on themes such as culture, citizenship, media, and education were designed ...

  18. The wise leader. (United States)

    Nonaka, Ikujiro; Takeuchi, Hirotaka


    In an era of increasing discontinuity, wise leadership has nearly vanished. Many leaders find it difficult to reinvent their corporations rapidly enough to cope with new technologies, demographic shifts, and consumption trends. They can't develop truly global organizations that operate effortlessly across borders. And they find it tough to ensure that their people adhere to values and ethics. The authors assert that leaders must acquire practical wisdom, or what Aristotle called phronesis: experiential knowledge that enables people to make ethically sound judgments. Wise leaders demonstrate six abilities: (i) They make decisions on the basis of what is good for the organization and for society. (2) They quickly grasp the essence of a situation and fathom the nature and meaning of people, things, and events. (3) They provide contexts in which executives and employees can interact to create new meaning. (4) They employ metaphors and stories to convert their experience into tacit knowledge that others can use. (5) They exert political power to bring people together and spur them to act. (6) They use apprenticeship and mentoring to cultivate practical wisdom in orders.

  19. The Radon Cumulative Distribution Transform and Its Application to Image Classification. (United States)

    Kolouri, Soheil; Park, Se Rim; Rohde, Gustavo K


    Invertible image representation methods (transforms) are routinely employed as low-level image processing operations based on which feature extraction and recognition algorithms are developed. Most transforms in current use (e.g., Fourier, wavelet, and so on) are linear transforms and, by themselves, are unable to substantially simplify the representation of image classes for classification. Here, we describe a nonlinear, invertible, low-level image processing transform based on combining the well-known Radon transform for image data, and the 1D cumulative distribution transform proposed earlier. We describe a few of the properties of this new transform, and with both theoretical and experimental results show that it can often render certain problems linearly separable in a transform space.

  20. A Screening Method for Assessing Cumulative Impacts

    Directory of Open Access Journals (Sweden)

    Joan Denton


    Full Text Available The California Environmental Protection Agency (Cal/EPA Environmental Justice Action Plan calls for guidelines for evaluating “cumulative impacts.” As a first step toward such guidelines, a screening methodology for assessing cumulative impacts in communities was developed. The method, presented here, is based on the working definition of cumulative impacts adopted by Cal/EPA [1]: “Cumulative impacts means exposures, public health or environmental effects from the combined emissions and discharges in a geographic area, including environmental pollution from all sources, whether single or multi-media, routinely, accidentally, or otherwise released. Impacts will take into account sensitive populations and socio-economic factors, where applicable and to the extent data are available.” The screening methodology is built on this definition as well as current scientific understanding of environmental pollution and its adverse impacts on health, including the influence of both intrinsic, biological factors and non-intrinsic socioeconomic factors in mediating the effects of pollutant exposures. It addresses disparities in the distribution of pollution and health outcomes. The methodology provides a science-based tool to screen places for relative cumulative impacts, incorporating both the pollution burden on a community- including exposures to pollutants, their public health and environmental effects- and community characteristics, specifically sensitivity and socioeconomic factors. The screening methodology provides relative rankings to distinguish more highly impacted communities from less impacted ones. It may also help identify which factors are the greatest contributors to a community’s cumulative impact. It is not designed to provide quantitative estimates of community-level health impacts. A pilot screening analysis is presented here to illustrate the application of this methodology. Once guidelines are adopted, the methodology can

  1. A screening method for assessing cumulative impacts. (United States)

    Alexeeff, George V; Faust, John B; August, Laura Meehan; Milanes, Carmen; Randles, Karen; Zeise, Lauren; Denton, Joan


    The California Environmental Protection Agency (Cal/EPA) Environmental Justice Action Plan calls for guidelines for evaluating "cumulative impacts." As a first step toward such guidelines, a screening methodology for assessing cumulative impacts in communities was developed. The method, presented here, is based on the working definition of cumulative impacts adopted by Cal/EPA: "Cumulative impacts means exposures, public health or environmental effects from the combined emissions and discharges in a geographic area, including environmental pollution from all sources, whether single or multi-media, routinely, accidentally, or otherwise released. Impacts will take into account sensitive populations and socio-economic factors, where applicable and to the extent data are available." The screening methodology is built on this definition as well as current scientific understanding of environmental pollution and its adverse impacts on health, including the influence of both intrinsic, biological factors and non-intrinsic socioeconomic factors in mediating the effects of pollutant exposures. It addresses disparities in the distribution of pollution and health outcomes. The methodology provides a science-based tool to screen places for relative cumulative impacts, incorporating both the pollution burden on a community- including exposures to pollutants, their public health and environmental effects- and community characteristics, specifically sensitivity and socioeconomic factors. The screening methodology provides relative rankings to distinguish more highly impacted communities from less impacted ones. It may also help identify which factors are the greatest contributors to a community's cumulative impact. It is not designed to provide quantitative estimates of community-level health impacts. A pilot screening analysis is presented here to illustrate the application of this methodology. Once guidelines are adopted, the methodology can serve as a screening tool to help Cal

  2. Two new constraints for the cumulant matrix

    Energy Technology Data Exchange (ETDEWEB)

    Ramos-Cordoba, Eloy; Salvador, Pedro; Matito, Eduard [Institut de Química Computacional i Catàlisi (IQCC) and Department de Química, Universitat de Girona, Campus de Montilivi, 17071 Girona, Catalonia (Spain); Piris, Mario [Kimika Fakultatea, Euskal Herriko Unibertsitatea UPV/EHU, and Donostia International Physics Center (DIPC). P.K. 1072, 20080 Donostia, Euskadi (Spain)


    We suggest new strict constraints that the two-particle cumulant matrix should fulfill. The constraints are obtained from the decomposition of 〈S-^{sup 2}〉, previously developed in our laboratory, and the vanishing number of electrons shared by two non-interacting fragments. The conditions impose stringent constraints into the cumulant structure without any need to perform an orbital optimization procedure thus carrying very small or no computational effort. These constraints are tested on the series of Piris natural orbital functionals (PNOF), which are among the most accurate ones available in the literature. Interestingly, even though all PNOF cumulants ensure correct overall 〈S{sup ^2}〉 values, none of them is consistent with the local spin structure of systems that dissociate more than one pair of electrons. A careful analysis of the local spin components reveals the most important missing contributions in the cumulant expression thus suggesting a means to improve PNOF5. The constraints provide an inexpensive tool for the construction and testing of cumulant structures that complement previously known conditions such as the N-representability or the square of the total spin angular momentum, 〈S{sup ^2}〉.

  3. Predicting Cumulative Incidence Probability by Direct Binomial Regression

    DEFF Research Database (Denmark)

    Scheike, Thomas H.; Zhang, Mei-Jie

    Binomial modelling; cumulative incidence probability; cause-specific hazards; subdistribution hazard......Binomial modelling; cumulative incidence probability; cause-specific hazards; subdistribution hazard...

  4. Predicting Cumulative Incidence Probability: Marginal and Cause-Specific Modelling

    DEFF Research Database (Denmark)

    Scheike, Thomas H.; Zhang, Mei-Jie


    cumulative incidence probability; cause-specific hazards; subdistribution hazard; binomial modelling......cumulative incidence probability; cause-specific hazards; subdistribution hazard; binomial modelling...

  5. Automated real-time epileptic seizure detection in scalp EEG recordings using an algorithm based on wavelet packet transform. (United States)

    Zandi, Ali Shahidi; Javidan, Manouchehr; Dumont, Guy A; Tafreshi, Reza


    A novel wavelet-based algorithm for real-time detection of epileptic seizures using scalp EEG is proposed. In a moving-window analysis, the EEG from each channel is decomposed by wavelet packet transform. Using wavelet coefficients from seizure and nonseizure references, a patient-specific measure is developed to quantify the separation between seizure and nonseizure states for the frequency range of 1-30 Hz. Utilizing this measure, a frequency band representing the maximum separation between the two states is determined and employed to develop a normalized index, called combined seizure index (CSI). CSI is derived for each epoch of every EEG channel based on both rhythmicity and relative energy of that epoch as well as consistency among different channels. Increasing significantly during ictal states, CSI is inspected using one-sided cumulative sum test to generate proper channel alarms. Analyzing alarms from all channels, a seizure alarm is finally generated. The algorithm was tested on scalp EEG recordings from 14 patients, totaling approximately 75.8 h with 63 seizures. Results revealed a high sensitivity of 90.5%, a false detection rate of 0.51 h(-1) and a median detection delay of 7 s. The algorithm could also lateralize the focus side for patients with temporal lobe epilepsy.

  6. Electrocardiogram de-noising based on forward wavelet transform ...

    Indian Academy of Sciences (India)

    noising based on thresholding of the coefficients obtained from the application of the Forward Wavelet Transform Translation Invariant (FWT_TI) to each Bionic Wavelet coefficient. The De-noise De-noised ECG is obtained from the application ...

  7. adaptive single-pole autoreclosure scheme based on wavelet ...

    African Journals Online (AJOL)


    WAVELET TRANSFORM AND MULTILAYER PERCEPTRON. E. A. Frimpong, P. Y. Okyere and E. K. Anto. Department of ... value to achieve successful autoreclosing (Park et al., 2004; Megahed et al., 2003; Kim et al.,. 2000; Ahn ... transform (Fitton et al., 1996; Zoric et al.,. 2000), and wavelet transform (Yu and Song,. 1998a ...

  8. Wavelet Transforms: Application to Data Analysis - I -10 ...

    Indian Academy of Sciences (India)

    include image processing and artificial intelligence. ... Fourier domain. Broadly speaking, two different fea- tures common to all wavelets are responsible for their utility value. The basis functions of the wavelets are produced from two units, the ... Here, j and k take integral values, the values of j range from 0 to 00, whereas ...

  9. Polarized spectral features of human breast tissues through wavelet ...

    Indian Academy of Sciences (India)


    Nov 27, 2015 ... Fluorescence characteristics of human breast tissues are investigated through wavelet transform and principal component analysis (PCA). Wavelet transform of polarized fluorescence spectra of human breast tissues is found to localize spectral features that can reliably differentiate different tissue types.

  10. Noisy signal filtration using complex wavelet basis sets (United States)

    Yaseen, A. S.; Pavlova, O. N.; Pavlov, A. N.


    Methods of noisy signal filtration using a discrete wavelet transform (DWT) with real basis sets of the Daubechies family are compared to methods employing a double-density dual-tree complex wavelet transform (DDCWT) with excess (nonorthonormalized) basis sets. Recommendations concerning the choice of filter parameters for minimization of the error of noisy signal filtration are formulated.

  11. SVD-based digital image watermarking using complex wavelet ...

    Indian Academy of Sciences (India)

    A new robust method of non-blind image watermarking is proposed in this paper. The suggested method is performed by modification on singular value decomposition (SVD) of images in Complex Wavelet Transform (CWT) domain while CWT provides higher capacity than the real wavelet domain. Modification of the ...

  12. Multidimensional filter banks and wavelets research developments and applications

    CERN Document Server

    Levy, Bernard


    Multidimensional Filter Banks and Wavelets: Reserach Developments and Applications brings together in one place important contributions and up-to-date research results in this important area. Multidimensional Filter Banks and Wavelets: Research Developments and Applications serves as an excellent reference, providing insight into some of the most important research issues in the field.

  13. Fault diagnosis in gear using wavelet envelope power spectrum ...

    African Journals Online (AJOL)

    An experimental data set is used to compare the diagnostic capability of the fast Fourier transform power spectrum to the wavelet envelope power spectrum as respectively computed using Laplace and Morlet wavelet functions. The gear testing apparatus was used for experimental studies to obtain the vibration signal from ...

  14. Multiresolution signal decomposition schemes. Part 2: Morphological wavelets

    NARCIS (Netherlands)

    H.J.A.M. Heijmans (Henk); J. Goutsias (John)


    htmlabstractIn its original form, the wavelet transform is a linear tool. However, it has been increasingly recognized that nonlinear extensions are possible. A major impulse to the development of nonlinear wavelet transforms has been given by the introduction of the lifting scheme by Sweldens. The

  15. Wavelet transform of generalized functions in K′{Mp} spaces

    Indian Academy of Sciences (India)

    Using convolution theory in K { M p } space we obtain bounded results for the wavelet transform. Calderón-type reproducing formula is derived in distribution sense as an application of the same. An inversion formula for the wavelet transform of generalized functions is established.

  16. A Load Balanced Domain Decomposition Method Using Wavelet Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Jameson, L; Johnson, J; Hesthaven, J


    Wavelet Analysis provides an orthogonal basis set which is localized in both the physical space and the Fourier transform space. We present here a domain decomposition method that uses wavelet analysis to maintain roughly uniform error throughout the computation domain while keeping the computational work balanced in a parallel computing environment.

  17. Leader emergence: the case of the narcissistic leader. (United States)

    Brunell, Amy B; Gentry, William A; Campbell, W Keith; Hoffman, Brian J; Kuhnert, Karl W; Demarree, Kenneth G


    These studies investigate whether individuals with high narcissism scores would be more likely to emerge as leaders during leaderless group discussions. The authors hypothesized that narcissists would emerge as group leaders. In three studies, participants completed personality questionnaires and engaged in four-person leaderless group discussions. Results from all three studies reveal a link between narcissism and leader emergence. Studies 1 and 2 further reveal that the power dimension of narcissism predicted reported leader emergence while controlling for sex, self-esteem, and the Big Five personality traits. Study 3 demonstrates an association between narcissism and expert ratings of leader emergence in a group of executives. The implications of the propensity of narcissists to emerge as leaders are discussed.

  18. Career anchors of dentist leaders. (United States)

    Tuononen, Tiina; Lammintakanen, Johanna; Suominen, Anna Liisa


    The work of a health care leader is demanding; in order to cope, leaders need motivation and support. The occurrence of intrinsic factors called career anchors (combination of one's competence, motives and values) could be a contributing factor in dentist leaders' career decisions. The aim of our study was to identify dentist leaders' career anchors and their association to dentist leaders' retention or turnover of the leadership position. Materials were gathered in 2014 via an electronic questionnaire from 156 current (Leaders) or former (Leavers) Finnish dentist leaders. Career anchor evaluation was conducted by the questionnaire and scoring-table taken from Edgar Schein's Career Anchors Self-Assessment. Both the most and the least important career anchors were detected by the highest and lowest scores and their occurrence reported as percentages. Associations between career anchor scores and tendency to stay were analyzed with logistic regression. 'Technical/Functional Competence' and 'Lifestyle' were most frequently reported as the most important and 'Entrepreneurial Creativity' and 'General Managerial Competence' as the least important career anchors. However, a higher level of 'General Managerial Competence' anchor was most significantly associated with staying in a leadership position. Instead, 'Pure Challenge' and 'Lifestyle' decreased the odds to stay. The knowledge of the important and essential career anchors of dentist leaders' and individuals' could perform crucial part in career choices and also in planning education, work opportunities and human resource policies promoting retention of dentist leaders and probably also other health care leaders.

  19. Application of higher order cumulant features for cardiac health diagnosis using ECG signals. (United States)

    Martis, Roshan Joy; Acharya, U Rajendra; Lim, Choo Min; Mandana, K M; Ray, A K; Chakraborty, Chandan


    Electrocardiogram (ECG) is the electrical activity of the heart indicated by P, Q-R-S and T wave. The minute changes in the amplitude and duration of ECG depicts a particular type of cardiac abnormality. It is very difficult to decipher the hidden information present in this nonlinear and nonstationary signal. An automatic diagnostic system that characterizes cardiac activities in ECG signals would provide more insight into these phenomena thereby revealing important clinical information. Various methods have been proposed to detect cardiac abnormalities in ECG recordings. Application of higher order spectra (HOS) features is a seemingly promising approach because it can capture the nonlinear and dynamic nature of the ECG signals. In this paper, we have automatically classified five types of beats using HOS features (higher order cumulants) using two different approaches. The five types of ECG beats are normal (N), right bundle branch block (RBBB), left bundle branch block (LBBB), atrial premature contraction (APC) and ventricular premature contraction (VPC). In the first approach, cumulant features of segmented ECG signal were used for classification; whereas in the second approach cumulants of discrete wavelet transform (DWT) coefficients were used as features for classifiers. In both approaches, the cumulant features were subjected to data reduction using principal component analysis (PCA) and classified using three layer feed-forward neural network (NN) and least square-support vector machine (LS-SVM) classifiers. In this study, we obtained the highest average accuracy of 94.52%, sensitivity of 98.61% and specificity of 98.41% using first approach with NN classifier. The developed system is ready clinically to run on large datasets.

  20. Wavelet discretization of the engineered barrier system. Technical report

    Energy Technology Data Exchange (ETDEWEB)

    Nasif, Hesham; Umeki, Hiroyuki [Japan Nuclear Cycle Development Inst., Tokai, Ibaraki (Japan)


    The relative merits of the wavelet-Galerkin solution of the nonlinear system of partial differential equations arising from a model formulation of migration of high-level radioactive waste (HLW) are quantitatively and qualitatively analyzed. Wavelet functions are generated by dilation and translation on a scaling function. The wavelet functions are localized in space and compactly supported, so these properties can be utilized to solve differential equations that have severe 'stiff'. A mathematical model for predicting the nuclide migration of (HLW) was formulated and compared with the results from the reference case. The model, which is wavelet-discretized model, is devised to be very reasonable and accurate by proper selection of wavelet order and dilation order pair. We would like to thank Mr. Atsushi Neyama (Computer Software Development Co., Ltd.) and Prof. Atsuyuki Suzuki (Department of Quantum Engineering and Systems Science) for some productive discussions and their critical reviews of this study. (author)

  1. International Conference and Workshop on Fractals and Wavelets

    CERN Document Server

    Barnsley, Michael; Devaney, Robert; Falconer, Kenneth; Kannan, V; PB, Vinod


    Fractals and wavelets are emerging areas of mathematics with many common factors which can be used to develop new technologies. This volume contains the selected contributions from the lectures and plenary and invited talks given at the International Workshop and Conference on Fractals and Wavelets held at Rajagiri School of Engineering and Technology, India from November 9-12, 2013. Written by experts, the contributions hope to inspire and motivate researchers working in this area. They provide more insight into the areas of fractals, self similarity, iterated function systems, wavelets and the applications of both fractals and wavelets. This volume will be useful for the beginners as well as experts in the fields of fractals and wavelets.

  2. Introduction to wavelet-based compression of medical images. (United States)

    Schomer, D F; Elekes, A A; Hazle, J D; Huffman, J C; Thompson, S K; Chui, C K; Murphy, W A


    Medical image compression can significantly enhance the performance of picture archiving and communication systems and may be considered an enabling technology for telemedicine. The wavelet transform is a powerful mathematical tool with many unique qualities that are useful for image compression and processing applications. Although wavelet concepts can be traced back to 1910, the mathematics of wavelets have only recently been formalized. By exploiting spatial and spectral information redundancy in images, wavelet-based methods offer significantly better results for compressing medical images than do compression algorithms based on Fourier methods, such as the discrete cosine transform used by the Joint Photographic Experts Group. Furthermore, wavelet-based compression does not suffer from blocking artifacts, and the restored image quality is generally superior at higher compression rates.

  3. Combining Wavelet Transform and Hidden Markov Models for ECG Segmentation

    Directory of Open Access Journals (Sweden)

    Jérôme Boudy


    Full Text Available This work aims at providing new insights on the electrocardiogram (ECG segmentation problem using wavelets. The wavelet transform has been originally combined with a hidden Markov models (HMMs framework in order to carry out beat segmentation and classification. A group of five continuous wavelet functions commonly used in ECG analysis has been implemented and compared using the same framework. All experiments were realized on the QT database, which is composed of a representative number of ambulatory recordings of several individuals and is supplied with manual labels made by a physician. Our main contribution relies on the consistent set of experiments performed. Moreover, the results obtained in terms of beat segmentation and premature ventricular beat (PVC detection are comparable to others works reported in the literature, independently of the type of the wavelet. Finally, through an original concept of combining two wavelet functions in the segmentation stage, we achieve our best performances.

  4. Discrete wavelet analysis for multiparticle production experiments

    CERN Document Server

    Georgopoulos, G; Vassiliou, Maria


    In high energy nucleus-nucleus collisions (SPS, RHIC, LHC) and in cosmic ray interactions, many particles are produced in the available phase space. We make an attempt to apply the wavelets technique in order to classify such events according to the event pattern and also to locate the so-called "clustering" in a distribution. After describing the method, we demonstrate its power (a) to a single event, produced by a pion condensation theoretical model, (b) to a sample of Pb-Pb simulated data at 158 GeV/c per nucleon taking into account all the experimental uncertainties. (15 refs).

  5. Lung tissue classification using wavelet frames. (United States)

    Depeursinge, Adrien; Sage, Daniel; Hidki, Asmâa; Platon, Alexandra; Poletti, Pierre-Alexandre; Unser, Michael; Müller, Henning


    We describe a texture classification system that identifies lung tissue patterns from high-resolution computed tomography (HRCT) images of patients affected with interstitial lung diseases (ILD). This pattern recognition task is part of an image-based diagnostic aid system for ILDs. Five lung tissue patterns (healthy, emphysema, ground glass, fibrosis and microdules) selected from a multimedia database are classified using the overcomplete discrete wavelet frame decompostion combined with grey-level histogram features. The overall multiclass accuracy reaches 92.5% of correct matches while combining the two types of features, which are found to be complementary.

  6. Building leaders paving the path for emerging leaders

    CERN Document Server

    Stoner, Charles R


    Although the selection and development of emerging leaders is fundamental to organizational growth and success, many organizations are facing a troubling scenario - a striking gap between the leaders they need and the talent available to assume the mantle of leadership. This book, grounded in empirical investigations and philosophical insights into the study of leadership, is designed to help emerging leaders bridge the gap between 'new leader' and confident, respected difference maker. From the development of leadership skills to the practice and application of successful strategies, award-wi

  7. Cumulative Culture and Future Thinking: Is Mental Time Travel a Prerequisite to Cumulative Cultural Evolution? (United States)

    Vale, G. L.; Flynn, E. G.; Kendal, R. L.


    Cumulative culture denotes the, arguably, human capacity to build on the cultural behaviors of one's predecessors, allowing increases in cultural complexity to occur such that many of our cultural artifacts, products and technologies have progressed beyond what a single individual could invent alone. This process of cumulative cultural evolution…

  8. On leadership and leaders. (United States)

    Haddad, Mary Jo


    Leadership is the vital ingredient to achieving organizational excellence and outstanding healthcare systems. There is so much to be celebrated when reflecting on the evolution of healthcare leadership over the past 50 years. However, in 50 years, we have created silos of care, of funding and of social policy that have undermined our progress in improving the care process, shifting away from health and toward healthcare, and we have lost the opportunity to promote streamlined care through the continuum of health needs. Exemplary healthcare leaders of tomorrow will need sophisticated business skills, balanced with the capacity to inspire innovation, in order to manage an ever-growing complex environment.

  9. Paul Everett Meehl: the cumulative record. (United States)

    Waller, Niels G; Lilienfeld, Scott O


    In this brief biographical sketch of Paul Meehl, the authors examine the "cumulative record" of his scholarship and mentorship. This record sheds light on why Meehl is widely regarded as one of the most influential clinical psychologists of the 20th century, as well as on Meehl's remarkable intellectual life. Time has proven that Meehl's writings are exceptional in their quality, influence, breadth, and depth. In addition, Meehl's cumulative record raises important questions regarding the reinforcement contingencies in major research-oriented psychology departments. 2005 Wiley Periodicals, Inc.

  10. Strategic Leader as Strategic Communicator (United States)


    efforts personally. “In an era of instant communications and 24-hour news cycles, the strategic leader must be able to manage meaning, be able to ‘tell... model to leaders and commanders in every unit at every level. With his charter as a roadmap, we must strategically plan those engagements...entire DOD. By role modeling now the behaviors and actions of a truly inculcated culture of engagement, strategic leaders can chart the future

  11. Managing a Leader Transition Process (United States)


    GENERAL DOUGLAS MACARTHUR MILITARY LEADERSHIP WRITING COMPETITION SUBMISSION Managing a Leader Transition Process Major Michael B. Siegl 23...DATE 23 FEB 2007 2. REPORT TYPE 3. DATES COVERED 00-00-2007 to 00-00-2007 4. TITLE AND SUBTITLE Managing a Leader Transition Process 5a...1 Managing a Leader Transition Process …one should bear in mind that there is nothing more difficult to execute, nor more dubious of

  12. Strategic Military Leaders - Leading Tomorrow (United States)


    St ra te gy R es ea rc h Pr oj ec t STRATEGIC MILITARY LEADERS –LEADING TOMORROW BY COLONEL NG WAI KIT Singapore Army DISTRIBUTION...Strategic Military Leaders - Leading Tomorrow 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Ng Kit 5d. PROJECT...STRATEGIC MILITARY LEADERS – LEADING TOMORROW by Colonel Ng Wai Kit Singapore Army Dr. Leonard Wong Project

  13. Economic Thinking for Strategic Leaders (United States)


    future stewards of the profession. 8 Political-Cultural. Army leaders require the expertise to manage cultures across organizational and... management theorists as well as detailed review of the frameworks components and how it can be an aid to inform senior leader judgment when facing...St ra te gy R es ea rc h Pr oj ec t ECONOMIC THINKING FOR STRATEGIC LEADERS BY COLONEL MARK B. KELLY United States Army DISTRIBUTION

  14. Systems Thinking for Strategic Leaders (United States)


    managers resulted in them doing things ―right‖ within well-defined structures. Ackoff offered that systems thinking was required by leaders to determine...concepts across three distinct domains—organizational management , international politics, and military doctrine—for strategic leaders in each of...SYSTEMS THINKING FOR STRATEGIC LEADERS Colonel (Retired) Charles D. Allen Professor of Cultural Science Colonel (Retired) Glenn K

  15. Developing Leaders for Army 2020 (United States)


    Soldiers over the next five years, with a reduction of eight Brigade Combat Teams over this same time period.3 Army senior leaders and force managers ...properly reduce personnel and leader levels to meet end strength directives. As the Army draws down end strength, a challenge arises for force managers ...many managers and leaders , reducing continuity, and leaving firms with teams doing multiple tasks.48 Multi Source Assessment and Feedback instruments

  16. Strategic Communication for Tactical Leaders (United States)


    STRATEGIC COMMUNICATION FOR TACTICAL LEADERS A thesis presented to the Faculty of the U.S. Army Command and General Staff College...Strategic Communication for Tactical Leaders 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Major Lee...currently evolving concept in the U.S. military, and it is currently not widely understood what role, if any, leaders at the tactical level have in it. In

  17. Innovativeness of nurse leaders. (United States)

    Clement-O'Brien, Karen; Polit, Denise F; Fitzpatrick, Joyce J


    The purpose of the present study was to describe the innovativeness and the rate of adoption of change among chief nursing officers (CNOs) of acute care hospitals, and explore the difference in the innovativeness of CNOs of Magnet hospitals vs. non-Magnet hospitals. There is little evidence to guide the description of innovativeness for nurse leaders, crucial to the implementation of evidence-based practice standards. CNOs of acute care hospitals of New York State participated in a mailed survey which incorporated the Scale for the Measurement of Innovativeness. The response rate was 41% (106/261). The majority of the sample was prepared at the master's level with 5-10 years of experience in the CNO role. A significant relationship was found between the innovativeness scale scores and the innovativeness diversity index. The CNOs who completed more leadership courses had implemented significantly more types of innovations and had higher innovativeness scale scores.   Graduate level education, years of CNO experience and leadership course completion were identified as significantly influencing innovativeness of CNOs. The characteristics of innovativeness for nurse leaders presented in the present study may assist organizations, CNOs and the Magnet recognition programme to describe innovativeness that supports organizations to continuously improve the quality of patient care. © 2011 The Authors. Journal compilation © 2011 Blackwell Publishing Ltd.

  18. Solar activity explored with new wavelet methods

    Directory of Open Access Journals (Sweden)

    H. Lundstedt


    Full Text Available In order to improve the forecasts of the impact of solar activity on the terrestrial environment on time scales longer than days, improved understanding and forecasts of the solar activity are needed. The first results of a new approach of modelling and forecasting solar activity are presented. Time series of solar activity indicators, such as sunspot number, group sunspot number, F10.7, E10.7, solar magnetic mean field, Mount Wilson plage and sunspot index, have been studied with new wavelet methods; ampligrams and time-scale spectra. Wavelet power spectra of the sunspot number for the period 1610 up to the present show not only that a dramatic increase in the solar activity took place after 1940 but also that an interesting change occurred in 1990. The main 11-year solar cycle was further studied with ampligrams for the period after 1850. time-scale spectra were used to examine the processes behind the variability of the solar activity. Several interesting deterministic and more stochastic features were detected in the time series of the solar activity indicators. The solar nature of these features will be further studied. Keywords. Solar physics, astrophysics and astronomy (Magnetic fields; Stellar interiors and dynamo theory – Space plasma physics (nonlinear phenomena

  19. ERG signal analysis using wavelet transform. (United States)

    Barraco, R; Persano Adorno, D; Brai, M


    The wavelet analysis is a powerful tool for analyzing and detecting features of signals characterized by time-dependent statistical properties, as biomedical signals. The identification and the analysis of the components of these signals in the time-frequency domain, give meaningful information about the physiological mechanisms that govern them. This article presents the results of the wavelet analysis applied to the a-wave component of the human electroretinogram. In order to deepen and improve our knowledge about the behavior of the early photoreceptoral response, including the possible activation of interactions and correlations among the photoreceptors, we have detected and identified the stable time-frequency components of the a-wave, using six representative values of luminance. The results indicate the occurrence of three frequencies lying in the range 20-200 Hz. The lowest one is attributed to the summed activities of the photoreceptors. The others are weaker and at low luminance one of them does not occur. We relate them to the response of the rods and the cones whose aggregate activities are non-linear and typically exhibit self-organization under selective stimuli. The identification of the stable frequency components and of their times of occurrence helps us to shine light about the complex mechanisms governing the a-wave. The present results are promising toward the assessment of more refined model concerning the photoreceptoral activities.

  20. Multifractal and wavelet analysis of epileptic seizures (United States)

    Dick, Olga E.; Mochovikova, Irina A.

    The aim of the study is to develop quantitative parameters of human electroencephalographic (EEG) recordings with epileptic seizures. We used long-lasting recordings from subjects with epilepsy obtained as part of their clinical investigation. The continuous wavelet transform of the EEG segments and the wavelet-transform modulus maxima method enable us to evaluate the energy spectra of the segments, to fin lines of local maximums, to gain the scaling exponents and to construct the singularity spectra. We have shown that the significant increase of the global energy with respect to background and the redistribution of the energy over the frequency range are observed in the patterns involving the epileptic activity. The singularity spectra expand so that the degree of inhomogenety and multifractality of the patterns enhances. Comparing the results gained for the patterns during different functional probes such as open and closed eyes or hyperventilation we demonstrate the high sensitivity of the analyzed parameters (the maximal global energy, the width and asymmetry of the singularity spectrum) for detecting the epileptic patterns.

  1. Inertial Sensor Signals Denoising with Wavelet Transform

    Directory of Open Access Journals (Sweden)

    Ioana-Raluca EDU


    Full Text Available In the current paper we propose a new software procedure for processing data from an inertial navigation system boarded on a moving vehicle, in order to achieve accurate navigation information on the displacement of the vehicle in terms of position, speed, acceleration and direction. We divided our research in three phases. In the first phase of our research, we implemented a real-time evaluation criterion with the intention of achieving real-time data from an accelerometer. It is well-known that most errors in the detection of position, velocity and attitude in inertial navigation occur due to difficult numerical integration of noise. In the second phase, we were interested in achieving a better estimation and compensation of the gyro sensor angular speed measurements. The errors of these sensors occur because of their miniaturization, they cannot be eliminated but can be modelled by applying specific signal processing methods. The objective of both studies was to propose a signal processing algorithm, based on Wavelet filter, along with a criterion for evaluating and updating the optimal decomposition level of Wavelet transform for achieving accurate information from inertial sensors. In the third phase of our work we are suggesting the utility of a new complex algorithm for processing data from an inertial measurement unit, containing both miniaturized accelerometers and gyros, after undergoing a series of numerical simulations and after obtaining accurate information on vehicle displacement

  2. Investigation of hydrological drought using Cumulative Standardized ...

    Indian Academy of Sciences (India)

    The cumulative droughtconcept is proposed to characterize long-term hydrologic drought, which affects the shallow groundwaterproductivity in terms of quantity and quality. Gamma probability distribution was fitted to the long-termannual precipitation in Damascus from 1918–1919 to 2007–2008 (n = 90 years). Generally ...

  3. An axiomatization of cumulative prospect theory

    NARCIS (Netherlands)

    P.P. Wakker (Peter); A. Tversky (Amos)


    textabstractThis paper presents a method for axiomatizing a variety of models for decision making under uncertainty, including Expected Utility and Cumulative Prospect Theory. This method identifies, for each model, the situations that permit consistent inferences about the ordering of value

  4. Pavlovian conditioning and cumulative reinforcement rate. (United States)

    Harris, Justin A; Patterson, Angela E; Gharaei, Saba


    In 5 experiments using delay conditioning of magazine approach with rats, reinforcement rate was varied either by manipulating the mean interval between onset of the conditioned stimulus (CS) and unconditioned stimulus (US) or by manipulating the proportion of CS presentations that ended with the US (trial-based reinforcement rate). Both manipulations influenced the acquisition of responding. In each experiment, a specific comparison was made between 2 CSs that differed in their mean CS-US interval and in their trial-based reinforcement rate, such that the cumulative reinforcement rate-the cumulative duration of the CS between reinforcements-was the same for the 2 CSs. For example, a CS reinforced on 100% of trials with a mean CS-US interval of 60 s was compared with a CS reinforced on 33% of trials and a mean duration of 20 s. Across the 5 experiments, conditioning was virtually identical for the 2 CSs with matched cumulative reinforcement rate. This was true as long as the timing of the US was unpredictable and, thus, response rates were uniform across the length of the CS. We conclude that the effects of CS-US interval and of trial-based reinforcement rate are reducible entirely to their common effect on cumulative reinforcement rate. We discuss the implications of this for rate-based, trial-based, and real-time associative models of conditioning. (c) 2015 APA, all rights reserved).

  5. Calculation of the Poisson cumulative distribution function (United States)

    Bowerman, Paul N.; Nolty, Robert G.; Scheuer, Ernest M.


    A method for calculating the Poisson cdf (cumulative distribution function) is presented. The method avoids computer underflow and overflow during the process. The computer program uses this technique to calculate the Poisson cdf for arbitrary inputs. An algorithm that determines the Poisson parameter required to yield a specified value of the cdf is presented.

  6. Cumulative watershed effects: a research perspective (United States)

    Leslie M. Reid; Robert R. Ziemer


    A cumulative watershed effect (CWE) is any response to multiple land-use activities that is caused by, or results in, altered watershed function. The CWE issue is politically defined, as is the significance of particular impacts. But the processes generating CWEs are the traditional focus of geomorphology and ecology, and have thus been studied for decades. The CWE...

  7. Semiparametric models for cumulative incidence functions. (United States)

    Bryant, John; Dignam, James J


    In analyses of time-to-failure data with competing risks, cumulative incidence functions may be used to estimate the time-dependent cumulative probability of failure due to specific causes. These functions are commonly estimated using nonparametric methods, but in cases where events due to the cause of primary interest are infrequent relative to other modes of failure, nonparametric methods may result in rather imprecise estimates for the corresponding subdistribution. In such cases, it may be possible to model the cause-specific hazard of primary interest parametrically, while accounting for the other modes of failure using nonparametric estimators. The cumulative incidence estimators so obtained are simple to compute and are considerably more efficient than the usual nonparametric estimator, particularly with regard to interpolation of cumulative incidence at early or intermediate time points within the range of data used to fit the function. More surprisingly, they are often nearly as efficient as fully parametric estimators. We illustrate the utility of this approach in the analysis of patients treated for early stage breast cancer.

  8. Online Leader Training Course: Nebraska Equine Extension Leader Certification (United States)

    Cottle, Lena; D'Angelo, Nicole


    The Nebraska Equine Advancement Level Leader Certification Program is an online learning tool that clarifies principles of the Nebraska 4-H Equine Advancement Programs. Through an online Moodle course through, 4-H leaders and Extension educators are able to fulfill the certification requirement from any location before allowing youth…

  9. Teaching Leaders to Lead Themselves: An Emerging Leader Exercise (United States)

    Chavez, Carolyn I.; Gomez, Claudia; Valenzuela, Marcus; Perera, Yasanthi B.


    This article describes an exercise that allows students to experience and understand the importance of perception in leader emergence. Based on implicit leadership theories, this exercise asks students to provide one another with anonymous feedback about what extent they exhibit various trait-based leader behaviors. This exercise, which can be…

  10. Signal-dependent independent component analysis by tunable mother wavelets

    Energy Technology Data Exchange (ETDEWEB)

    Seo, Kyung Ho


    The objective of this study is to improve the standard independent component analysis when applied to real-world signals. Independent component analysis starts from the assumption that signals from different physical sources are statistically independent. But real-world signals such as EEG, ECG, MEG, and fMRI signals are not statistically independent perfectly. By definition, standard independent component analysis algorithms are not able to estimate statistically dependent sources, that is, when the assumption of independence does not hold. Therefore before independent component analysis, some preprocessing stage is needed. This paper started from simple intuition that wavelet transformed source signals by 'well-tuned' mother wavelet will be simplified sufficiently, and then the source separation will show better results. By the correlation coefficient method, the tuning process between source signal and tunable mother wavelet was executed. Gamma component of raw EEG signal was set to target signal, and wavelet transform was executed by tuned mother wavelet and standard mother wavelets. Simulation results by these wavelets was shown.

  11. Evolutionary Spectra Estimation of Field Measurement Typhoon Processes Using Wavelets

    Directory of Open Access Journals (Sweden)

    Guang-Dong Zhou


    Full Text Available This paper presents a wavelet-based method for estimating evolutionary power spectral density (EPSD of nonstationary stochastic oscillatory processes and its application to field measured typhoon processes. The EPSD, which is deduced in a closed form based on the definition of the EPSD and the algorithm of the continuous wavelet transform, can be formulated as a sum of squared moduli of the wavelet functions in time domain modulated by frequency-dependent coefficients that relate to the squared values of wavelet coefficients and two wavelet functions with different time shifts. A parametric study is conducted to examine the efficacy of the wavelet-based estimation method and the accuracy of different wavelets. The results indicate that all of the estimated EPSDs have acceptable accuracy in engineering application and the Morlet transform can provide desirable estimations in both time and frequency domains. Finally, the proposed method is adopted to investigate the time-frequency characteristics of the Typhoon Matsa measured in bridge site. The nonstationary energy distribution and stationary frequency component during the whole process are found. The work in this paper may promote an improved understanding of the nonstationary features of typhoon winds.

  12. Nerio: Leader Election and Edict Ordering


    van Renesse, Robbert; Schneider, Fred B.; Gehrke, Johannes


    Coordination in a distributed system is facilitated if there is a unique process, the leader, to manage the other processes. The leader creates edicts and sends them to other processes for execution or forwarding to other processes. The leader may fail, and when this occurs a leader election protocol selects a replacement. This paper describes Nerio, a class of such leader election protocols.

  13. Ethical leader behavior and leader effectiveness: the role of prototypicality and trust

    NARCIS (Netherlands)

    Kalshoven, K.; den Hartog, D.N.


    The study examines factors that mediate the impact of ethical leader behavior on leader effectiveness. Little is known about how ethical leadership impacts leader effectiveness. We hypothesized that prototypicality and trust sequentially mediate the relationship between ethical leader behavior and

  14. Wavelet transform based on the optimal wavelet pairs for tunable diode laser absorption spectroscopy signal processing. (United States)

    Li, Jingsong; Yu, Benli; Fischer, Horst


    This paper presents a novel methodology-based discrete wavelet transform (DWT) and the choice of the optimal wavelet pairs to adaptively process tunable diode laser absorption spectroscopy (TDLAS) spectra for quantitative analysis, such as molecular spectroscopy and trace gas detection. The proposed methodology aims to construct an optimal calibration model for a TDLAS spectrum, regardless of its background structural characteristics, thus facilitating the application of TDLAS as a powerful tool for analytical chemistry. The performance of the proposed method is verified using analysis of both synthetic and observed signals, characterized with different noise levels and baseline drift. In terms of fitting precision and signal-to-noise ratio, both have been improved significantly using the proposed method.

  15. Leading Your Leaders (United States)

    Hale, Wayne N.


    Even though working on a problem has been your primary effort for the past year, your leadership may have heard about this once in a briefing a decade ago. Now they are basically clueless. Pretend that you are talking to your daughter's fifth-grade class. Explain how your complicated gizmo works. If possible, do not use acronyms. Define your terms. Put your work in context. Assume your leader has no idea what you do, who you work for, or what your gizmo does. That is a good place to start. Remember, taking the next century to study the problem or spending the Gross National Product to invent a new solution are probably not going to be acceptable solutions. Real engineers and technicians build real hardware that works in the real world in a reasonable manner within a reasonable time at a reasonable cost. True, skimping on time or money can cause mistakes, but folks whose gizmos are delayed unreasonably or cost more than is practical get their programs canceled, force the business into bankruptcy, or give the market over to the competition. Real engineers and technicians always consider cost and schedule in their work. Raising questions is important. However, we are in the business of doing things. Engineers and technicians are paid to get things done. Yes, you have to identify the problem, frame the design, identify the tests, perform the analysis, and assemble the hardware. But the goal is to solve the problem. Nobody ever said flying in space was easy. We make it look easy the same way that an Olympic champion makes her sport look easy: by working hard at improving performance every day. Better are the results of a well-defined test. Remember that a test on a laboratory bench is always an approximation of reality, and rules similar to those for good analysis also apply. One should always be mindful of Mechelay's rule: "It is better to be stupid than to run a stupid test." Often we try to overtest. If a piece of hardware passes an unbelievably difficult test, then

  16. Team Leader System description

    Energy Technology Data Exchange (ETDEWEB)

    Evans, B.J.; Lundeen, T.F.; Moon, B.D.


    Purpose of the project is to design, develop, and demonstrate an advanced, prototype computer system to support on-site inspections. The system is a highly portable field computer with on-line access to facilities information, real-time communications, positioning information, and an electronic notebook for data capture. The Team Leader System provides an inspection team with a suite of advanced communication, data gathering, and data analysis tools and can be implemented on many PC-based hardware platforms. The suitcase unit is a transportable system for on-site support in a vehicle or at a stationary location at an inspection site; the personal unit is a wearable computer for in-facility or on-foot inspections.

  17. Harriet Tubman: A Servant Leader? (United States)


    for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management of the greatest leaders in United States history. Harriet Tubman epitomized the characteristics of a servant- leader . This paper suggests that she

  18. Subordinates' Reactions to Female Leaders. (United States)

    Forsyth, Donelson R.; Forsyth, Nancy M.

    Although recent reviews of the effectiveness of male versus female leaders reveal little evidence of male superiority, evaluative and perceptual biases (beliefs about what constitutes good leadership, and stereotyped beliefs about men and women) among group members persist. To examine attributional biases against female leaders, 85 college…

  19. Library Leaders: Who and Why? (United States)

    Gertzog, Alice


    In this survey, librarians were asked to list leaders in librarianship and their reasons for selecting them to investigate (1) where leadership is perceived in librarianship; (2) how well integrated the field is; (3) whether there is a fieldwide definition of leadership; and (4) similarities among perceived leaders. Sixteen finalists are listed.…

  20. Tartus alustas tegevust LEADER infokeskus

    Index Scriptorium Estoniae


    Tartus alustas tegevust LEADER infokeskus, mille eesmärk on informeerida ja nõustada maakondade omavalitsustöötajate, ettevõtjate ning MTÜde esindajaid, kes on huvitatud Eesti riikliku arengukava meetme "Kohaliku initsiatiivi arendamine - LEADER-tüüpi meetme raames toetuse saamisest ning selleks vajalike partnerlusel põhinevate kohalike tegevusgruppide loomisest"

  1. From the Field: Learning Leaders (United States)

    Weigel, Kathleen; Jones, Richard


    Leadership is essential to successful schools. One of the ways to support effective school leadership is to share ideas and best practices to address the common challenges faced by school leaders. This question and response format addresses common challenges and questions from practicing school leaders in the manner that a mentor might respond to…

  2. On the Daubechies-based wavelet differentiation matrix (United States)

    Jameson, Leland


    The differentiation matrix for a Daubechies-based wavelet basis is constructed and superconvergence is proven. That is, it will be proven that under the assumption of periodic boundary conditions that the differentiation matrix is accurate of order 2M, even though the approximation subspace can represent exactly only polynomials up to degree M-1, where M is the number of vanishing moments of the associated wavelet. It is illustrated that Daubechies-based wavelet methods are equivalent to finite difference methods with grid refinement in regions of the domain where small-scale structure is present.

  3. EEG Artifact Removal Using a Wavelet Neural Network (United States)

    Nguyen, Hoang-Anh T.; Musson, John; Li, Jiang; McKenzie, Frederick; Zhang, Guangfan; Xu, Roger; Richey, Carl; Schnell, Tom


    !n this paper we developed a wavelet neural network. (WNN) algorithm for Electroencephalogram (EEG) artifact removal without electrooculographic (EOG) recordings. The algorithm combines the universal approximation characteristics of neural network and the time/frequency property of wavelet. We. compared the WNN algorithm with .the ICA technique ,and a wavelet thresholding method, which was realized by using the Stein's unbiased risk estimate (SURE) with an adaptive gradient-based optimal threshold. Experimental results on a driving test data set show that WNN can remove EEG artifacts effectively without diminishing useful EEG information even for very noisy data.

  4. Wavelets an elementary treatment of theory and applications

    CERN Document Server

    Koornwinder, T H


    Nowadays, some knowledge of wavelets is almost mandatory for mathematicians, physicists and electrical engineers. The emphasis in this volume, based on an intensive course on Wavelets given at CWI, Amsterdam, is on the affine case. The first part presents a concise introduction of the underlying theory to the uninitiated reader. The second part gives applications in various areas. Some of the contributions here are a fresh exposition of earlier work by others, while other papers contain new results by the authors. The areas are so diverse as seismic processing, quadrature formulae, and wavelet

  5. Identification Method of Mud Shale Fractures Base on Wavelet Transform (United States)

    Xia, Weixu; Lai, Fuqiang; Luo, Han


    In recent years, inspired by seismic analysis technology, a new method for analysing mud shale fractures oil and gas reservoirs by logging properties has emerged. By extracting the high frequency attribute of the wavelet transform in the logging attribute, the formation information hidden in the logging signal is extracted, identified the fractures that are not recognized by conventional logging and in the identified fracture segment to show the “cycle jump”, “high value”, “spike” and other response effect is more obvious. Finally formed a complete wavelet denoising method and wavelet high frequency identification fracture method.

  6. Wavelets for computer-aided breast cancer diagnosis (United States)

    Myers, Lemuel R., Jr.; Kocur, Catherine M.; Rogers, Steven K.; Eisenbies, Chris; Hoffmeister, Jeffrey W.


    More than 50 million women over the age of 40 are currently at risk for breast cancer in the United States. Computer-aided diagnosis, used as a `second opinion' to radiologists, will aid in decreasing the number of false readings of mammograms. A novel feature extraction method is presented that provides increased classification power. Wavelets, previously only exploited for their segmentation benefits, are explored as features for classification. Daubechies4, Daubechies20, and biorthogonal wavelets are each investigated. Applied to 94 difficult-to- diagnose digitized microcalcification cases, performance is 74 percent correct classifications. Feature selection techniques are presented which further improve wavelet classification performance to 88 percent correct classification.

  7. A First Course in Wavelets with Fourier Analysis

    CERN Document Server

    Boggess, Albert


    A comprehensive, self-contained treatment of Fourier analysis and wavelets-now in a new edition Through expansive coverage and easy-to-follow explanations, A First Course in Wavelets with Fourier Analysis, Second Edition provides a self-contained mathematical treatment of Fourier analysis and wavelets, while uniquely presenting signal analysis applications and problems. Essential and fundamental ideas are presented in an effort to make the book accessible to a broad audience, and, in addition, their applications to signal processing are kept at an elementary level. The book begins with an intr

  8. EEG seizure identification by using optimized wavelet decomposition. (United States)

    Pinzon-Morales, R D; Orozco-Gutierrez, A; Castellanos-Dominguez, G


    A methodology for wavelet synthesis based on lifting scheme and genetic algorithms is presented. Often, the wavelet synthesis is addressed to solve the problem of choosing properly a wavelet function from an existing library, but which may be not specially designed to the application in hand. The task under consideration is the identification of epileptic seizures over electroencephalogram recordings. Although basic classifiers are employed, results rendered that the proposed methodology is successful in the considered study achieving similar classification rates that had been reported in literature.

  9. The uncompromising leader. (United States)

    Eisenstat, Russell A; Beer, Michael; Foote, Nathaniel; Fredberg, Tobias; Norrgren, Flemming


    Managing the tension between performance and people is at the heart of the CEO's job. But CEOs under fierce pressure from capital markets often focus solely on the shareholder, which can lead to employee disenchantment. Others put so much stock in their firms' heritage that they don't notice as their organizations slide into complacency. Some leaders, though, manage to avoid those traps and create high-commitment, high-performance (HCHP) companies. The authors' in-depth research of HCHP CEOs reveals several shared traits: These CEOs earn the trust of their organizations through their openness to the unvarnished truth. They are deeply engaged with their people, and their exchanges are direct and personal. They mobilize employees around a focused agenda, concentrating on only one or two initiatives. And they work to build collective leadership capabilities. These leaders also forge an emotionally resonant shared purpose across their companies. That consists of a three-part promise: The company will help employees build a better world and deliver performance they can be proud of, and will provide an environment in which they can grow. HCHP CEOs approach finding a firm's moral and strategic center in a competitive market as a calling, not an engineering problem. They drive their firms to be strongly market focused while at the same time reinforcing their firms' core values. They are committed to short-term performance while also investing in long-term leadership and organizational capabilities. By refusing to compromise on any of these terms, they build great companies.

  10. RFI Mitigation in Microwave Radiometry Using Wavelets

    Directory of Open Access Journals (Sweden)

    José Miguel Tarongí


    Full Text Available The performance of microwave radiometers can be seriously degraded by the presence of radio-frequency interference (RFI. Spurious signals and harmonics from lower frequency bands, spread-spectrum signals overlapping the “protected” band of operation, or out-of-band emissions not properly rejected by the pre-detection filters due to the finite rejection modify the detected power and the estimated antenna temperature from which the geophysical parameters will be retrieved. In recent years, techniques to detect the presence of RFI have been developed. They include time- and/or frequency domain analyses, or statistical analysis of the received signal which, in the absence of RFI, must be a zero-mean Gaussian process. Current mitigation techniques are mostly based on blanking in the time and/or frequency domains where RFI has been detected. However, in some geographical areas, RFI is so persistent in time that is not possible to acquire RFI-free radiometric data. In other applications such as sea surface salinity retrieval, where the sensitivity of the brightness temperature to salinity is weak, small amounts of RFI are also very difficult to detect and mitigate. In this work a wavelet-based technique is proposed to mitigate RFI (cancel RFI as much as possible. The interfering signal is estimated by using the powerful denoising capabilities of the wavelet transform. The estimated RFI signal is then subtracted from the received signal and a “cleaned” noise signal is obtained, from which the power is estimated later. The algorithm performance as a function of the threshold type, and the threshold selection method, the decomposition level, the wavelet type and the interferenceto-noise ratio is presented. Computational requirements are evaluated in terms of quantization levels, number of operations, memory requirements (sequence length. Even though they are high for today’s technology, the algorithms presented can be applied to recorded data

  11. Negative Outgroup Leader Actions Increase Liking for Ingroup Leaders: An Experimental Test of Intergroup Leader-Enhancement Effects


    Pittinsky, Todd L.; Welle, Brian


    Abstract We conducted two studies to examine how information about outgroup leaders' negative actions affect ingroup leader favorability ratings. Study 1 found that people hold more favorable attitudes toward ingroup leaders (i.e. their own nation's leaders) when learning of negative actions of outgroup leaders (i.e. another nation's leaders). Study 2 replicated the finding, examining social identity strength as a moderator of this effect, and found that participants with strong na...

  12. WaveletQuant, an improved quantification software based on wavelet signal threshold de-noising for labeled quantitative proteomic analysis

    Directory of Open Access Journals (Sweden)

    Li Song


    Full Text Available Abstract Background Quantitative proteomics technologies have been developed to comprehensively identify and quantify proteins in two or more complex samples. Quantitative proteomics based on differential stable isotope labeling is one of the proteomics quantification technologies. Mass spectrometric data generated for peptide quantification are often noisy, and peak detection and definition require various smoothing filters to remove noise in order to achieve accurate peptide quantification. Many traditional smoothing filters, such as the moving average filter, Savitzky-Golay filter and Gaussian filter, have been used to reduce noise in MS peaks. However, limitations of these filtering approaches often result in inaccurate peptide quantification. Here we present the WaveletQuant program, based on wavelet theory, for better or alternative MS-based proteomic quantification. Results We developed a novel discrete wavelet transform (DWT and a 'Spatial Adaptive Algorithm' to remove noise and to identify true peaks. We programmed and compiled WaveletQuant using Visual C++ 2005 Express Edition. We then incorporated the WaveletQuant program in the Trans-Proteomic Pipeline (TPP, a commonly used open source proteomics analysis pipeline. Conclusions We showed that WaveletQuant was able to quantify more proteins and to quantify them more accurately than the ASAPRatio, a program that performs quantification in the TPP pipeline, first using known mixed ratios of yeast extracts and then using a data set from ovarian cancer cell lysates. The program and its documentation can be downloaded from our website at

  13. Wavelet bicoherence: A new turbulence analysis tool

    Energy Technology Data Exchange (ETDEWEB)

    van Milligen, B.P.; Sanchez, E.; Estrada, T.; Hidalgo, C.; Branas, B. [Asociacion EURATOM-CIEMAT, Madrid (Spain); Carreras, B. [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Garcia, L. [Universidad Carlos III, Madrid (Spain)


    A recently introduced tool for the analysis of turbulence, wavelet bicoherence [van Milligen, Hidalgo, and Sanchez, Phys. Rev. Lett. {bold 16}, 395 (1995)], is investigated. It is capable of detecting phase coupling---nonlinear interactions of the lowest (quadratic) order---with time resolution. To demonstrate its potential, it is applied to numerical models of chaos and turbulence and to real measurements. It detected the coupling interaction between two coupled van der Pol oscillators. When applied to a model of drift wave turbulence relevant to plasma physics, it detected a highly localized coherent structure. Analyzing reflectometry measurements made in fusion plasmas, it detected temporal intermittency and a strong increase in nonlinear phase coupling coinciding with the L/H (low-to-high confinement mode) transition. {copyright} {ital 1995} {ital American} {ital Institute} {ital of} {ital Physics}.

  14. Fast wavelet based sparse approximate inverse preconditioner

    Energy Technology Data Exchange (ETDEWEB)

    Wan, W.L. [Univ. of California, Los Angeles, CA (United States)


    Incomplete LU factorization is a robust preconditioner for both general and PDE problems but unfortunately not easy to parallelize. Recent study of Huckle and Grote and Chow and Saad showed that sparse approximate inverse could be a potential alternative while readily parallelizable. However, for special class of matrix A that comes from elliptic PDE problems, their preconditioners are not optimal in the sense that independent of mesh size. A reason may be that no good sparse approximate inverse exists for the dense inverse matrix. Our observation is that for this kind of matrices, its inverse entries typically have piecewise smooth changes. We can take advantage of this fact and use wavelet compression techniques to construct a better sparse approximate inverse preconditioner. We shall show numerically that our approach is effective for this kind of matrices.

  15. Network Anomaly Detection Based on Wavelet Analysis

    Directory of Open Access Journals (Sweden)

    Ali A. Ghorbani


    Full Text Available Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

  16. Market turning points forecasting using wavelet analysis (United States)

    Bai, Limiao; Yan, Sen; Zheng, Xiaolian; Chen, Ben M.


    Based on the system adaptation framework we previously proposed, a frequency domain based model is developed in this paper to forecast the major turning points of stock markets. This system adaptation framework has its internal model and adaptive filter to capture the slow and fast dynamics of the market, respectively. The residue of the internal model is found to contain rich information about the market cycles. In order to extract and restore its informative frequency components, we use wavelet multi-resolution analysis with time-varying parameters to decompose this internal residue. An empirical index is then proposed based on the recovered signals to forecast the market turning points. This index is successfully applied to US, UK and China markets, where all major turning points are well forecasted.

  17. Structural Vibration Monitoring Using Cumulative Spectral Analysis

    Directory of Open Access Journals (Sweden)

    Satoru Goto


    Full Text Available This paper describes a resonance decay estimation for structural health monitoring in the presence of nonstationary vibrations. In structural health monitoring, the structure's frequency response and resonant decay characteristics are very important for understanding how the structure changes. Cumulative spectral analysis (CSA estimates the frequency decay by using the impulse response. However, measuring the impulse response of buildings is impractical due to the need to shake the building itself. In a previous study, we reported on system damping monitoring using cumulative harmonic analysis (CHA, which is based on CSA. The current study describes scale model experiments on estimating the hidden resonance decay under non-stationary noise conditions by using CSA for structural condition monitoring.

  18. Inertial fusion by magnetically transmitted axial cumulation

    Energy Technology Data Exchange (ETDEWEB)

    Eliezer, S.; Martinez-Val, J.; Piera, M. [Institute of Nuclear Fusion, Madrid (Spain); Vorobeichik, I.; Henis, Z. [Soreq Nuclear Research Centre, (Israel); Piera, M. [ETSII, UNED, Madrid (Spain)


    An analytical and numerical study is presented on the physics of Z-pinch implosions including magnetic fields to transmit the kinetic energy from the imploding shell to an axially placed filament. The shell kinetic energy can be built-up along a long pinch phase and a fraction of this energy could be transmitted to the filament in a much shorter interaction phase. Although initial estimates are very positive for energy cumulation in the filament, a deeper analysis shows that compressibility effects dominate the space-time evolution of the filament, and the energy cumulation level remains moderate. The scheme could be used to trigger fusion ignition in a direct-drive scenario (without radiation hohlraums) but driver specifications to get it are very demanding. (authors)

  19. Is cumulated pyrethroid exposure associated with prediabetes?

    DEFF Research Database (Denmark)

    Hansen, Martin Rune; Jørs, Erik; Lander, Flemming


    Pyrethroids are a class of insecticides used widely for vector control programs. Acute pyrethroid poisoning is rare, but well documented, whereas effects of cumulative exposure are insufficiently described, including possible negative effect on glucose regulation. The objective of this study...... was to investigate an association between exposure to pyrethroids and abnormal glucose regulation (prediabetes or diabetes). A cross-sectional study was performed among 116 pesticide sprayers from public vector control programs in Bolivia and 92 nonexposed controls. Pesticide exposure (duration, intensity...... pyrethroids, a significant positive trend was observed between cumulative pesticide exposure (total number of hours sprayed) and adjusted OR of abnormal glucose regulation, with OR 14.7 [0.9-235] in the third exposure quintile. The study found a severely increased prevalence of prediabetes among Bolivian...

  20. Is cumulated pyrethroid exposure associated with prediabetes?

    DEFF Research Database (Denmark)

    Hansen, Martin Rune; Jørs, Erik; Lander, Flemming


    pyrethroids, a significant positive trend was observed between cumulative pesticide exposure (total number of hours sprayed) and adjusted OR of abnormal glucose regulation, with OR 14.7 [0.9-235] in the third exposure quintile. The study found a severely increased prevalence of prediabetes among Bolivian......Pyrethroids are a class of insecticides used widely for vector control programs. Acute pyrethroid poisoning is rare, but well documented, whereas effects of cumulative exposure are insufficiently described, including possible negative effect on glucose regulation. The objective of this study...... was to investigate an association between exposure to pyrethroids and abnormal glucose regulation (prediabetes or diabetes). A cross-sectional study was performed among 116 pesticide sprayers from public vector control programs in Bolivia and 92 nonexposed controls. Pesticide exposure (duration, intensity...

  1. Summarizing differences in cumulative incidence functions. (United States)

    Zhang, Mei-Jie; Fine, Jason


    The cumulative incidence function is widely reported in competing risks studies, with group differences assessed by an extension of the log-rank test. However, simple, interpretable summaries of group differences are not available. An adaptation of the proportional hazards model to the cumulative incidence function is often employed, but the interpretation of the hazard ratio may be somewhat awkward, unlike the usual survival set-up. We propose nonparametric inferences for general summary measures, which may be time-varying, and for time-averaged versions of the measures. Theoretical justification is provided using counting process techniques. A real data example illustrates the practical utility of the methods. Copyright 2008 John Wiley & Sons, Ltd.

  2. Avoiding Program-Induced Cumulative Overload (PICO). (United States)

    Orr, Robin; Knapik, Joseph J; Pope, Rodney


    This article defines the concept of program-induced cumulative overload (PICO), provides examples, and advises ways to mitigate the adverse effects. PICO is the excessive cumulative physical workload that can be imparted to military personnel by a military training program with an embedded physical training component. PICO can be acute (accumulating within a single day) or chronic (accumulating across the entirety of the program) and results in adverse outcomes for affected personnel, including detrimental fatigue, performance degradation, injuries, or illness. Strategies to mitigate PICO include focusing administration and logistic practices during the development and ongoing management of a trainee program and implementing known musculoskeletal injury prevention strategies. More training is not always better, and trainers need to consider the total amount of physical activity that military personnel experience across both operational training and physical training if PICO is to be mitigated. 2016.

  3. Complexity and demographic explanations of cumulative culture. (United States)

    Querbes, Adrien; Vaesen, Krist; Houkes, Wybo


    Formal models have linked prehistoric and historical instances of technological change (e.g., the Upper Paleolithic transition, cultural loss in Holocene Tasmania, scientific progress since the late nineteenth century) to demographic change. According to these models, cumulation of technological complexity is inhibited by decreasing--while favoured by increasing--population levels. Here we show that these findings are contingent on how complexity is defined: demography plays a much more limited role in sustaining cumulative culture in case formal models deploy Herbert Simon's definition of complexity rather than the particular definitions of complexity hitherto assumed. Given that currently available empirical evidence doesn't afford discriminating proper from improper definitions of complexity, our robustness analyses put into question the force of recent demographic explanations of particular episodes of cultural change.

  4. Complexity and demographic explanations of cumulative culture.

    Directory of Open Access Journals (Sweden)

    Adrien Querbes

    Full Text Available Formal models have linked prehistoric and historical instances of technological change (e.g., the Upper Paleolithic transition, cultural loss in Holocene Tasmania, scientific progress since the late nineteenth century to demographic change. According to these models, cumulation of technological complexity is inhibited by decreasing--while favoured by increasing--population levels. Here we show that these findings are contingent on how complexity is defined: demography plays a much more limited role in sustaining cumulative culture in case formal models deploy Herbert Simon's definition of complexity rather than the particular definitions of complexity hitherto assumed. Given that currently available empirical evidence doesn't afford discriminating proper from improper definitions of complexity, our robustness analyses put into question the force of recent demographic explanations of particular episodes of cultural change.

  5. Senior Leader Mentoring: Its Role in Leader Development Doctrine (United States)


    employ mentors."’ 21 It defined a mentor as a leader who develops "an individual by being for that individual a role model , teacher, coach, advisor, and...Shapiro, E. C., F. P. Hazeltine, and M. P. Rowe. "Moving Up: Role Models , Mentors, and the Patron System." Sloan Management Review (Spring 1978): 51-58...AD-A284 464 3 June 1994 Master’s Thesis, 2 Aug 93-3 Jun 94 Senior Leader Mentoring: Its Role in Leader Development Doctrine Major Mark L. Ritter, USA

  6. Sikap Kerja Duduk Terhadap Cumulative Trauma Disorder


    Sugiharto, -; Rahmawati, Yulita


    Permasalahan yang diteliti adalah adakah hubungan antara sikap kerja duduk dengan kejadian Cumulative Trauma Disorder (CTD) pada pekerja bagian pengamplasan di PT. Geromar Jepara. Tujuan yang ingin dicapai adalah untuk mengetahui hubungan antara sikap kerja duduk dengan kejadian CTD pada pekerja bagian pengamplasan. Metode penelitian ini bersifat explanatory dengan menggunakan pendekatan belah lintang. Populasi dalam penelitian ini adalah pekerja bagian pengamplasan sebanyak 30 orang. Teknik ...

  7. Fuzzy set theory for cumulative trauma prediction


    Fonseca, Daniel J.; Merritt, Thomas W.; Moynihan, Gary P.


    A widely used fuzzy reasoning algorithm was modified and implemented via an expert system to assess the potential risk of employee repetitive strain injury in the workplace. This fuzzy relational model, known as the Priority First Cover Algorithm (PFC), was adapted to describe the relationship between 12 cumulative trauma disorders (CTDs) of the upper extremity, and 29 identified risk factors. The algorithm, which finds a suboptimal subset from a group of variables based on the criterion of...

  8. Cumulative Effect of Depression on Dementia Risk


    Olazarán, J.; Trincado, R.; Bermejo-Pareja, F.


    Objective. To analyze a potential cumulative effect of life-time depression on dementia and Alzheimer’s disease (AD), with control of vascular factors (VFs). Methods. This study was a subanalysis of the Neurological Disorders in Central Spain (NEDICES) study. Past and present depression, VFs, dementia status, and dementia due to AD were documented at study inception. Dementia status was also documented after three years. Four groups were created according to baseline data: never depression (n...

  9. Complexity and Demographic Explanations of Cumulative Culture


    Adrien Querbes; Krist Vaesen; Wybo Houkes


    Formal models have linked prehistoric and historical instances of technological change (e.g., the Upper Paleolithic transition, cultural loss in Holocene Tasmania, scientific progress since the late nineteenth century) to demographic change. According to these models, cumulation of technological complexity is inhibited by decreasing--while favoured by increasing--population levels. Here we show that these findings are contingent on how complexity is defined: demography plays a much more limit...

  10. Expansive Soil Crack Depth under Cumulative Damage

    Directory of Open Access Journals (Sweden)

    Bei-xiao Shi


    Full Text Available The crack developing depth is a key problem to slope stability of the expansive soil and its project governance and the crack appears under the roles of dry-wet cycle and gradually develops. It is believed from the analysis that, because of its own cohesion, the expansive soil will have a certain amount of deformation under pulling stress but without cracks. The soil body will crack only when the deformation exceeds the ultimate tensile strain that causes cracks. And it is also believed that, due to the combined effect of various environmental factors, particularly changes of the internal water content, the inherent basic physical properties of expansive soil are weakened, and irreversible cumulative damages are eventually formed, resulting in the development of expansive soil cracks in depth. Starting from the perspective of volumetric strain that is caused by water loss, considering the influences of water loss rate and dry-wet cycle on crack developing depth, the crack developing depth calculation model which considers the water loss rate and the cumulative damages is established. Both the proposal of water loss rate and the application of cumulative damage theory to the expansive soil crack development problems try to avoid difficulties in matrix suction measurement, which will surely play a good role in promoting and improving the research of unsaturated expansive soil.

  11. Higher order cumulants in colorless partonic plasma

    Energy Technology Data Exchange (ETDEWEB)

    Cherif, S. [Sciences and Technologies Department, University of Ghardaia, Ghardaia, Algiers (Algeria); Laboratoire de Physique et de Mathématiques Appliquées (LPMA), ENS-Kouba (Bachir El-Ibrahimi), Algiers (Algeria); Ahmed, M. A. A. [Department of Physics, College of Science, Taibah University Al-Madinah Al-Mounawwarah KSA (Saudi Arabia); Department of Physics, Taiz University in Turba, Taiz (Yemen); Laboratoire de Physique et de Mathématiques Appliquées (LPMA), ENS-Kouba (Bachir El-Ibrahimi), Algiers (Algeria); Ladrem, M., E-mail: [Department of Physics, College of Science, Taibah University Al-Madinah Al-Mounawwarah KSA (Saudi Arabia); Laboratoire de Physique et de Mathématiques Appliquées (LPMA), ENS-Kouba (Bachir El-Ibrahimi), Algiers (Algeria)


    Any physical system considered to study the QCD deconfinement phase transition certainly has a finite volume, so the finite size effects are inevitably present. This renders the location of the phase transition and the determination of its order as an extremely difficult task, even in the simplest known cases. In order to identify and locate the colorless QCD deconfinement transition point in finite volume T{sub 0}(V), a new approach based on the finite-size cumulant expansion of the order parameter and the ℒ{sub m,n}-Method is used. We have shown that both cumulants of higher order and their ratios, associated to the thermodynamical fluctuations of the order parameter, in QCD deconfinement phase transition behave in a particular enough way revealing pronounced oscillations in the transition region. The sign structure and the oscillatory behavior of these in the vicinity of the deconfinement phase transition point might be a sensitive probe and may allow one to elucidate their relation to the QCD phase transition point. In the context of our model, we have shown that the finite volume transition point is always associated to the appearance of a particular point in whole higher order cumulants under consideration.

  12. A Secret Image Sharing Method Using Integer Wavelet Transform

    Directory of Open Access Journals (Sweden)

    Li Ching-Chung


    Full Text Available A new image sharing method, based on the reversible integer-to-integer (ITI wavelet transform and Shamir's threshold scheme is presented, that provides highly compact shadows for real-time progressive transmission. This method, working in the wavelet domain, processes the transform coefficients in each subband, divides each of the resulting combination coefficients into shadows, and allows recovery of the complete secret image by using any or more shadows . We take advantages of properties of the wavelet transform multiresolution representation, such as coefficient magnitude decay and excellent energy compaction, to design combination procedures for the transform coefficients and processing sequences in wavelet subbands such that small shadows for real-time progressive transmission are obtained. Experimental results demonstrate that the proposed method yields small shadow images and has the capabilities of real-time progressive transmission and perfect reconstruction of secret images.

  13. A simple output voltage control scheme for single phase wavelet ...

    African Journals Online (AJOL)

    -phase pulse-width-modulated (PWM) dc-ac inverter. ... function, derived using wavelet theory, can be used to generate the switching signal as well as to model the inverter output which is not possible with other modulation techniques.

  14. Tree-structured wavelet transform signature for classification of melanoma (United States)

    Patwardhan, Sachin V.; Dhawan, Atam P.; Relue, Patricia A.


    The purpose of this work is to evaluate the use of a wavelet transform based tree structure in classifying skin lesion images in to melanoma and dysplastic nevus based on the spatial/frequency information. The classification is done using the wavelet transform tree structure analysis. Development of the tree structure in the proposed method uses energy ratio thresholds obtained from a statistical analysis of the coefficients in the wavelet domain. The method is used to obtain a tree structure signature of melanoma and dysplastic nevus, which is then used to classify the data set in to the two classes. Images are classified by using a semantic comparison of the wavelet transform tree structure signatures. Results show that the proposed method is effective and simple for classification based on spatial/frequency information, which also includes the textural information.

  15. Doppler radar fall activity detection using the wavelet transform. (United States)

    Su, Bo Yu; Ho, K C; Rantz, Marilyn J; Skubic, Marjorie


    We propose in this paper the use of Wavelet transform (WT) to detect human falls using a ceiling mounted Doppler range control radar. The radar senses any motions from falls as well as nonfalls due to the Doppler effect. The WT is very effective in distinguishing the falls from other activities, making it a promising technique for radar fall detection in nonobtrusive inhome elder care applications. The proposed radar fall detector consists of two stages. The prescreen stage uses the coefficients of wavelet decomposition at a given scale to identify the time locations in which fall activities may have occurred. The classification stage extracts the time-frequency content from the wavelet coefficients at many scales to form a feature vector for fall versus nonfall classification. The selection of different wavelet functions is examined to achieve better performance. Experimental results using the data from the laboratory and real inhome environments validate the promising and robust performance of the proposed detector.

  16. Wavelet Neural Network Model for Yield Spread Forecasting

    Directory of Open Access Journals (Sweden)

    Firdous Ahmad Shah


    Full Text Available In this study, a hybrid method based on coupling discrete wavelet transforms (DWTs and artificial neural network (ANN for yield spread forecasting is proposed. The discrete wavelet transform (DWT using five different wavelet families is applied to decompose the five different yield spreads constructed at shorter end, longer end, and policy relevant area of the yield curve to eliminate noise from them. The wavelet coefficients are then used as inputs into Levenberg-Marquardt (LM ANN models to forecast the predictive power of each of these spreads for output growth. We find that the yield spreads constructed at the shorter end and policy relevant areas of the yield curve have a better predictive power to forecast the output growth, whereas the yield spreads, which are constructed at the longer end of the yield curve do not seem to have predictive information for output growth. These results provide the robustness to the earlier results.

  17. Optimization and Assessment of Wavelet Packet Decompositions with Evolutionary Computation

    Directory of Open Access Journals (Sweden)

    Schell Thomas


    Full Text Available In image compression, the wavelet transformation is a state-of-the-art component. Recently, wavelet packet decomposition has received quite an interest. A popular approach for wavelet packet decomposition is the near-best-basis algorithm using nonadditive cost functions. In contrast to additive cost functions, the wavelet packet decomposition of the near-best-basis algorithm is only suboptimal. We apply methods from the field of evolutionary computation (EC to test the quality of the near-best-basis results. We observe a phenomenon: the results of the near-best-basis algorithm are inferior in terms of cost-function optimization but are superior in terms of rate/distortion performance compared to EC methods.


    Energy Technology Data Exchange (ETDEWEB)



    In this paper the authors consider applications of methods from wavelet analysis to nonlinear dynamical problems related to accelerator physics. In this approach they take into account underlying algebraical, geometrical and topological structures of corresponding problems.


    Directory of Open Access Journals (Sweden)

    Endina Putri Purwandari


    Full Text Available Image splicing is a form of digital image manipulation by combining two or more image into a new image. The application was developed through a passive approach using demosaicking and wavelet transformation method. This research purposed a method to implement the demosaicking and wavelet transform for digital image forgery detection with a passive approach. This research shows that (1 demosaicking can be used as a comparison image in forgery detection; (2 the application of demosaicking and wavelet transformation can improve the quality of the input image (3 demosaicking and wavelet algorithm are able to estimate whether the input image is real or fake image with a passive approach and estimate the manipulation area from the input image.

  20. Remembering the Leaders of China. (United States)

    Fu, Mingchen; Xue, Yan; DeSoto, K Andrew; Yuan, Ti-Fei


    In two studies, we examined Chinese students' memory for the names of the leaders of China. In Study 1, subjects were cued with the names of periods from China's history. Subjects listed as many leaders as possible from each period and put them in the correct ordinal position when they could (see Roediger and DeSoto, 2014). Results showed that within each period, a primacy effect and sometimes a recency effect emerged. Moreover, the average recall probability for leaders within a specific period was a function of the ordinal position of the period. In Study 2, we asked another group of subjects to identify the sources through which they were able to recall each leader. We found that most subjects remembered leaders due to class and coursework. We also found a relation between a leader's recall probability and the amount of information available on that leader on the Internet. Our findings further imply that the serial position function captures the form of collective memory.

  1. A short introduction to frames, Gabor systems, and wavelet systems

    DEFF Research Database (Denmark)

    Christensen, Ole


    In this article we present a short survey of frame theory in Hilbert spaces. We discuss Gabor frames and wavelet frames, and a recent transform that allows to move results from one setting into the other and vice versa.......In this article we present a short survey of frame theory in Hilbert spaces. We discuss Gabor frames and wavelet frames, and a recent transform that allows to move results from one setting into the other and vice versa....

  2. Wavelet based methods for improved wind profiler signal processing

    Directory of Open Access Journals (Sweden)

    V. Lehmann


    Full Text Available In this paper, we apply wavelet thresholding for removing automatically ground and intermittent clutter (airplane echoes from wind profiler radar data. Using the concept of discrete multi-resolution analysis and non-parametric estimation theory, we develop wavelet domain thresholding rules, which allow us to identify the coefficients relevant for clutter and to suppress them in order to obtain filtered reconstructions.Key words. Meteorology and atmospheric dynamics (instruments and techniques – Radio science (remote sensing; signal processing

  3. Controlled wavelet domain sparsity for x-ray tomography (United States)

    Purisha, Zenith; Rimpeläinen, Juho; Bubba, Tatiana; Siltanen, Samuli


    Tomographic reconstruction is an ill-posed inverse problem that calls for regularization. One possibility is to require sparsity of the unknown in an orthonormal wavelet basis. This, in turn, can be achieved by variational regularization, where the penalty term is the sum of the absolute values of the wavelet coefficients. The primal-dual fixed point algorithm showed that the minimizer of the variational regularization functional can be computed iteratively using a soft-thresholding operation. Choosing the soft-thresholding parameter \

  4. Music Tune Restoration Based on a Mother Wavelet Construction (United States)

    Fadeev, A. S.; Konovalov, V. I.; Butakova, T. I.; Sobetsky, A. V.


    It is offered to use the mother wavelet function obtained from the local part of an analyzed music signal. Requirements for the constructed function are proposed and the implementation technique and its properties are described. The suggested approach allows construction of mother wavelet families with specified identifying properties. Consequently, this makes possible to identify the basic signal variations of complex music signals including local time-frequency characteristics of the basic one.

  5. An Empirical Analysis of Dynamic Multiscale Hedging using Wavelet Decomposition


    Conlon, Thomas; Cotter, John


    This paper investigates the hedging effectiveness of a dynamic moving window OLS hedging model, formed using wavelet decomposed time-series. The wavelet transform is applied to calculate the appropriate dynamic minimum-variance hedge ratio for various hedging horizons for a number of assets. The effectiveness of the dynamic multiscale hedging strategy is then tested, both in- and out-of-sample, using standard variance reduction and expanded to include a downside risk metric, the time horizon ...

  6. Sparse imaging of cortical electrical current densities via wavelet transforms (United States)

    Liao, Ke; Zhu, Min; Ding, Lei; Valette, Sébastien; Zhang, Wenbo; Dickens, Deanna


    While the cerebral cortex in the human brain is of functional importance, functions defined on this structure are difficult to analyze spatially due to its highly convoluted irregular geometry. This study developed a novel L1-norm regularization method using a newly proposed multi-resolution face-based wavelet method to estimate cortical electrical activities in electroencephalography (EEG) and magnetoencephalography (MEG) inverse problems. The proposed wavelets were developed based on multi-resolution models built from irregular cortical surface meshes, which were realized in this study too. The multi-resolution wavelet analysis was used to seek sparse representation of cortical current densities in transformed domains, which was expected due to the compressibility of wavelets, and evaluated using Monte Carlo simulations. The EEG/MEG inverse problems were solved with the use of the novel L1-norm regularization method exploring the sparseness in the wavelet domain. The inverse solutions obtained from the new method using MEG data were evaluated by Monte Carlo simulations too. The present results indicated that cortical current densities could be efficiently compressed using the proposed face-based wavelet method, which exhibited better performance than the vertex-based wavelet method. In both simulations and auditory experimental data analysis, the proposed L1-norm regularization method showed better source detection accuracy and less estimation errors than other two classic methods, i.e. weighted minimum norm (wMNE) and cortical low-resolution electromagnetic tomography (cLORETA). This study suggests that the L1-norm regularization method with the use of face-based wavelets is a promising tool for studying functional activations of the human brain.

  7. Photoionization of a Statistic Atom by Ultrashort Wavelet Pulses (United States)

    Astapenko, V. A.; Ionichev, E. Yu.; Yakovets, A. V.


    Photoionization of atoms by ultrashort electromagnetic wavelet pulses is investigated within the framework of a statistical model. Integral representations of the total probability of atom ionization are obtained within the time over which the pulse acts. It is shown that the dependence of this probability on the pulse duration in the considered case is bell-shaped. The wavelet pulse duration at which the maximum photoionization probability is reached is determined for different charges of atomic nuclii.

  8. Journal Afrika Statistika ISSN 0852-0305 Nonlinear wavelet ...

    African Journals Online (AJOL)

    introduce a new nonlinear wavelet-based estimator of the regression function in the right censorship model. ... wavelet estimator of the density function has first been considered for complete data; see,. Hall and Patil ..... 0 = x0 < x1 < ··· < xN < xN+1 = 1 such that the first r derivatives of l and h exist and are bounded and ...

  9. Big data extraction with adaptive wavelet analysis (Presentation Video) (United States)

    Qu, Hongya; Chen, Genda; Ni, Yiqing


    Nondestructive evaluation and sensing technology have been increasingly applied to characterize material properties and detect local damage in structures. More often than not, they generate images or data strings that are difficult to see any physical features without novel data extraction techniques. In the literature, popular data analysis techniques include Short-time Fourier Transform, Wavelet Transform, and Hilbert Transform for time efficiency and adaptive recognition. In this study, a new data analysis technique is proposed and developed by introducing an adaptive central frequency of the continuous Morlet wavelet transform so that both high frequency and time resolution can be maintained in a time-frequency window of interest. The new analysis technique is referred to as Adaptive Wavelet Analysis (AWA). This paper will be organized in several sections. In the first section, finite time-frequency resolution limitations in the traditional wavelet transform are introduced. Such limitations would greatly distort the transformed signals with a significant frequency variation with time. In the second section, Short Time Wavelet Transform (STWT), similar to Short Time Fourier Transform (STFT), is defined and developed to overcome such shortcoming of the traditional wavelet transform. In the third section, by utilizing the STWT and a time-variant central frequency of the Morlet wavelet, AWA can adapt the time-frequency resolution requirement to the signal variation over time. Finally, the advantage of the proposed AWA is demonstrated in Section 4 with a ground penetrating radar (GPR) image from a bridge deck, an analytical chirp signal with a large range sinusoidal frequency change over time, the train-induced acceleration responses of the Tsing-Ma Suspension Bridge in Hong Kong, China. The performance of the proposed AWA will be compared with the STFT and traditional wavelet transform.

  10. Optical wavelet de-noising applied in multi-span nonlinear fiber links (United States)

    Shao, Qunfeng; Zhang, Xiaoping; Qi, Xiaoqiong; Li, Hu; Xiang, Lian


    In this work, optical wavelet de-noising with several different types of wavelets such as db4, coif4 and dmey wavelet was applied at the end of the 40 Gbit/s multi-span intensity-modulated fiber communication systems. The results of numerical simulations carried out in different fiber links demonstrated that the optical wavelet de-noising method could remove the random amplitude fluctuation induced by the interaction of EDFA's ASE noise and optical fiber's dispersion and nonlinearity. The SNR and BER curves of the optical bit sequence without and with optical wavelet de-noising in dispersion compensation fiber link were plotted to show the effectiveness of the wavelet de-noising in the fiber-optic communication systems and wavelet de-noising with demy wavelet can achieve better result than with other type wavelet.

  11. Leaders, managers, and employee care. (United States)

    Stewart, Della W


    With the economic and market changes currently taking place, organizations cannot survive or prosper without quality employees. Key to employee loyalty, performance, and retention is the relationship between the leader, manager, and employee. Leaders are visionaries who make sure that the right things are done for the organization. Managers are in a position to make sure that things are done right within the organization. There are traits and qualities that good leaders and managers must possess to ensure organizational success. Displaying these characteristics will ensure that employees are taken care of, which will benefit both the employees and the organization.

  12. Wavelet analysis for ground penetrating radar applications: a case study (United States)

    Javadi, Mehdi; Ghasemzadeh, Hasan


    Noises may significantly disturb ground penetrating radar (GPR) signals, therefore, filtering undesired information using wavelet analysis would be challenging, despite the fact that several methods have been presented. Noises are gathered by probe, particularly from deep locations, and they may conceal reflections, suffering from small altitudes, because of signal attenuation. Multiple engineering fields need data analysis to distinguish valued material, based on information obtained by underground observations. Using wavelets as one of the useful methods for analyzing data is considered in this paper. However, optimal wavelet analysis would be challenging in the realm of exploring GPR signals. There is no doubt that accounting for wavelet function, decomposition level, threshold estimation method and threshold transformation, in the matter of de-noising and investigating signals, is of great importance; they must be chosen with judgment as they influence the results enormously if they are not carefully designated. Multiple wavelet functions are applied to perform de-noising and reconstruction on synthetic noisy signals generated by the finite-difference time-domain (FDTD) method to account for the most appropriate function for the purpose. In addition, various possible decomposition levels, threshold estimation methods and threshold transformations in the de-noising procedure are tested. The optimal wavelet analysis is also evaluated by examining real data acquired from several antenna frequencies which are common in engineering practice.

  13. Myoelectric signal compression using zero-trees of wavelet coefficients. (United States)

    Norris, Jason A; Englehart, Kevin B; Lovely, Dennis F


    Recent progress in the diagnostic use of the myoelectric signal for neuromuscular diseases, coupled with increasing interests in telemedicine applications, mandate the need for an effective compression technique. The efficacy of the embedded zero-tree wavelet compression algorithm is examined with respect to some important analysis parameters (the length of the analysis segment and wavelet type) and measurement conditions (muscle type and contraction type). It is shown that compression performance improves with segment length, and that good choices of wavelet type include the Meyer wavelet and the fifth order biorthogonal wavelet. The effects of different muscle sites and contraction types on compression performance are less conclusive.A comparison of a number of lossy compression techniques has revealed that the EZW algorithm exhibits superior performance to a hard thresholding wavelet approach, but falls short of adaptive differential pulse code modulation. The bit prioritization capability of the EZW algorithm allows one to specify the compression factor online, making it an appealing technique for streaming data applications, as often encountered in telemedicine.

  14. Analysis and removing noise from speech using wavelet transform (United States)

    Tomala, Karel; Voznak, Miroslav; Partila, Pavol; Rezac, Filip; Safarik, Jakub


    The paper discusses the use of Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT) wavelet in removing noise from voice samples and evaluation of its impact on speech quality. One significant part of Quality of Service (QoS) in communication technology is the speech quality assessment. However, this part is seriously overlooked as telecommunication providers often focus on increasing network capacity, expansion of services offered and their enforcement in the market. Among the fundamental factors affecting the transmission properties of the communication chain is noise, either at the transmitter or the receiver side. A wavelet transform (WT) is a modern tool for signal processing. One of the most significant areas in which wavelet transforms are used is applications designed to suppress noise in signals. To remove noise from the voice sample in our experiment, we used the reference segment of the voice which was distorted by Gaussian white noise. An evaluation of the impact on speech quality was carried out by an intrusive objective algorithm Perceptual Evaluation of Speech Quality (PESQ). DWT and SWT transformation was applied to voice samples that were devalued by Gaussian white noise. Afterwards, we determined the effectiveness of DWT and SWT by means of objective algorithm PESQ. The decisive criterion for determining the quality of a voice sample once the noise had been removed was Mean Opinion Score (MOS) which we obtained in PESQ. The contribution of this work lies in the evaluation of efficiency of wavelet transformation to suppress noise in voice samples.

  15. Iterative PET Image Reconstruction Using Translation Invariant Wavelet Transform. (United States)

    Zhou, Jian; Senhadji, Lotfi; Coatrieux, Jean-Louis; Luo, Limin


    The present work describes a Bayesian maximum a posteriori (MAP) method using a statistical multiscale wavelet prior model. Rather than using the orthogonal discrete wavelet transform (DWT), this prior is built on the translation invariant wavelet transform (TIWT). The statistical modeling of wavelet coefficients relies on the generalized Gaussian distribution. Image reconstruction is performed in spatial domain with a fast block sequential iteration algorithm. We study theoretically the TIWT MAP method by analyzing the Hessian of the prior function to provide some insights on noise and resolution properties of image reconstruction. We adapt the key concept of local shift invariance and explore how the TIWT MAP algorithm behaves with different scales. It is also shown that larger support wavelet filters do not offer better performance in contrast recovery studies. These theoretical developments are confirmed through simulation studies. The results show that the proposed method is more attractive than other MAP methods using either the conventional Gibbs prior or the DWT-based wavelet prior.

  16. Selection of the wavelet function for the frequencies estimation; Seleccion de la funcion wavelet para la estimacion de frecuencias

    Energy Technology Data Exchange (ETDEWEB)

    Garcia R, A. [ININ, Carretera Mexico-Toluca S/N, 52750 La Marquesa, Ocoyoacac, Estado de Mexico (Mexico)]. e-mail:


    At the moment the signals are used to diagnose the state of the systems, by means of the extraction of their more important characteristics such as the frequencies, tendencies, changes and temporary evolutions. This characteristics are detected by means of diverse analysis techniques, as Autoregressive methods, Fourier Transformation, Fourier transformation in short time, Wavelet transformation, among others. The present work uses the one Wavelet transformation because it allows to analyze stationary, quasi-stationary and transitory signals in the time-frequency plane. It also describes a methodology to select the scales and the Wavelet function to be applied the one Wavelet transformation with the objective of detecting to the dominant system frequencies. (Author)

  17. Forecasting of particulate matter time series using wavelet analysis and wavelet-ARMA/ARIMA model in Taiyuan, China. (United States)

    Zhang, Hong; Zhang, Sheng; Wang, Ping; Qin, Yuzhe; Wang, Huifeng


    Particulate matter with aerodynamic diameter below 10 μm (PM10) forecasting is difficult because of the uncertainties in describing the emission and meteorological fields. This paper proposed a wavelet-ARMA/ARIMA model to forecast the short-term series of the PM10 concentrations. It was evaluated by experiments using a 10-year data set of daily PM10 concentrations from 4 stations located in Taiyuan, China. The results indicated the following: (1) PM10 concentrations of Taiyuan had a decreasing trend during 2005 to 2012 but increased in 2013. PM10 concentrations had an obvious seasonal fluctuation related to coal-fired heating in winter and early spring. (2) Spatial differences among the four stations showed that the PM10 concentrations in industrial and heavily trafficked areas were higher than those in residential and suburb areas. (3) Wavelet analysis revealed that the trend variation and the changes of the PM10 concentration of Taiyuan were complicated. (4) The proposed wavelet-ARIMA model could be efficiently and successfully applied to the PM10 forecasting field. Compared with the traditional ARMA/ARIMA methods, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction. Wavelet analysis can filter noisy signals and identify the variation trend and the fluctuation of the PM10 time-series data. Wavelet decomposition and reconstruction reduce the nonstationarity of the PM10 time-series data, and thus improve the accuracy of the prediction. This paper proposed a wavelet-ARMA/ARIMA model to forecast the PM10 time series. Compared with the traditional ARMA/ARIMA method, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction. The proposed model could be efficiently and successfully applied to the PM10 forecasting field.

  18. Potential Leaders and Democratic Values (United States)

    Monsma, Stephen V.


    Indicates that potential contenders for public office are likely to be more knowledgeable, interested, and libertarian than the average citizen. Concludes that these differences exist before leaders are elected and that this discrimination is functional in a democracy. (MB)

  19. Peer tutors as learning and teaching partners: a cumulative ...

    African Journals Online (AJOL)

    Peer tutors as learning and teaching partners: a cumulative approach to building peer tutoring capacity in higher education. ... when training and development is theoretically informed, coherent, and oriented towards improving practice. Keywords: academic development, academic literacies, cumulative learning, higher

  20. Is Mohammed a Strategic Leader? (United States)


    St ra te gy R es ea rc h Pr oj ec t IS MOHAMMED A STRATEGIC LEADER ? BY COLONEL JEFFREY WAYNE DRUSHAL United States Army DISTRIBUTION...To) 4. TITLE AND SUBTITLE Is Mohammed a Strategic Leader ? 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...ORGANIZATION NAME(S) AND ADDRESS(ES) Mr. Scott T. Forster Department of Command, Leadership, and Management 8. PERFORMING ORGANIZATION REPORT

  1. Career anchors of dentist leaders


    Tuononen Tiina; Lammintakanen Johanna; Suominen Anna Liisa


    Objective: The work of a health care leader is demanding; in order to cope, leaders need motivation and support. The occurrence of intrinsic factors called career anchors (combination of one’s competence, motives and values) could be a contributing factor in dentist leaders’ career decisions. The aim of our study was to identify dentist leaders’ career anchors and their association to dentist leaders’ retention or turnover of the leadership position. Material and methods: Materials were g...

  2. Hannibal: A Leader for Today. (United States)


    everything they say and do. Senior leaders model the Army value of honor: defined by courage, integrity, loyalty, duty, selfless service and...HANNIBAL: A LEADER FOR TODAY A thesis presented to the Faculty of the U.S. Army Command and General Staff College in partial fulfillment of the...Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188), Washington. DC 20503. 1. AGENCY USE ONLY

  3. Disarming the Key Leader Engagement (United States)


    niques and the managed expectation of key leader engagement effects. Effects are not immediate, and we must build them with candor, genuine agreement for U.S. forces? The agree- ment was understood in theory , but its application generated a litany of ques- tions. However, one...thing was clear: the way ahead would require systematic engagements with Iraqi leaders to leverage their powers of public persuasion. Military

  4. What leaders really do. (United States)

    Kotter, J P


    Leadership is different from management, but not for the reasons most people think. Leadership isn't mystical and mysterious. It has nothing to do with having "charisma" or other exotic personality traits. It is not the province of a chosen few. Nor is leadership necessarily better than management or a replacement for it. Rather, leadership and management are two distinctive and complementary systems of action. Each has its own function and characteristic activities. Both are necessary for success in today's business environment. Management is about coping with complexity. Its practices and procedures are largely a response to the emergence of large, complex organizations in the twentieth century. Leadership, by contrast, is about coping with change. Part of the reason it has become so important in recent years is that the business world has become more competitive and more volatile. More change always demands more leadership. Most U. S. corporations today are overmanaged and underled. They need to develop their capacity to exercise leadership. Successful corporations don't wait for leaders to come along. They actively seek out people with leadership potential and expose them to career experiences designed to develop that potential. Indeed, with careful selection, nurturing, and encouragement, dozens of people can play important leadership roles in a business organization. But while improving their ability to lead, companies should remember that strong leadership with weak management is no better, and is sometimes actually worse, than the reverse. The real challenge is to combine strong leadership and strong management and use each to balance the other.

  5. Preserved cumulative semantic interference despite amnesia

    Directory of Open Access Journals (Sweden)

    Gary Michael Oppenheim


    As predicted by Oppenheim et al’s (2010 implicit incremental learning account, WRP’s BCN RTs demonstrated strong (and significant repetition priming and semantic blocking effects (Figure 1. Similar to typical results from neurally intact undergraduates, WRP took longer to name pictures presented in semantically homogeneous blocks than in heterogeneous blocks, an effect that increased with each cycle. This result challenges accounts that ascribe cumulative semantic interference in this task to explicit memory mechanisms, instead suggesting that the effect has the sort of implicit learning bases that are typically spared in hippocampal amnesia.

  6. Is there any cumulative dose for trastuzumab? (United States)

    Mutlu, Hasan; Coşkun, Hasan Şenol


    Trastuzumab is one of the most important agents that target human epidermal growth factor receptor 2, but its cardiotoxic effect limits to use it. The mechanism of cardiac dysfunction-related trastuzumab is still unclear. In literature, there is no definite information about the cumulative dose of trastuzumab for cardiotoxicity. In presented case, we reported a breast cancer patient who has been receiving long-term trastuzumab. We have not found any cardiac problems for duration of over four years. According to our case and literature review, we may say that trastuzumab is safely used with periodically echocardiographic control in patients with breast cancer. © The Author(s) 2014.

  7. Remembering the Leaders of China

    Directory of Open Access Journals (Sweden)

    Mingchen eFu


    Full Text Available In two studies, we examined Chinese students’ memory for the names of the leaders of China. In Study 1, subjects were cued with the names of periods from China’s history. Subjects listed as many leaders as possible from each period and put them in the correct ordinal position when they could (see Roediger & DeSoto, 2014. Results showed that within each period, a primacy effect and sometimes a recency effect emerged. Moreover, the average recall probability for leaders within a specific period was a function of the ordinal position of the period. In Study 2, we asked another group of subjects to identify the sources through which they were able to recall each leader. We found that most subjects remembered leaders thanks to class and coursework. We also found a relation between a leader’s recall probability and the amount of information available on that leader on the Internet. Our findings further imply that the serial position function captures the form of collective memory.

  8. What Is an Innovative Educational Leader? (United States)

    Marron, Joseph M.; Cunniff, Dan


    This paper outlined the traits of an innovative educational leader in our changing society. It discussed the difference in a manager and leader, as well as the specific dispositions that differentiate the innovative educational leader from what many consider the average leader. The authors used the acronym "HELPSS" to highlight the…

  9. Kernel wavelet-Reed-Xiaoli: an anomaly detection for forward-looking infrared imagery. (United States)

    Mehmood, Asif; Nasrabadi, Nasser M


    This paper describes a new kernel wavelet-based anomaly detection technique for long-wave (LW) forward-looking infrared imagery. The proposed approach called kernel wavelet-Reed-Xiaoli (wavelet-RX) algorithm is essentially an extension of the wavelet-RX algorithm (combination of wavelet transform and RX anomaly detector) to a high-dimensional feature space (possibly infinite) via a certain nonlinear mapping function of the input data. The wavelet-RX algorithm in this high-dimensional feature space can easily be implemented in terms of kernels that implicitly compute dot products in the feature space (kernelizing the wavelet-RX algorithm). In the proposed kernel wavelet-RX algorithm, a two-dimensional wavelet transform is first applied to decompose the input image into uniform subbands. A number of significant subbands (high-energy subbands) are concatenated together to form a subband-image cube. The kernel RX algorithm is then applied to this subband-image cube. Experimental results are presented for the proposed kernel wavelet-RX, wavelet-RX, and the classical constant false alarm rate (CFAR) algorithm for detecting anomalies (targets) in a large database of LW imagery. The receiver operating characteristic plots show that the proposed kernel wavelet-RX algorithm outperforms the wavelet-RX as well as the classical CFAR detector.

  10. Spectral Laplace-Beltrami wavelets with applications in medical images. (United States)

    Tan, Mingzhen; Qiu, Anqi


    The spectral graph wavelet transform (SGWT) has recently been developed to compute wavelet transforms of functions defined on non-Euclidean spaces such as graphs. By capitalizing on the established framework of the SGWT, we adopt a fast and efficient computation of a discretized Laplace-Beltrami (LB) operator that allows its extension from arbitrary graphs to differentiable and closed 2-D manifolds (smooth surfaces embedded in the 3-D Euclidean space). This particular class of manifolds are widely used in bioimaging to characterize the morphology of cells, tissues, and organs. They are often discretized into triangular meshes, providing additional geometric information apart from simple nodes and weighted connections in graphs. In comparison with the SGWT, the wavelet bases constructed with the LB operator are spatially localized with a more uniform "spread" with respect to underlying curvature of the surface. In our experiments, we first use synthetic data to show that traditional applications of wavelets in smoothing and edge detectio can be done using the wavelet bases constructed with the LB operator. Second, we show that multi-resolutional capabilities of the proposed framework are applicable in the classification of Alzheimer's patients with normal subjects using hippocampal shapes. Wavelet transforms of the hippocampal shape deformations at finer resolutions registered higher sensitivity (96%) and specificity (90%) than the classification results obtained from the direct usage of hippocampal shape deformations. In addition, the Laplace-Beltrami method requires consistently a smaller number of principal components (to retain a fixed variance) at higher resolution as compared to the binary and weighted graph Laplacians, demonstrating the potential of the wavelet bases in adapting to the geometry of the underlying manifold.

  11. Cumulative effects of job characteristics on health. (United States)

    Fletcher, Jason M; Sindelar, Jody L; Yamaguchi, Shintaro


    We examine whether the job characteristics of physical demands and environmental conditions affect individual's health. Five-year cumulative measures of these job characteristics are used to reflect findings in the biological and physiological literature that indicate that cumulative exposure to hazards and stresses harms health. To create our analytic sample, we merge job characteristics from the Dictionary of Occupational Titles with the PSID data set. We control for early and also lagged health measures and a set of pre-determined characteristics to try to address concerns that individuals self-select into jobs. Our results indicate that individuals who work in jobs with the 'worst' conditions experience declines in their health, though this effect varies by demographic group. We also find some evidence that job characteristics are more detrimental to the health of females and older workers. Finally, we report suggestive evidence that earned income, a job characteristic, partially cushions the health impact of physical demands and harsh environmental conditions for workers. These results are robust to inclusion of occupation fixed effects. Copyright © 2010 John Wiley & Sons, Ltd.

  12. Wavelet Coherence Analysis of Change Blindness

    Directory of Open Access Journals (Sweden)

    Irfan Ali Memon


    Full Text Available Change blindness is the incapability of the brain to detect substantial visual changes in the presence of other visual interruption. The objectives of this study are to examine the EEG (Electroencephalographic based changes in functional connectivity of the brain due to the change blindness. The functional connectivity was estimated using the wavelet-based MSC (Magnitude Square Coherence function of ERPs (Event Related Potentials. The ERPs of 30 subjects were used and were recorded using the visual attention experiment in which subjects were instructed to detect changes in visual stimulus presented before them through the computer monitor. The two-way ANOVA statistical test revealed significant increase in both gamma and theta band MSCs, and significant decrease in beta band MSC for change detection trials. These findings imply that change blindness might be associated to the lack of functional connectivity in gamma and theta bands and increase of functional connectivity in beta band. Since gamma, theta, and beta frequency bands reflect different functions of cognitive process such as maintenance, encoding, retrieval, and matching and work load of VSTM (Visual Short Term Memory, the change in functional connectivity might be correlated to these cognitive processes during change blindness.

  13. WAKES: Wavelet Adaptive Kinetic Evolution Solvers (United States)

    Mardirian, Marine; Afeyan, Bedros; Larson, David


    We are developing a general capability to adaptively solve phase space evolution equations mixing particle and continuum techniques in an adaptive manner. The multi-scale approach is achieved using wavelet decompositions which allow phase space density estimation to occur with scale dependent increased accuracy and variable time stepping. Possible improvements on the SFK method of Larson are discussed, including the use of multiresolution analysis based Richardson-Lucy Iteration, adaptive step size control in explicit vs implicit approaches. Examples will be shown with KEEN waves and KEEPN (Kinetic Electrostatic Electron Positron Nonlinear) waves, which are the pair plasma generalization of the former, and have a much richer span of dynamical behavior. WAKES techniques are well suited for the study of driven and released nonlinear, non-stationary, self-organized structures in phase space which have no fluid, limit nor a linear limit, and yet remain undamped and coherent well past the drive period. The work reported here is based on the Vlasov-Poisson model of plasma dynamics. Work supported by a Grant from the AFOSR.

  14. The Emotional Intelligence of Leaders as Antecedent to Leader-Member Exchanges: A Field Study (United States)

    Barbuto, John E., Jr.; Bugenhagen, Marilyn J.


    Eighty elected leaders and 388 followers were sampled to test the relationships between leaders' emotional intelligence and the quality of leader-member exchange. Results of the field study found a significant relationship between leaders' emotional intelligence (total) and leader-member exchange quality. Specific subscales of emotional…

  15. Gender, Communication Styles, and Leader Effectiveness


    Timko, Krisztina


    We study gender differences in the behavior, communication, and effectiveness of randomly selected leaders in a laboratory experiment using the turnaround game. Leaders can send nonbinding pre‐play text messages to try to convince followers to coordinate on the Pareto‐efficient equilibrium. The treatment variations consist of the gender of the leader, and whether the communication is one‐way (only leaders send messages) or two‐way (first followers send messages to their leader, and subsequent...

  16. Wavelet Domain Radiofrequency Pulse Design Applied to Magnetic Resonance Imaging.

    Directory of Open Access Journals (Sweden)

    Andrew M Huettner

    Full Text Available A new method for designing radiofrequency (RF pulses with numerical optimization in the wavelet domain is presented. Numerical optimization may yield solutions that might otherwise have not been discovered with analytic techniques alone. Further, processing in the wavelet domain reduces the number of unknowns through compression properties inherent in wavelet transforms, providing a more tractable optimization problem. This algorithm is demonstrated with simultaneous multi-slice (SMS spin echo refocusing pulses because reduced peak RF power is necessary for SMS diffusion imaging with high acceleration factors. An iterative, nonlinear, constrained numerical minimization algorithm was developed to generate an optimized RF pulse waveform. Wavelet domain coefficients were modulated while iteratively running a Bloch equation simulator to generate the intermediate slice profile of the net magnetization. The algorithm minimizes the L2-norm of the slice profile with additional terms to penalize rejection band ripple and maximize the net transverse magnetization across each slice. Simulations and human brain imaging were used to demonstrate a new RF pulse design that yields an optimized slice profile and reduced peak energy deposition when applied to a multiband single-shot echo planar diffusion acquisition. This method may be used to optimize factors such as magnitude and phase spectral profiles and peak RF pulse power for multiband simultaneous multi-slice (SMS acquisitions. Wavelet-based RF pulse optimization provides a useful design method to achieve a pulse waveform with beneficial amplitude reduction while preserving appropriate magnetization response for magnetic resonance imaging.

  17. The Ricker wavelet and the Lambert W function (United States)

    Wang, Yanghua


    The Ricker wavelet has been widely used in the analysis of seismic data, as its asymmetrical amplitude spectrum can represent the attenuation feature of seismic wave propagation through viscoelastic homogeneous media. However, the frequency band of the Ricker wavelet is not analytically determined yet. The determination of the frequency band leads to an inverse exponential equation. To solve this equation analytically a special function, the Lambert W function, is needed. The latter provides a closed and elegant expression of the frequency band of the Ricker wavelet, which is a sample application of the Lambert W function in geophysics and there have been other applications in various scientific and engineering fields in the past decade. Moreover, the Lambert W function is a variation of the Ricker wavelet amplitude spectrum. Since the Ricker wavelet is the second derivative of a Gaussian function and its spectrum is a single-valued smooth curve, numerical evaluation of the Lambert W function can be implemented by a stable interpolation procedure, followed by a recursive computation for high precision.


    Directory of Open Access Journals (Sweden)

    Yasemin KAHRAMANER


    Full Text Available The influence of climatic oscillations (based on NAO and ENSO on monthly catch rates of fish population such as blue fish and sea bass (pomatomus population between 1991-2008 were analyzed in Black Sea and Marmara Sea by wavelet transform (Wavelet 1-D and continuous wavelet 1-D with DMeyer for 7-Levels. Wavelet analysis is an efficient method of time series analysis to study non-stationary data. Wavelet analyses allowed us to quantify both the pattern of variability in the time series and non-stationary associations between fish population and climatic signals. Phase analyses were carried out to investigate dependency between the two signals. We reported strong relations between fish stock and climate series for the 4- and 5-yr periodic modes, i.e. the periodic band of the El Nino Southern Oscillation signal propagation in the Black and Marmara Seas. These associations were non-stationary, evidenced from 1995 to 2008. Warm episodes matched increases of longline catch rates of bigeye during the 1970-1990 time frames, whereas the strong 1997-1998 warm event matched a decrease of purse seine catch rates of yellowfin. We discussed these results in terms of changes in catchability for purse seine and longline. The results of this study were compared with former harmonic analyses to explain seasonal effects of NAO and ENSO on fish population.

  19. Using Wavelets to Understand the Relationship between Mortgages and Gross Domestic Product in Spain

    Directory of Open Access Journals (Sweden)

    C. González-Concepción


    Full Text Available We use wavelet multiresolution decomposition and cross-wavelet analysis to reveal certain properties in financial data related to mortgages to households and gross domestic product data in Spain. Wavelet techniques possess many desirable properties, some of which are useful as a vehicle for analysing economic and financial data. In our case, wavelets are useful for drawing conclusions both in the time and frequency domains and for obtaining information on the different phases through which the study variables progress.

  20. Signal Separation of Helicopter Radar Returns Using Wavelet-Based Sparse Signal Optimisation (United States)


    transforms based on rational sampling factors, in Proc. Wavelet Applications in Industrial Processing. 56 UNCLASSIFIED UNCLASSIFIED DST-Group–RR–0436 [38...separation techniques cannot be applied. A sparse signal representation technique is now proposed for this problem with the tunable Q wavelet transform ...components using state-of-the-art wavelet transforms and sparse signal representation techniques. Wavelet transforms have been used extensively to

  1. Wavelet neural networks with applications in financial engineering, chaos, and classification

    CERN Document Server

    Alexandridis, Antonios K


    Through extensive examples and case studies, Wavelet Neural Networks provides a step-by-step introduction to modeling, training, and forecasting using wavelet networks. The acclaimed authors present a statistical model identification framework to successfully apply wavelet networks in various applications, specifically, providing the mathematical and statistical framework needed for model selection, variable selection, wavelet network construction, initialization, training, forecasting and prediction, confidence intervals, prediction intervals, and model adequacy testing. The text is ideal for

  2. Efficient algorithms for discrete wavelet transform with applications to denoising and fuzzy inference systems

    CERN Document Server

    Shukla, K K


    Due to its inherent time-scale locality characteristics, the discrete wavelet transform (DWT) has received considerable attention in signal/image processing. Wavelet transforms have excellent energy compaction characteristics and can provide perfect reconstruction. The shifting (translation) and scaling (dilation) are unique to wavelets. Orthogonality of wavelets with respect to dilations leads to multigrid representation. As the computation of DWT involves filtering, an efficient filtering process is essential in DWT hardware implementation. In the multistage DWT, coefficients are calculated

  3. Multi-input Multi-output Beta Wavelet Network: Modeling of Acoustic Units for Speech Recognition


    Chokri Ben Amar; Mourad Zaied; Ridha Ejbali


    In this paper, we propose a novel architecture of wavelet network called Multi-input Multi-output Wavelet Network MIMOWN as a generalization of the old architecture of wavelet network. This newel prototype was applied to speech recognition application especially to model acoustic unit of speech. The originality of our work is the proposal of MIMOWN to model acoustic unit of speech. This approach was proposed to overcome limitation of old wavelet network model. The use of the multi-input multi...

  4. Ion cumulation by conical cathode electrolysis.

    CERN Document Server

    Grishin, V G


    Results of solid-state sodium stearate electrolysis with conical and cylindrical cathodes is presented here. Both electric measurement and conical samples destruction can be explained if a stress developing inside the conical sample is much bigger than in the cylindrical case and there is its unlimited amplification along cone slopes. OTHER KEYWORDS: ion, current, solid, symmetry, cumulation, polarization, depolarization, ionic conductor,superionic conductor, ice, crystal, strain, V-center, V-centre, doped crystal, interstitial impurity, intrinsic color center, high pressure technology, Bridgman, anvil, experiment, crowdion, dielectric, proton, layer, defect, lattice, dynamics, electromigration, mobility, muon catalysis, concentration, doping, dopant, conductivity, pycnonuclear reaction, permittivity, dielectric constant, point defects, interstitials, polarizability, imperfection, defect centers, glass, epitaxy, sodium hydroxide, metallic substrate, crystallization, point, tip, susceptibility, ferroelectric, ...

  5. Kinetics of cumulative jet penetration into glass (United States)

    Rumyantsev, B. V.


    Assumption concerning violation of the regime of continuous hydrodynamic penetration is justified using experimental data on the cumulative jet (CJ) penetration into a glass obstacle. It is established that the CJ penetration into glass has a jumplike character and consists of a primary hydrodynamic penetration stage, cavity collapse, and secondary penetration into the collapsed material. In the case of continuous CJ supply, this process is repeated over the penetration depth. Necessary conditions for the secondary penetration are (i) a high strength of the glass target and (ii) a high rate of fracture, which ensure spalling of the material and collapse of the cavity walls. The jumplike penetration ceases when a pressure release wave arrives at the primary penetration zone.

  6. Leader performance and prototypicality : Their inter-relationship and impact on leaders' identity entrepreneurship

    NARCIS (Netherlands)

    Steffens, Niklas K.; Haslam, S. Alexander; Ryan, Michelle K.; Kessler, Thomas


    Research has demonstrated that leader performance and leader prototypicality are both predictors of leader endorsement. While performance and prototypicality have generally been considered to be independent, this paper suggests that performance and prototypicality are interdependent and have a

  7. Combined Logistics Officers Advanced Course (CLOAC): Leader Development for Future Ordnance Strategic Leaders

    National Research Council Canada - National Science Library

    Shipley, Claude


    Formal training is one of the methods for development of strategic leaders. The development of strategic Ordnance leaders is rooted initially with an officer first becoming competent as a leader and knowledgeable in their technical skills...

  8. Wavelet characterization of Hörmander symbol class Sm Sm Sm ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    Our new idea is to analyse the symbol operators in phase space with relative wavelets, and to establish the kernel distribution property and the operator's continuity on the basis of the wavelets coefficients in phase space. Keywords. Hörmander's symbol; wavelet; kernel distribution; operator's continuity. 1. Introduction.

  9. On Parseval Wavelet Frames with Two or Three Generators via the Unitary Extension Principle

    DEFF Research Database (Denmark)

    Christensen, Ole; Kim, Hong Oh; Kim, Rae Young


    The unitary extension principle (UEP) by A. Ron and Z. Shen yields a sufficient condition for the construction of Parseval wavelet frames with multiple generators. In this paper we characterize the UEP-type wavelet systems that can be extended to a Parseval wavelet frame by adding just one UEP-ty...



    Krotkikh, S. S.; Kirichenko, L. O.


    In this work we use discrete wavelet transform for analyzes the frequency structure of EEG signal with evoked potentials after effect of stimulus. The method for determining the response time to a stimulus, based on the evaluation of the wavelet entropy and relative wavelet entropy EEG, has been implemented.

  11. Travel opinion leaders and seekers

    DEFF Research Database (Denmark)

    Yoo, Kyung-Hyan; Gretzel, Ulrike; Zach, Florian


    While opinion leadership has been recognized as important in tourism, there has been very little empirical research investigating the phenomenon. Given new developments in social media technologies, it is especially important to understand whether travel opinion leadership and seeking are drivers...... of specific social media perceptions and behaviours. Based on an online survey of US online travellers, this paper seeks to identify travel opinion leaders and seekers and their characteristics. Further, the research conducted investigated linkages between travel opinion leadership/seeking and travel social...... media use. The findings suggest that travel opinion leadership and seeking are distinct but connected. Both opinion leaders and seekers are technology savvy, young, educated, involved in travel planning and engaged in social media use for travel. What distinguishes opinion leaders is their greater...

  12. Ethical leader behavior and leader effectiveness: the role of prototypicality and trust


    Kalshoven, K.; den Hartog, D.N.


    The study examines factors that mediate the impact of ethical leader behavior on leader effectiveness. Little is known about how ethical leadership impacts leader effectiveness. We hypothesized that prototypicality and trust sequentially mediate the relationship between ethical leader behavior and perceived leader effectiveness. The group prototype forms an ideal representation of the group’s identity, prescribing appropriate attitudes and behaviors. Ethical leaders are role models and thus a...

  13. Leader Attributions and Leader Behavior. First Stage Testing of Theoretical Model (United States)



  14. Anisotropy in wavelet-based phase field models

    KAUST Repository

    Korzec, Maciek


    When describing the anisotropic evolution of microstructures in solids using phase-field models, the anisotropy of the crystalline phases is usually introduced into the interfacial energy by directional dependencies of the gradient energy coefficients. We consider an alternative approach based on a wavelet analogue of the Laplace operator that is intrinsically anisotropic and linear. The paper focuses on the classical coupled temperature/Ginzburg--Landau type phase-field model for dendritic growth. For the model based on the wavelet analogue, existence, uniqueness and continuous dependence on initial data are proved for weak solutions. Numerical studies of the wavelet based phase-field model show dendritic growth similar to the results obtained for classical phase-field models.

  15. Classification of FTIR cancer data using wavelets and BPNN (United States)

    Cheng, Cungui; Tian, Yumei; Zhang, Changjiang


    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.

  16. Evaluation of the wavelet image two-line coder

    DEFF Research Database (Denmark)

    Rein, Stephan Alexander; Fitzek, Frank Hanns Paul; Gühmann, Clemens


    This paper introduces the wavelet image two-line (Wi2l) coding algorithm for low complexity compression of images. The algorithm recursively encodes an image backwards reading only two lines of a wavelet subband, which are read in blocks of 512 bytes from flash memory. It thus only requires very....... The times on a low-cost microcontroller for 256×256 grayscale pictures are measured as 0.25–0.6 s for encoding and 0.22–0.77 s for decoding. The algorithm can thus realize a low complexity system for compression of images when combined with a customized scheme for the wavelet transform; low complexity here....... The compression system uses flash memory (SD or MMC card) and a small camera sensor thus building an image communication system. It is also suitable for mobile devices or satellite communication. The underlying C source code is made publicly available....

  17. Viewing seismic velocity anomalies with 3-D continuous Gaussian wavelets (United States)

    Bergeron, Stephen Y.; Vincent, Alain P.; Yuen, David A.; Tranchant, Benoît J. S.; Tchong, Catherine

    Seismic velocity anomalies (SVA) have traditionally been viewed as spatial objects. We present a new method for looking at SVA, based on a 3-D continuous Gaussian wavelet transform. Local spectra of the seismic anomalies are calculated with the wavelet transforms. Two proxy quantities based on wavelets are used for viewing SVA. These proxy quantities are the 3-D spatial distributions of (1.) the local maxima of the L2-norm of the seismic anomalies, E-max, and (2.) the associated local horizontal wavenumber k-max. The P1200 tomographical model [Zhou 1996] has been used for this purpose. Geographical distributions of E-max and k-max yield information which are not obvious from direct visual inspection of SVA. Some examples are the depth extent of the tectonic boundaries and the inference of a plume-like object beneath the transition zone under Iceland.

  18. Apple Shape Classification Method Based on Wavelet Moment

    Directory of Open Access Journals (Sweden)

    Jiangsheng Gui


    Full Text Available Shape is not only an important indicator for assessing the grade of the apple, but also the important factors for increasing the value of the apple. In order to improve the apple shape classification accuracy rate, an approach for apple shape sorting based on wavelet moments was proposed, the image was first subjected to a normalization process using its regular moments to obtain scale and translation invariance, the rotation invariant wavelet moment features were then extracted from the scale and translation normalized images and the method of cluster analysis was used for finished the shape classification. This method performs better than traditional approaches such as Fourier descriptors and Zernike moments, because of that Wavelet moments can provide time-domain and frequency domain window, which was verified by experiments. The normal fruit shape, mild deformity and severe deformity classification accuracy is 86.21 %, 85.82 %, 90.81 % by our method.

  19. Dual tree fractional quaternion wavelet transform for disparity estimation. (United States)

    Kumar, Sanoj; Kumar, Sanjeev; Sukavanam, Nagarajan; Raman, Balasubramanian


    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. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Shearlet-Wavelet Regularized Semismooth Newton Iteration for Image Restoration

    Directory of Open Access Journals (Sweden)

    Liang Ding


    Full Text Available Image normally has both dots-like and curve structures. But the traditional wavelet or multidirectional wave (ridgelet, contourlet, curvelet, etc. could only restore one of these structures efficiently so that the restoration results for complex images are unsatisfactory. For the image restoration, this paper adopted a strategy of combined shearlet and wavelet frame and proposed a new restoration method. Theoretically, image sparse representation of dots-like and curve structures could be achieved by shearlet and wavelet, respectively. Under the L1 regularization, the two frame-sparse structures could show their respective advantages and efficiently restore the two structures. In order to achieve superlinear convergence, this paper applied semismooth Newton method based on subgradient to solve objective functional without differentiability. Finally, through numerical results, the effectiveness of this strategy was validated, which presented outstanding advantages for any individual frame alone. Some detailed information that could not be restored in individual frame could be clearly demonstrated with this strategy.

  1. Wavelet-based Image Enhancement Using Fourth Order PDE

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Forchhammer, Søren


    The presence of noise interference signal may cause problems in signal and image analysis; hence signal and image de-noising is often used as a preprocessing stage in many signal processing applications. In this paper, a new method is presented for image de-noising based on fourth order partial...... differential equations (PDEs) and wavelet transform. In the existing wavelet thresholding methods, the final noise reduced image has limited improvement. It is due to keeping the approximate coefficients of the image unchanged. These coefficients have the main information of the image. Since noise affects both...... the approximate and detail coefficients, in this research, the anisotropic diffusion technique for noise reduction is applied on the approximation band to alleviate the deficiency of the existing wavelet thresholding methods. The proposed method was applied on several standard noisy images and the results...

  2. Wavelet regression model in forecasting crude oil price (United States)

    Hamid, Mohd Helmie; Shabri, Ani


    This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

  3. Wavelet coherence of EEG signals for a visual oddball task. (United States)

    Qassim, Yahya T; Cutmore, Tim R H; James, Daniel A; Rowlands, David D


    Neural co-activation in frontal and central cortex was examined during a visual oddball task using wavelet coherence. EEG was recorded during a visual oddball task, presented to 12 participants with a random mix of 15% oddball targets and 85% frequent non-target letters over 265 trials. Wavelet coherence of individual trials was shown to distinguish frequent and oddball trials. Averaged wavelet coherence showed significant differences: oddball targets showed higher delta-theta activity whereas frequent background stimuli showed higher gamma activity. Increased gamma coherence appeared to be related to expectation of the targets with our analysis showing an R(2) of 0.935 for the relationship between averaged sections of gamma coherence and the number of intervening (frequent) trials since the last oddball. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. Real-time video codec using reversible wavelets (United States)

    Huang, Gen Dow; Chiang, David J.; Huang, Yi-En; Cheng, Allen


    This paper describes the hardware implementation of a real-time video codec using reversible Wavelets. The TechSoft (TS) real-time video system employs the Wavelet differencing for the inter-frame compression based on the independent Embedded Block Coding with Optimized Truncation (EBCOT) of the embedded bit stream. This high performance scalable image compression using EBCOT has been selected as part of the ISO new image compression standard, JPEG2000. The TS real-time video system can process up to 30 frames per second (fps) of the DVD format. In addition, audio signals are also processed by the same design for the cost reduction. Reversible Wavelets are used not only for the cost reduction, but also for the lossless applications. Design and implementation issues of the TS real-time video system are discussed.

  5. Image superresolution of cytology images using wavelet based patch search (United States)

    Vargas, Carlos; García-Arteaga, Juan D.; Romero, Eduardo


    Telecytology is a new research area that holds the potential of significantly reducing the number of deaths due to cervical cancer in developing countries. This work presents a novel super-resolution technique that couples high and low frequency information in order to reduce the bandwidth consumption of cervical image transmission. The proposed approach starts by decomposing into wavelets the high resolution images and transmitting only the lower frequency coefficients. The transmitted coefficients are used to reconstruct an image of the original size. Additional details are added by iteratively replacing patches of the wavelet reconstructed image with equivalent high resolution patches from a previously acquired image database. Finally, the original transmitted low frequency coefficients are used to correct the final image. Results show a higher signal to noise ratio in the proposed method over simply discarding high frequency wavelet coefficients or replacing directly down-sampled patches from the image-database.

  6. Application of wavelet transform in γ-ray spectra analysis (United States)

    Yu, GuoLiang; Gu, JianZhong; Hou, Long; Li, ZhenYu; Wang, YanZhao; Zhang, YiYun


    The frequency distribution of different ingredients in γ-ray spectra, e.g., photo-peak, fluctuations of counts and Compton region, is separately analyzed. After wavelet transform of γ-ray spectra, the wavelet coefficients of a photo-peak increase with transforming scales and these coefficients show direct proportion with intensity of peak at determinate scale. A novel algorithm based on wavelet transform is proposed and studied. The results indicate that most of the photo-peaks in multi-spectra can be determined accurately, the γ-rays energy and intensity of the peak can also be determined. This method has the prospect of being applied in on-line multi-spectra analysis in such fields as radioprotection and nuclear safety monitoring.

  7. Optimization of the Continuous Wavelet Transform for DSP Processor Implementation. (United States)

    Patil, Sunil; Abel, E


    The redundant wavelet transform is an effective tool when emphasis is on the analysis of non-stationary signals and on localization and characterization of singularities. Here we describe an optimized method to implement a B-spline based redundant wavelet transform (RWT) on a Digital Signal Processor (DSP) for integer scales. Expressions are derived to give an exact operation count at any integer scale m for any B-spline of order n. Finally experimental results are given using cubic b-spline as scaling function and first-and second-order derivative of B-splines as wavelets. It has been shown that optimized method improves the execution speed over the standard method by 20-28%.

  8. Wavelet analysis of MR functional data from the cerebellum

    Energy Technology Data Exchange (ETDEWEB)

    Karen, Romero Sánchez, E-mail:, E-mail:, E-mail:; Vásquez Reyes Marcos, A., E-mail:, E-mail:, E-mail:; González Gómez Dulce, I., E-mail:, E-mail:, E-mail:; Hernández López, Javier M., E-mail: [Faculty of Physics and Mathematics, BUAP, Puebla, Pue (Mexico); Silvia, Hidalgo Tobón, E-mail: [Infant Hospital of Mexico, Federico Gómez, Mexico DF. Mexico and Physics Department, Universidad Autónoma Metropolitana. Iztapalapa, Mexico DF. (Mexico); Pilar, Dies Suarez, E-mail:, E-mail:; Eduardo, Barragán Pérez, E-mail:, E-mail: [Infant Hospital of Mexico, Federico Gómez, Mexico DF. (Mexico); Benito, De Celis Alonso, E-mail: [Faculty of Physics and Mathematics, BUAP, Puebla, Pue. Mexico and Foundation for Development Carlos Sigüenza. Puebla, Pue. (Mexico)


    The main goal of this project was to create a computer algorithm based on wavelet analysis of BOLD signals, which automatically diagnosed ADHD using information from resting state MR experiments. Male right handed volunteers (infants with ages between 7 and 11 years old) were studied and compared with age matched controls. Wavelet analysis, which is a mathematical tool used to decompose time series into elementary constituents and detect hidden information, was applied here to the BOLD signal obtained from the cerebellum 8 region of all our volunteers. Statistical differences between the values of the a parameters of wavelet analysis was found and showed significant differences (p<0.02) between groups. This difference might help in the future to distinguish healthy from ADHD patients and therefore diagnose ADHD.

  9. Color graph based wavelet transform with perceptual information (United States)

    Malek, Mohamed; Helbert, David; Carré, Philippe


    We propose a numerical strategy to define a multiscale analysis for color and multicomponent images based on the representation of data on a graph. Our approach consists of computing the graph of an image using the psychovisual information and analyzing it by using the spectral graph wavelet transform. We suggest introducing color dimension into the computation of the weights of the graph and using the geodesic distance as a mean of distance measurement. We thus have defined a wavelet transform based on a graph with perceptual information by using the CIELab color distance. This new representation is illustrated with denoising and inpainting applications. Overall, by introducing psychovisual information in the graph computation for the graph wavelet transform, we obtain very promising results. Thus, results in image restoration highlight the interest of the appropriate use of color information.

  10. Preparing nurse leaders for 2020. (United States)

    Huston, Carol


    This article highlights eight leadership competencies likely to be an essential part of the nurse leader's repertoire in 2020. Planning for the future is difficult, even when environments are relatively static. When environments are dynamic, the challenges multiply exponentially. Unfortunately, few environments have been more unpredictable in the 21st century than health care. The healthcare system is in chaos, as is much of the business world. It is critical then that contemporary nursing and healthcare leaders identify skill sets that will be needed by nurse leaders in 2020 and begin now to create the educational models and management development programs necessary to assure these skills are present. Essential nurse leader competencies for 2020 include: (i) A global perspective or mindset regarding healthcare and professional nursing issues. (ii) Technology skills which facilitate mobility and portability of relationships, interactions, and operational processes. (iii) Expert decision-making skills rooted in empirical science. (iv) The ability to create organization cultures that permeate quality healthcare and patient/worker safety. (v) Understanding and appropriately intervening in political processes. (vi) Highly developed collaborative and team building skills. (vii) The ability to balance authenticity and performance expectations. (viii) Being able to envision and proactively adapt to a healthcare system characterized by rapid change and chaos. Nursing education programmes and healthcare organizations must be begin now to prepare nurses to be effective leaders in 2020. This will require the formal education and training that are a part of most management development programmes as well as a development of appropriate attitudes through social learning. Proactive succession planning will also be key to having nurse leaders who can respond effectively to the new challenges and opportunities that will be presented to them in 2020.

  11. Denoising portal images by means of wavelet techniques (United States)

    Gonzalez Lopez, Antonio Francisco

    Portal images are used in radiotherapy for the verification of patient positioning. The distinguishing feature of this image type lies in its formation process: the same beam used for patient treatment is used for image formation. The high energy of the photons used in radiotherapy strongly limits the quality of portal images: Low contrast between tissues, low spatial resolution and low signal to noise ratio. This Thesis studies the enhancement of these images, in particular denoising of portal images. The statistical properties of portal images and noise are studied: power spectra, statistical dependencies between image and noise and marginal, joint and conditional distributions in the wavelet domain. Later, various denoising methods are applied to noisy portal images. Methods operating in the wavelet domain are the basis of this Thesis. In addition, the Wiener filter and the non local means filter (NLM), operating in the image domain, are used as a reference. Other topics studied in this Thesis are spatial resolution, wavelet processing and image processing in dosimetry in radiotherapy. In this regard, the spatial resolution of portal imaging systems is studied; a new method for determining the spatial resolution of the imaging equipments in digital radiology is presented; the calculation of the power spectrum in the wavelet domain is studied; reducing uncertainty in film dosimetry is investigated; a method for the dosimetry of small radiation fields with radiochromic film is presented; the optimal signal resolution is determined, as a function of the noise level and the quantization step, in the digitization process of films and the useful optical density range is set, as a function of the required uncertainty level, for a densitometric system. Marginal distributions of portal images are similar to those of natural images. This also applies to the statistical relationships between wavelet coefficients, intra-band and inter-band. These facts result in a better

  12. Leaders – A Determinant Role

    Directory of Open Access Journals (Sweden)

    Vacar Anca


    Full Text Available No matter of the business sector the company plays in, today leadership is essential in order to be successful, because when we speak about leadership we think about the power that is the result of the connection between a leader and his followers. Today it is important to have good managers that organize and conduct the company in order to achieve the objectives, but it is more important that the managers to be good leaders that have the power to influence other in participating for achieving companies goals.

  13. Key Opinion Leaders - SMi's Second Conference Knowledge Leaders. (United States)

    Mason, Vicki L


    The Key Opinion Leaders (KOLs) conference, held in London, included topics covering new developments regarding the role of KOLs in the pharmaceutical industry. This conference report highlights selected presentations on insights from KOLs regarding their relationship with drug companies, conflicts of interest and negative aspects of the use of KOLs, and the role of patient advocacy groups.

  14. License to fail..?!! Leader prototypicality, leader performance, and leadership endorsement

    NARCIS (Netherlands)

    Giessner, S.R.; van Knippenberg, D.; Sleebos, E.


    Leadership often serves as an explanatory category for performance outcomes (i.e., failure and success). This process can strengthen or weaken leadership effectiveness, because contingent on their performance leaders may gain or lose follower endorsement - the basis of leadership. Drawing on the


    DEFF Research Database (Denmark)

    Pavlov, A.N.; Pavlova, O.N.; Mosekilde, Erik


    The purpose of this study is to demonstrate the possibility of revealing new characteristic features of renal blood flow autoregulation in healthy and pathological states through the application of discrete wavelet transforms to experimental time series for normotensive and hypertensive rats....... A reduction in the variability of the wavelet coefficients in hypertension is observed at both the microscopic level of the blood flow in efferent arterioles of individual nephrons and at the macroscopic level of the blood pressure in the main arteries. The reduction is manifest in both of the main frequency...

  16. Wavelet-analysis for Laser Images of Blood Plasma

    Directory of Open Access Journals (Sweden)



    Full Text Available The possibilities of the local wavelet-analysis of polarization-inhomogeneous laser image of human blood plasma were considered. The set of statistics, correlation and fractal parameters of the distributions of wavelet-coefficients that are characterize different scales of the polarization maps of polycrystalline networks of amino acids of blood plasma were defined. The criteria for the differentiation of the transformation of birefringence optical-anisotropic structures of blood plasma at different scales of their geometric dimensions were determined.

  17. Image restoration by minimizing zero norm of wavelet frame coefficients (United States)

    Bao, Chenglong; Dong, Bin; Hou, Likun; Shen, Zuowei; Zhang, Xiaoqun; Zhang, Xue


    In this paper, we propose two algorithms, namely the extrapolated proximal iterative hard thresholding (EPIHT) algorithm and the EPIHT algorithm with line-search, for solving the {{\\ell }}0-norm regularized wavelet frame balanced approach for image restoration. Under the theoretical framework of Kurdyka-Łojasiewicz property, we show that the sequences generated by the two algorithms converge to a local minimizer with linear convergence rate. Moreover, extensive numerical experiments on sparse signal reconstruction and wavelet frame based image restoration problems including CT reconstruction, image deblur, demonstrate the improvement of {{\\ell }}0-norm based regularization models over some prevailing ones, as well as the computational efficiency of the proposed algorithms.

  18. Speckle Suppression in Ultrasonic Images Based on Undecimated Wavelets

    Directory of Open Access Journals (Sweden)

    Fabrizio Argenti


    Full Text Available An original method to denoise ultrasonic images affected by speckle is presented. Speckle is modeled as a signal-dependent noise corrupting the image. Noise reduction is approached as a Wiener-like filtering performed in a shift-invariant wavelet domain by means of an adaptive rescaling of the coefficients of an undecimated octave decomposition. The scaling factor of each coefficient is calculated from local statistics of the degraded image, the parameters of the noise model, and the wavelet filters. Experimental results demonstrate that excellent background smoothing as well as preservation of edge sharpness and fine details can be obtained.

  19. Time-frequency analysis with the continuous wavelet transform (United States)

    Lang, W. Christopher; Forinash, Kyle


    The continuous wavelet transform can be used to produce spectrograms which show the frequency content of sounds (or other signals) as a function of time in a manner analogous to sheet music. While this technique is commonly used in the engineering community for signal analysis, the physics community has, in our opinion, remained relatively unaware of this development. Indeed, some find the very notion of frequency as a function of time troublesome. Here spectrograms will be displayed for familiar sounds whose pitches change with time, demonstrating the usefulness of the continuous wavelet transform.

  20. Electroencephalography data analysis by using discrete wavelet packet transform (United States)

    Karim, Samsul Ariffin Abdul; Ismail, Mohd Tahir; Hasan, Mohammad Khatim; Sulaiman, Jumat; Muthuvalu, Mohana Sundaram; Janier Josefina, B.


    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.

  1. Adaptive wavelet-based recognition of oscillatory patterns on electroencephalograms (United States)

    Nazimov, Alexey I.; Pavlov, Alexey N.; Hramov, Alexander E.; Grubov, Vadim V.; Koronovskii, Alexey A.; Sitnikova, Evgenija Y.


    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.

  2. Wind Speed Forecasting Using Hybrid Wavelet Transform—ARMA Techniques

    Directory of Open Access Journals (Sweden)

    Diksha Kaur


    Full Text Available The objective of this paper is to develop a novel wind speed forecasting technique, which produces more accurate prediction. The Wavelet Transform (WT along with the Auto Regressive Moving Average (ARMA is chosen to form a hybrid whose combination is expected to give minimum Mean Absolute Prediction Error (MAPE. A simulation study has been conducted by comparing the forecasting results using the Wavelet-ARMA with the ARMA and Artificial Neural Network (ANN-Ensemble Kalman Filter (EnKF hybrid technique to verify the effectiveness of the proposed hybrid method. Results of the proposed hybrid show significant improvements in the forecasting error.

  3. Research on Far-Field Wavelet's Extraction and Application of Vertical Cable System (United States)

    Wang, Xiangchun; Xiao, Qingsong; Xia, Changliang; Wu, Zhongliang; Xie, Chengliang


    In marine seismic exploration, ghost wave and bubble effect reduce the vertical resolution and interpretation accuracy seriously. Here firstly the far-field wavelet including source wavelet, ghost wave and bubble effect recorded by the vertical cable system (VCS) is extracted. Then, filters are designed using the extracted far-field wavelet to eliminate ghost wave, bubble effect and source wavelet. At last, the designed filters are applied to the seismic data of VCS. The results show that this method can eliminate ghost wave, bubble effect and source wavelet effectively and the vertical resolution of the seismic data is improved obviously.

  4. Structural Health Monitoring approach for detecting ice accretion on bridge cable using the Haar Wavelet Transform

    DEFF Research Database (Denmark)

    Andre, Julia; Kiremidjian, Anne; Liao, Yizheng


    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 de fined 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...

  5. Research on artificial neural network intrusion detection photochemistry based on the improved wavelet analysis and transformation (United States)

    Li, Hong; Ding, Xue


    This paper combines wavelet analysis and wavelet transform theory with artificial neural network, through the pretreatment on point feature attributes before in intrusion detection, to make them suitable for improvement of wavelet neural network. The whole intrusion classification model gets the better adaptability, self-learning ability, greatly enhances the wavelet neural network for solving the problem of field detection invasion, reduces storage space, contributes to improve the performance of the constructed neural network, and reduces the training time. Finally the results of the KDDCup99 data set simulation experiment shows that, this method reduces the complexity of constructing wavelet neural network, but also ensures the accuracy of the intrusion classification.

  6. Addressing cumulative effects in Strategic Environmental Assessment of spatial planning

    Directory of Open Access Journals (Sweden)

    Chiara Bragagnolo


    Full Text Available Strategic environmental Assessment (SEA is a decision support instrument for predicting and evaluating the likely environmental effects of implementing a policy, plan or programme. SEA can consider the cumulative impacts of more than one project or activity on the same environmen- tal component. This paper discusses the analysis of cumulative effects in SEA, with reference to spatial planning by: providing a review of key concepts and methods related to cumulative effects literature; presenting a rationale for the inclusion of cumulative effects in SEA of spatial plans; advancing a proposal to address cumulative effects in different SEA stages. The paper concludes that SEA offers the opportunity to support a better management of cumulative effects arising from many local-level spatial planning decisions. Three aspects emerged as critical to ensure good practices: the selection of valued environmental components, the adoption of future-oriented approaches, and the use of spatially-explicit information.

  7. George Washington: A Grounded Leader (United States)


    Highway, Suite 1204·, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington, DC......a broad array of experiences, enabled him to become a leader who profoundly affected those around him. George Washington reflected a man of the

  8. Strategic Communications for School Leaders (United States)

    Gunther, Vicki; McGowan, James; Donegan, Kate


    Gunther, McGowan and Donegan draw on their own experiences and those of others in the field, to explain the importance of communication in school leadership. In focusing on the communication process--why it's critical for schools, and how it can be executed well--they make the case that communication must be a primary emphasis for leaders, not an…

  9. Types of Leader in Organisation

    Directory of Open Access Journals (Sweden)

    Marian Aurelian Bârgău


    Full Text Available Besides leading theories of people in one way or another from different angles reveal the types of leaders who can meet in business management literature contains classifications of management styles, which take into account different criteria or viewpoints. The word “leadership‟ has been used in various aspects of human endeavor such as politics, businesses, academics, social works, etc. Previous views about leadership show it as personal ability. The individual leader traits depend not only on personal abilities and his characteristics, but in special on the characteristics of the situation and environment in which he finds himself. People could become members of an organization in other to achieve certain personal objectives, the extent to which they are active members depends on how they are convinced that their membership will enable them to achieve their predetermined objectives. The leader will support an organization if he believes that through it his personal objectives and goals could be met otherwise the person’s interest will decline. The type leader or style of leading in an organization is one of the factors that play significant role in enhancing or retarding the interest and commitment of the individuals in the organization.

  10. LEADER-tegevusest / Ene Sarapuu

    Index Scriptorium Estoniae

    Sarapuu, Ene


    Läänemaa LEADER-tegevusgrupi eesmärk on maakonna kui terviku ühtne areng, et kogu Läänemaa oleks vajalike teenustega kaetud ning ettevõtjad julgeks ning suudaks uute teenuste ja toodetega turule tulla

  11. Women Administrators as Instructional Leaders (United States)

    Horner, Beth A.


    Women are under-represented in educational research and are much less likely to hold administrative positions than are men. This study, using the Liberal Feminist Theory and Structural Barrier Theory, proffers possible explanations for this phenomenon. Four women leaders were interviewed to gain insight into their instructional leadership…

  12. Educating School Leaders for Democracy (United States)

    Moos, Lejf


    In order to be able to discuss, in meaningful ways, how school leaders should be educated one needs to sketch the context in which they are going to lead, that is the visions and purpose of education and the schooling, which is dominant in society. In most societies one sees clashes of many discourses and cultural/political fights. In order to…

  13. A Leader, Not a Hero (United States)

    Rutledge, Lynda


    The author writes her experience in leading. She points out that a good leader should know when and how to let go than trying to do all the work by herself. It changed her focus on looking at details, implementation, dealing with the contractors, to leading leading people.

  14. Women Leaders Tell Their Stories (United States)

    Grady, Marilyn L.; Curley, Virginia Russell; Lacost, Barbara


    The purpose of this research study was to identify examples of women education leaders at their best. There were two parts to the study procedures. First, the women were asked to write a case story about a time when they were involved in a successful leadership experience. Second, the women were divided into small groups of 5-8. In the small…

  15. Dom Mintoff : un leader postcoloniale


    Mayo, Peter


    Ricordo del leader laburista maltese, che diresse a lungo il suo paese con una coraggiosa politica di non sudditanza verso le potenze dell’Occidente capitalistico. Il realismo sposato con la volontà di non perdere mai le ragioni del suo essere laburista.

  16. Comparison of a discrete wavelet transform method and a modified undecimated discrete wavelet transform method for denoising of mammograms. (United States)

    Matsuyama, Eri; Tsai, Du-Yih; Lee, Yongbum; Takahashi, Noriyuki


    The purpose of this study was to evaluate the performance of a conventional discrete wavelet transform (DWT) method and a modified undecimated discrete wavelet transform (M-UDWT) method applied to mammographic image denoising. Mutual information, mean square error, and signal to noise ratio were used as image quality measures of images processed by the two methods. We examined the performance of the two methods with visual perceptual evaluation. A two-tailed F test was used to measure statistical significance. The difference between the M-UDWT processed images and the conventional DWT-method processed images was statistically significant (Pimage quality as compared to the conventional DWT.

  17. 7 CFR 42.132 - Determining cumulative sum values. (United States)


    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Determining cumulative sum values. 42.132 Section 42... Determining cumulative sum values. (a) The parameters for the on-line cumulative sum sampling plans for AQL's... 3 1 2.5 3 1 2 1 (b) At the beginning of the basic inspection period, the CuSum value is set equal to...

  18. Neutron spectroscopy with scintillation detectors using wavelets (United States)

    Hartman, Jessica

    The purpose of this research was to study neutron spectroscopy using the EJ-299-33A plastic scintillator. This scintillator material provided a novel means of detection for fast neutrons, without the disadvantages of traditional liquid scintillation materials. EJ-299-33A provided a more durable option to these materials, making it less likely to be damaged during handling. Unlike liquid scintillators, this plastic scintillator was manufactured from a non-toxic material, making it safer to use, as well as easier to design detectors. The material was also manufactured with inherent pulse shape discrimination abilities, making it suitable for use in neutron detection. The neutron spectral unfolding technique was developed in two stages. Initial detector response function modeling was carried out through the use of the MCNPX Monte Carlo code. The response functions were developed for a monoenergetic neutron flux. Wavelets were then applied to smooth the response function. The spectral unfolding technique was applied through polynomial fitting and optimization techniques in MATLAB. Verification of the unfolding technique was carried out through the use of experimentally determined response functions. These were measured on the neutron source based on the Van de Graff accelerator at the University of Kentucky. This machine provided a range of monoenergetic neutron beams between 0.1 MeV and 24 MeV, making it possible to measure the set of response functions of the EJ-299-33A plastic scintillator detector to neutrons of specific energies. The response of a plutonium-beryllium (PuBe) source was measured using the source available at the University of Nevada, Las Vegas. The neutron spectrum reconstruction was carried out using the experimentally measured response functions. Experimental data was collected in the list mode of the waveform digitizer. Post processing of this data focused on the pulse shape discrimination analysis of the recorded response functions to remove the

  19. Identification and Quantification of Cumulative Factors that ... (United States)

    Evaluating the combined adverse effects of multiple stressors upon human health is an imperative component of cumulative risk assessment (CRA)1. In addition to chemical stressors, other non-chemical factors are also considered. For examples, smoking will elevate the risks of having lung cancer associated with radon exposure2; toluene and noise together will induce higher levels of hearing loss3; children exposed to violence will have higher risks of developing asthma in the presence of air pollution4. Environmental Justice (EJ) indicators, used as a tool to assess and quantify some of these non-chemical factors, include health, economic, and social indicators such as vulnerability and susceptibility5. Vulnerability factors encompass race, ethnicity, behavior, geographic location, etc., while susceptibility factors include life stage, genetic predisposition, pre-existing health condition and others6, although these two categories are not always mutually exclusive. Numerous findings regarding combined effects of EJ indicators and chemical stressors have been identified7-11. However, fewer studies have analyzed the interrelation between multiple stressors that exert combined harmful effects upon individual or population health in the context of exposure assessment within the risk assessment framework12. In this study, we connected EJ indicators to variables in the exposure assessment model, especially the Average Daily Dose (ADD) model13, in order to better underst

  20. Leadership, Leaders, and Leading (Part One). (United States)

    Dean, Peter J.


    Presents an historical overview of the leadership literature. Highlights include "great man" theories; studies of leaders' traits; studies of leaders' behavioral style; studies of leadership functions; and studies of the situational aspects of leadership. (LRW)

  1. Leader Trust, Competence, LMX, and Member Performance. (United States)

    Byun, Gukdo; Dai, Ye; Lee, Soojin; Kang, Seungwan


    Based on social exchange theory, this study examines the influence of leaders' trusting behavior and competence in in-role activities on members' perceived leader-member exchange (LMX) relationships. Our study proposes that a leader's trust in a member contributes to the member's perceived LMX, and that the leader's competence in in-role activities moderates this relationship. Furthermore, our study suggests that perceived LMX mediates the relationship between the leader's trust and members' task performance. Finally, the study proposes that the leader's competence moderates the mediating role of LMX in transmitting the effect of the leader's trust on members' task performance. Analyses of the data collected from soldiers and platoon leaders in the South Korean army support these hypotheses.

  2. Managers and Leaders: Are They Different? (United States)

    Zaleznik, Abraham


    Discusses the differences between managers and leaders in terms of personality, attitudes toward goals, conceptions of work, relations with others, and senses of self. Also examines the development of leadership and how organizations can develop leaders. (CT)

  3. Leader growth in Nordman fir christmas trees

    DEFF Research Database (Denmark)

    Christensen, Claus Jerram; Pedersen, Lars Bo

    Leader Griowth in Nordman fir Christmas trees: Growth visualization and effects of fertilization, irrigation and drought......Leader Griowth in Nordman fir Christmas trees: Growth visualization and effects of fertilization, irrigation and drought...

  4. Elastic wavelets and their application to problems of solitary wave propagation

    Directory of Open Access Journals (Sweden)

    Cattani, Carlo


    Full Text Available The paper can be referred to that direction in the wavelet theory, which was called by Kaiser "the physical wavelets". He developed the analysis of first two kinds of physical wavelets - electromagnetic (optic and acoustic wavelets. Newland developed the technique of application of harmonic wavelets especially for studying the harmonic vibrations. Recently Cattani and Rushchitsky proposed the 4th kind of physical wavelets - elastic wavelets. This proposal was based on three main elements: 1. Kaiser's idea of constructing the physical wavelets on the base of specially chosen (admissible solutions of wave equations. 2. Developed by one of authors theory of solitary waves (with profiles in the form of Chebyshov-Hermite functions propagated in elastic dispersive media. 3. The theory and practice of using the wavelet "Mexican Hat" system, the mother and farther wavelets (and their Fourier transforms of which are analytically represented as the Chebyshov-Hermite functions of different indexes. An application of elastic wavelets to studying the evolution of solitary waves of different shape during their propagation through composite materials is shown on many examples.

  5. Analysis of Memory Codes and Cumulative Rehearsal in Observational Learning (United States)

    Bandura, Albert; And Others


    The present study examined the influence of memory codes varying in meaningfulness and retrievability and cumulative rehearsal on retention of observationally learned responses over increasing temporal intervals. (Editor)

  6. Hybrid Fuzzy Wavelet Neural Networks Architecture Based on Polynomial Neural Networks and Fuzzy Set/Relation Inference-Based Wavelet Neurons. (United States)

    Huang, Wei; Oh, Sung-Kwun; Pedrycz, Witold


    This paper presents a hybrid fuzzy wavelet neural network (HFWNN) realized with the aid of polynomial neural networks (PNNs) and fuzzy inference-based wavelet neurons (FIWNs). Two types of FIWNs including fuzzy set inference-based wavelet neurons (FSIWNs) and fuzzy relation inference-based wavelet neurons (FRIWNs) are proposed. In particular, a FIWN without any fuzzy set component (viz., a premise part of fuzzy rule) becomes a wavelet neuron (WN). To alleviate the limitations of the conventional wavelet neural networks or fuzzy wavelet neural networks whose parameters are determined based on a purely random basis, the parameters of wavelet functions standing in FIWNs or WNs are initialized by using the C-Means clustering method. The overall architecture of the HFWNN is similar to the one of the typical PNNs. The main strategies in the design of HFWNN are developed as follows. First, the first layer of the network consists of FIWNs (e.g., FSIWN or FRIWN) that are used to reflect the uncertainty of data, while the second and higher layers consist of WNs, which exhibit a high level of flexibility and realize a linear combination of wavelet functions. Second, the parameters used in the design of the HFWNN are adjusted through genetic optimization. To evaluate the performance of the proposed HFWNN, several publicly available data are considered. Furthermore a thorough comparative analysis is covered.

  7. Modeling stepped leaders using a time-dependent multidipole model and high-speed video data (United States)

    Karunarathne, Sumedhe; Marshall, Thomas C.; Stolzenburg, Maribeth; Karunarathna, Nadeeka; Orville, Richard E.


    A full negative stepped leader and portions of four negative stepped leaders preceding negative cloud-to-ground lightning return strokes were modeled; each model was constrained to match electric field change measurements recorded at three or four sites located within 30 km of the leader. The time evolution and 2-D locations of stepped leaders were obtained from data collected with a high-speed video camera operated at 50,000 frames/s. The Lu et al. (Charge transfer during intracloud lightning from a time-dependent multidipole model, Journal of Geophysical Research, 2011) time-dependent multidipole model was used with some modifications. The model used a time step equal to one video frame, 20μs. At each time step, negative charges were deposited at stepped leader tips based on measured light intensity, and an equivalent positive charge was deposited at one of the locations of the initial breakdown pulses that preceded the stepped leaders. The method has the unique advantage of obtaining locations of CG stepped leaders including its branches all the way to the ground. Three main quantities were obtained from the model: total charge transfer of -1.50 to -7.51 C, average line charge density of -0.113 to -0.413 mC/m (mean =- 0.196 mC/m), and average current of -0.084 to -0.456 kA (mean =- 0.31 kA). From the video data, the estimated 2-D speeds were 2.43-4.95×105 m/s (mean 3.34 × 105 m/s), and the cumulative lengths of the all branches were 3.5-9.2 times the vertical distance traveled by the visible stepped leader.

  8. Construction of Interval Shannon Wavelet and Its Application in Solving Nonlinear Black-Scholes Equation

    Directory of Open Access Journals (Sweden)

    Liwei Liu


    Full Text Available Interval wavelet numerical method for nonlinear PDEs can improve the calculation precision compared with the common wavelet. A new interval Shannon wavelet is constructed with the general variational principle. Compared with the existing interval wavelet, both the gradient and the smoothness near the boundary of the approximated function are taken into account. Using the new interval Shannon wavelet, a multiscale interpolation wavelet operator was constructed in this paper, which can transform the nonlinear partial differential equations into matrix differential equations; this can be solved by the coupling technique of the wavelet precise integration method (WPIM and the variational iteration method (VIM. At last, the famous Black-Scholes model is taken as an example to test this new method. The numerical results show that this method can decrease the boundary effect greatly and improve the numerical precision in the whole definition domain compared with Yan’s method.

  9. Dependence and risk assessment for oil prices and exchange rate portfolios: A wavelet based approach (United States)

    Aloui, Chaker; Jammazi, Rania


    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.

  10. Developing 21st Century Senior Leaders (United States)


    containing “required SSC.” Use this list to ensure the system is policed by the Senior Leader Development (SLD) and branch managers through the validation...colleges produce senior leaders who work as organizational managers , leaders , and operational artist. Department of Army should have a more focused...St ra te gy R es ea rc h Pr oj ec t DEVELOPING 21ST CENTURY SENIOR LEADERS BY LIEUTENANT COLONEL KEATON L. BEAUMONT United States Army

  11. Wavelet based denoising of power quality events for characterization

    African Journals Online (AJOL)

    The effectiveness of wavelet transform (WT) methods for analyzing different power quality (PQ) events with or without noise has been demonstrated in this paper. Multi-resolution signal decomposition based on discrete WT is used to localize and to classify different power quality disturbances. The energy distribution at ...

  12. Wavelet Transforms: Application to Data Analysis-I

    Indian Academy of Sciences (India)

    ... Lecture Workshops · Refresher Courses · Symposia. Home; Journals; Resonance – Journal of Science Education; Volume 9; Issue 11. Wavelet Transforms: Application to Data Analysis – I. Jatan K Modi Sachin P Nanavati Amit S Phadke Prasanta K Panigrahi. General Article Volume 9 Issue 11 November 2004 pp 10-22 ...

  13. Wavelet Transforms: Application to Data Analysis–II

    Indian Academy of Sciences (India)

    ... Lecture Workshops · Refresher Courses · Symposia. Home; Journals; Resonance – Journal of Science Education; Volume 9; Issue 12. Wavelet Transforms: Application to Data Analysis – II. Jatan K Modi Sachin P Nanavati Amit S Phadke Prasanta K Panigrahi. General Article Volume 9 Issue 12 December 2004 pp 8-13 ...

  14. Accelerating Wavelet Lifting on Graphics Hardware Using CUDA

    NARCIS (Netherlands)

    Laan, Wladimir J. van der; Jalba, Andrei C.; Roerdink, Jos B.T.M.

    The Discrete Wavelet Transform (DWT) has a wide range of applications from signal processing to video and image compression. We show that this transform, by means of the lifting scheme, can be performed in a memory and computation-efficient way on modern, programmable GPUs, which can be regarded as

  15. Analytic discrete cosine harmonic wavelet transform based OFDM ...

    Indian Academy of Sciences (India)

    Abstract. An OFDM based on Analytic Discrete Cosine Harmonic Wavelet Trans- form (ADCHWT_OFDM) has been proposed in this paper. Analytic DCHWT has been realized by applying DCHWT to the original signal and to its Hilbert trans- form. ADCHWT has been found to be computationally efficient and very effective.

  16. Noise reduction in ultrasonic NDT using undecimated wavelet transforms. (United States)

    Pardo, E; San Emeterio, J L; Rodriguez, M A; Ramos, A


    Translation-invariant wavelet processing is applied to grain noise reduction in ultrasonic non-destructive testing of materials. In particular, the undecimated wavelet transform (UWT), which is essentially a discrete wavelet transform (DWT) that avoids decimation, is used. Two different UWT processors have been specifically developed for that purpose, based on two UWT implementation schemes: the "à trous" algorithm and the cycle-spinning scheme. The performance of these two UWT processors is compared with that of a classical DWT processor, by using synthetic grain noise registers and experimental pulse-echo NDT traces. The synthetic ultrasonic traces have been generated by an own-developed frequency-domain model that includes frequency dependence in both material attenuation and scattering. The experimental ultrasonic traces have been obtained by inspecting a piece of carbon-fiber reinforced plastic composite in which we have mechanized artificial flaws. Decomposition level-dependent thresholds, which are suitable for correlated noise, are specifically determined in all cases. Soft thresholding, Daubechies db6 mother wavelet and the three well-known threshold selection rules, Universal, Minimax and SURE, are applied to the different decomposition levels. The performance of the different de-noising procedures for single echo detection has been comparatively evaluated in terms of signal-to-noise ratio enhancement.

  17. Adaptive wavelet methods for solving operator equations: An overview

    NARCIS (Netherlands)

    Stevenson, R.; DeVore, R.A.; Kunoth, A.


    In [Math. Comp, 70 (2001), 27-75] and [Found. Comput. Math., 2(3) (2002), 203-245], Cohen, Dahmen and DeVore introduced adaptive wavelet methods for solving operator equations. These papers meant a break-through in the field, because their adaptive methods were not only proven to converge, but also

  18. Brain MRI tumor image fusion combined with Shearlet and wavelet (United States)

    Zhang, Changjiang; Fang, Mingchao


    In order to extract the effective information in different modalities of the tumor region in brain Magnetic resonance imaging (MRI) images, we propose a brain MRI tumor image fusion method combined with Shearlet and wavelet transform. First, the source images are transformed into Shearlet domain and wavelet domain. Second, the low frequency component of Shearlet domain is fused by Laplace pyramid decomposition. Then the low-frequency fusion image is obtained through inverse Shearlet transform. Third, the high frequency subimages in wavelet domain are fused. Then the high-frequency fusion image is obtained through inverse wavelet transform. Finally, the low-frequency fusion image and high-frequency fusion image are summated to get the final fusion image. Through experiments conducted on 10 brain MRI tumor images, the result shown that the proposed fusion algorithm has the best fusion effect in the evaluation indexes of spatial frequency, edge strength and average gradient. The main spatial frequency of 10 images is 29.22, and the mean edge strength and average gradient is 103.77 and 10.42. Compared with different fusion methods, we find that the proposed method effectively fuses the information of multimodal brain MRI tumor images and improves the clarity of the tumor area well.

  19. Wavelet diagnostics for detection of coherent structures in ...

    Indian Academy of Sciences (India)

    Int. J. Wavelets, Multi Resolution Inf. Process. (to appear). Basu A J, Narasimha R 1999 Direct numerical simulation of turbulent flows with cloud-like off-source heating. J. Fluid Mech. 385: 199–228. Bhat G S, Narasimha R 1996 A volumetrically heated jet: large-eddy structure and entrainment characteristics. J. Fluid Mech.

  20. On the equivalence of brushlet and wavelet bases

    DEFF Research Database (Denmark)

    Nielsen, Morten; Borup, Lasse


    We prove that the Meyer wavelet basis and a class of brushlet systems associated with exponential type partitions of the frequency axis form a family of equivalent (unconditional) bases for the Besov and Triebel-Lizorkin function spaces. This equivalence is then used to obtain new results...

  1. On the equivalence of brushlet and wavelet bases

    DEFF Research Database (Denmark)

    Borup, Lasse; Nielsen, Morten

    We prove that the Meyer wavelet basis and a class of brushlet systems associated with exponential type partitions of the frequency axis form a family of equivalent (unconditional) bases for the Besov and Triebel-Lizorkin function spaces. This equivalence is then used to obtain new results...

  2. Wavelet Packet Transform Based Driver Distraction Level Classification Using EEG

    Directory of Open Access Journals (Sweden)

    Mousa Kadhim Wali


    Full Text Available We classify the driver distraction level (neutral, low, medium, and high based on different wavelets and classifiers using wireless electroencephalogram (EEG signals. 50 subjects were used for data collection using 14 electrodes. We considered for this research 4 distraction stimuli such as Global Position Systems (GPS, music player, short message service (SMS, and mental tasks. Deriving the amplitude spectrum of three different frequency bands theta, alpha, and beta of EEG signals was based on fusion of discrete wavelet packet transform (DWPT and FFT. Comparing the results of three different classifiers (subtractive fuzzy clustering probabilistic neural network, -nearest neighbor was based on spectral centroid, and power spectral features extracted by different wavelets (db4, db8, sym8, and coif5. The results of this study indicate that the best average accuracy achieved by subtractive fuzzy inference system classifier is 79.21% based on power spectral density feature extracted by sym8 wavelet which gave a good class discrimination under ANOVA test.

  3. A New Wavelet Threshold Function and Denoising Application

    Directory of Open Access Journals (Sweden)

    Lu Jing-yi


    Full Text Available In order to improve the effects of denoising, this paper introduces the basic principles of wavelet threshold denoising and traditional structures threshold functions. Meanwhile, it proposes wavelet threshold function and fixed threshold formula which are both improved here. First, this paper studies the problems existing in the traditional wavelet threshold functions and introduces the adjustment factors to construct the new threshold function basis on soft threshold function. Then, it studies the fixed threshold and introduces the logarithmic function of layer number of wavelet decomposition to design the new fixed threshold formula. Finally, this paper uses hard threshold, soft threshold, Garrote threshold, and improved threshold function to denoise different signals. And the paper also calculates signal-to-noise (SNR and mean square errors (MSE of the hard threshold functions, soft thresholding functions, Garrote threshold functions, and the improved threshold function after denoising. Theoretical analysis and experimental results showed that the proposed approach could improve soft threshold functions with constant deviation and hard threshold with discontinuous function problems. The proposed approach could improve the different decomposition scales that adopt the same threshold value to deal with the noise problems, also effectively filter the noise in the signals, and improve the SNR and reduce the MSE of output signals.

  4. Tracking facial feature points with Gabor wavelets and shape models

    NARCIS (Netherlands)

    McKenna, SJ; Gong, SG; Wurtz, RP; Tanner, J; Banin, D; Bigun, J; Chollet, G; Borgefors, G


    A feature-based approach to tracking rigid and non-rigid facial motion is described. Feature points are characterised using Gabor wavelets and can be individually tracked by phase-based displacement estimation. In order to achieve robust tracking a flexible shape model is used to impose global

  5. An improved adaptive wavelet shrinkage for ultrasound despeckling

    Indian Academy of Sciences (India)

    ... Perundurai 638 052, India. 2Department of Electronics and Communication Engineering, Kongunadu College of. Engineering and Technology, Thottiyam 621 ... ter achieves an improvement in terms of quantitative measures and in terms of visual quality of the images. Keywords. Wavelet; translation invariance; inter and ...

  6. Impedance cardiography signal denoising using discrete wavelet transform. (United States)

    Chabchoub, Souhir; Mansouri, Sofienne; Salah, Ridha Ben


    Impedance cardiography (ICG) is a non-invasive technique for diagnosing cardiovascular diseases. In the acquisition procedure, the ICG signal is often affected by several kinds of noise which distort the determination of the hemodynamic parameters. Therefore, doctors cannot recognize ICG waveform correctly and the diagnosis of cardiovascular diseases became inaccurate. The aim of this work is to choose the most suitable method for denoising the ICG signal. Indeed, different wavelet families are used to denoise the ICG signal. The Haar, Daubechies (db2, db4, db6, and db8), Symlet (sym2, sym4, sym6, sym8) and Coiflet (coif2, coif3, coif4, coif5) wavelet families are tested and evaluated in order to select the most suitable denoising method. The wavelet family with best performance is compared with two denoising methods: one based on Savitzky-Golay filtering and the other based on median filtering. Each method is evaluated by means of the signal to noise ratio (SNR), the root mean square error (RMSE) and the percent difference root mean square (PRD). The results show that the Daubechies wavelet family (db8) has superior performance on noise reduction in comparison to other methods.

  7. Higher-order graph wavelets and sparsity on circulant graphs (United States)

    Kotzagiannidis, Madeleine S.; Dragotti, Pier Luigi


    The notion of a graph wavelet gives rise to more advanced processing of data on graphs due to its ability to operate in a localized manner, across newly arising data-dependency structures, with respect to the graph signal and underlying graph structure, thereby taking into consideration the inherent geometry of the data. In this work, we tackle the problem of creating graph wavelet filterbanks on circulant graphs for a sparse representation of certain classes of graph signals. The underlying graph can hereby be data-driven as well as fixed, for applications including image processing and social network theory, whereby clusters can be modelled as circulant graphs, respectively. We present a set of novel graph wavelet filter-bank constructions, which annihilate higher-order polynomial graph signals (up to a border effect) defined on the vertices of undirected, circulant graphs, and are localised in the vertex domain. We give preliminary results on their performance for non-linear graph signal approximation and denoising. Furthermore, we provide extensions to our previously developed segmentation-inspired graph wavelet framework for non-linear image approximation, by incorporating notions of smoothness and vanishing moments, which further improve performance compared to traditional methods.

  8. Pitch detection of speech signals in noisy environment by wavelet (United States)

    Yip, Wing-kei; Leung, KwongSak; Wong, Kin-hong


    The pitch of voiced speech sounds provides very important information in speech analysis. Pitch estimation is a difficult task when unprevented noise exists. However experimental results have shown that even robust pitch detection techniques fail in noisy environment with periodic patterns such as noise generated by machines. Wavelet transform, with its special properties in time frequency relation, can be used to detect pitch with remarkable advantage in noise resistance. In wavelet signal analysis, the modulus of the transform have been used extensively, however, we found that the phase information is equally important especially for pitch detection. Since the phase spectrum is always intensive to noise, a more promising pitch period can be obtained from the phase diagram. Properties of the phase pattern in wavelet transform are investigated and the result is applied to construct a robust pitch detector. In our first test, the detector is employed to detect the pitches of a set of speech signals with white noise. We found that our approach clearly outperforms other non-wavelet methods with low signal-to-noise ratio. Sinusoidal noise with different frequency levels is used in the second test. Simulation results have shown that our system works quite stable in such an environment.

  9. Assessing heart rate variability through wavelet-based statistical measures. (United States)

    Wachowiak, Mark P; Hay, Dean C; Johnson, Michel J


    Because of its utility in the investigation and diagnosis of clinical abnormalities, heart rate variability (HRV) has been quantified with both time and frequency analysis tools. Recently, time-frequency methods, especially wavelet transforms, have been applied to HRV. In the current study, a complementary computational approach is proposed wherein continuous wavelet transforms are applied directly to ECG signals to quantify time-varying frequency changes in the lower bands. Such variations are compared for resting and lower body negative pressure (LBNP) conditions using statistical and information-theoretic measures, and compared with standard HRV metrics. The latter confirm the expected lower variability in the LBNP condition due to sympathetic nerve activity (e.g. RMSSD: p=0.023; SDSD: p=0.023; LF/HF: p=0.018). Conversely, using the standard Morlet wavelet and a new transform based on windowed complex sinusoids, wavelet analysis of the ECG within the observed range of heart rate (0.5-1.25Hz) exhibits significantly higher variability, as measured by frequency band roughness (Morlet CWT: p=0.041), entropy (Morlet CWT: p=0.001), and approximate entropy (Morlet CWT: p=0.004). Consequently, this paper proposes that, when used with well-established HRV approaches, time-frequency analysis of ECG can provide additional insights into the complex phenomenon of heart rate variability. Copyright © 2016. Published by Elsevier Ltd.

  10. A Wavelet-Based Optimization Method for Biofuel Production

    Directory of Open Access Journals (Sweden)

    Maurizio Carlini


    Full Text Available On a global scale many countries are still heavily dependent on crude oil to produce energy and fuel for transport, with a resulting increase of atmospheric pollution. A possible solution to obviate this problem is to find eco-sustainable energy sources. A potential choice could be the use of biodiesel as fuel. The work presented aims to characterise the transesterification reaction of waste peanut frying oil using colour analysis and wavelet analysis. The biodiesel production, with the complete absence of mucilages, was evaluated through a suitable set of energy wavelet coefficients and scalograms. The physical characteristics of the biodiesel are influenced by mucilages. In particular the viscosity, that is a fundamental parameter for the correct use of the biodiesel, might be compromised. The presence of contaminants in the samples can often be missed by visual analysis. The low and high frequency wavelet analysis, by investigating the energy change of wavelet coefficient, provided a valid characterisation of the quality of the samples, related to the absence of mucilages, which is consistent with the experimental results. The proposed method of this work represents a preliminary analysis, before the subsequent chemical physical analysis, that can be develop during the production phases of the biodiesel in order to optimise the process, avoiding the presence of impurities in suspension in the final product.

  11. Haar Wavelet Operational Matrix Method for Fractional Oscillation Equations

    Directory of Open Access Journals (Sweden)

    Umer Saeed


    Full Text Available We utilized the Haar wavelet operational matrix method for fractional order nonlinear oscillation equations and find the solutions of fractional order force-free and forced Duffing-Van der Pol oscillator and higher order fractional Duffing equation on large intervals. The results are compared with the results obtained by the other technique and with exact solution.

  12. Application of the wavelet transform for speech processing (United States)

    Maes, Stephane


    Speaker identification and word spotting will shortly play a key role in space applications. An approach based on the wavelet transform is presented that, in the context of the 'modulation model,' enables extraction of speech features which are used as input for the classification process.

  13. Discrete wavelet transforms over finite sets which are translation invariant

    NARCIS (Netherlands)

    L. Kamstra


    textabstractThe discrete wavelet transform was originally a linear operator that works on signals that are modeled as functions from the integers into the real or complex numbers. However, many signals have discrete function values. This paper builds on two recent developments: the extension of

  14. Wavelet based denoising of power quality events for characterization

    African Journals Online (AJOL)


    Angrisani L., Daponte P., D'Apuuo M. and Testa A., 1996, A new wavelet transform based procedure for electrical power quality analysis, Proceedings of the International Conference on Harmonics and Quality of Power (ICHQP), Las Vegas, Nevada,. USA, pp. 608-614. Bollen Math H.J., 2000, Understanding power quality ...

  15. Piecewise Tensor Product Wavelet Bases by Extensions and Approximation Rates

    NARCIS (Netherlands)

    Chegini, N.G.; Dahlke, S.; Friedrich, U.; Stevenson, R.; Dahlke, S.; Dahmen, W.; Griebel, M.; Hackbusch, W.; Ritter, K.; Schneider, R.; Schwab, C.; Yserentant, H.


    DIn this chapter, we present some of the major results that have been achieved in the context of the DFG-SPP project "Adaptive Wavelet Frame Methods for Operator Equations: Sparse Grids, Vector-Valued Spaces and Applications to Nonlinear Inverse Problems". This project has been concerned with

  16. Inverse problem in archeological magnetic surveys using complex wavelet transform. (United States)

    Saracco, G.; Moreau, F.; Mathe, P. E.; Hermitte, D.


    The wavelet transform applied to potential fields (electric, magnetic, or gravimetric, ...) has been now used from several years in geophysical applications, in particular to define the depth of potentiel sources verifying Poisson equation and responsible for potential anomalies measured at the ground surface. The complex continuous wavelet transform (CCWT) has been described, but the phase has not yet been exploited. (For these kinds of problem we construct a complex analyzing wavelet by Hilbert transforms of the Poisson or derivative of the Poisson wavelet which is real by definition). We show, here, that the phase of the CCWT provides useful information on the geometric and total magnetic inclination of the potential sources, as the modulus allows to characterize their depth and heterogenety degree. Regarding the properties of the phase compared to the modulus, it is more stable in presence of noise and we can defined it, independantly of the low level of energy of the signal. In this sense, information carried by the phase is more efficient to detect small objects or to separate close sources. We have applied a multi-scale analysis on magnetic measurements providing from a cesium magnetometer on the Fox-Amphoux site (France), to detect and localize buried structures like antik ovens. Conjointly, a rock magnetic study including susceptibility and magnetisations (induced or remanent) measurements give a better constrain on the magnetic parameters we want to extract.

  17. A Wavelet-Based Approach to Fall Detection

    Directory of Open Access Journals (Sweden)

    Luca Palmerini


    Full Text Available Falls among older people are a widely documented public health problem. Automatic fall detection has recently gained huge importance because it could allow for the immediate communication of falls to medical assistance. The aim of this work is to present a novel wavelet-based approach to fall detection, focusing on the impact phase and using a dataset of real-world falls. Since recorded falls result in a non-stationary signal, a wavelet transform was chosen to examine fall patterns. The idea is to consider the average fall pattern as the “prototype fall”.In order to detect falls, every acceleration signal can be compared to this prototype through wavelet analysis. The similarity of the recorded signal with the prototype fall is a feature that can be used in order to determine the difference between falls and daily activities. The discriminative ability of this feature is evaluated on real-world data. It outperforms other features that are commonly used in fall detection studies, with an Area Under the Curve of 0.918. This result suggests that the proposed wavelet-based feature is promising and future studies could use this feature (in combination with others considering different fall phases in order to improve the performance of fall detection algorithms.

  18. Wind Speed Forecasting by Wavelet Neural Networks: A Comparative Study

    Directory of Open Access Journals (Sweden)

    Chuanan Yao


    Full Text Available Due to the environmental degradation and depletion of conventional energy, much attention has been devoted to wind energy in many countries. The intermittent nature of wind power has had a great impact on power grid security. Accurate forecasting of wind speed plays a vital role in power system stability. This paper presents a comparison of three wavelet neural networks for short-term forecasting of wind speed. The first two combined models are two types of basic combinations of wavelet transform and neural network, namely, compact wavelet neural network (CWNN and loose wavelet neural network (LWNN in this study, and the third model is a new hybrid method based on the CWNN and LWNN models. The efficiency of the combined models has been evaluated by using actual wind speed from two test stations in North China. The results show that the forecasting performances of the CWNN and LWNN models are unstable and are affected by the test stations selected; the third model is far more accurate than the other forecasting models in spite of the drawback of lower computational efficiency.

  19. Wavelet-Coded OFDM for Next Generation Mobile Communications

    DEFF Research Database (Denmark)

    Cavalcante, Lucas Costa Pereira; Vegas Olmos, Juan José; Tafur Monroy, Idelfonso


    efficiency. The results show that the Wavelet-Coded OFDM system achieves a BER of 10−3 with nearly 6 dB less SNR than the convolutional coded OFDM system in frequency selective channels with a normalized channel response variation rate of ζ = 10−4.The proposed system fits as a key enabler for the use of mm-wave...

  20. Wavelet Transformation for Damage Identication in Wind Turbine Blades

    DEFF Research Database (Denmark)

    Ulriksen, Martin Dalgaard; Skov, Jonas falk; Kirkegaard, Poul Henning


    -damage mode shapes are derived through modal analysis and subsequently analyzed with continuous two-dimensional wavelet transformation for damage identification, namely detection, localization and assessment. It is found that valid damage identification is obtained even when utilizing the mode shape...

  1. Evaluating Interpersonal Synchrony: Wavelet Transform Toward an Unstructured Conversation. (United States)

    Fujiwara, Ken; Daibo, Ikuo


    This study examined whether interpersonal synchrony could be extracted using spectrum analysis (i.e., wavelet transform) in an unstructured conversation. Sixty-two female undergraduates were randomly paired and they engaged in a 6-min unstructured conversation. Interpersonal synchrony was evaluated by calculating the cross-wavelet coherence of the time-series movement data, extracted using a video-image analysis software. The existence of synchrony was tested using a pseudo-synchrony paradigm. In addition, the frequency at which the synchrony occurred and the distribution of the relative phase was explored. The results showed that the value of cross-wavelet coherence was higher in the experimental participant pairs than in the pseudo pairs. Further, the coherence value was higher in the frequency band under 0.5 Hz. These results support the validity of evaluating interpersonal synchron Behavioral mimicry and interpersonal syyby using wavelet transform even in an unstructured conversation. However, the role of relative phase was not clear; there was no significant difference between each relative-phase region. The theoretical contribution of these findings to the area of interpersonal coordination is discussed.

  2. WaveJava: Wavelet-based network computing (United States)

    Ma, Kun; Jiao, Licheng; Shi, Zhuoer


    Wavelet is a powerful theory, but its successful application still needs suitable programming tools. Java is a simple, object-oriented, distributed, interpreted, robust, secure, architecture-neutral, portable, high-performance, multi- threaded, dynamic language. This paper addresses the design and development of a cross-platform software environment for experimenting and applying wavelet theory. WaveJava, a wavelet class library designed by the object-orient programming, is developed to take advantage of the wavelets features, such as multi-resolution analysis and parallel processing in the networking computing. A new application architecture is designed for the net-wide distributed client-server environment. The data are transmitted with multi-resolution packets. At the distributed sites around the net, these data packets are done the matching or recognition processing in parallel. The results are fed back to determine the next operation. So, the more robust results can be arrived quickly. The WaveJava is easy to use and expand for special application. This paper gives a solution for the distributed fingerprint information processing system. It also fits for some other net-base multimedia information processing, such as network library, remote teaching and filmless picture archiving and communications.

  3. Discovering the Merit of the Wavelet Transform for Object Classification (United States)


    Targeting Covert Messages: A Unique Approach for Detecting Novel Steganography . MS thesis, AFIT/GCE/ENG/03-02, Graduate School of Engineering, Air...Matl02] Math Works. MATLAB User’s Guide. 2002. [Mend01] Mendenhall, M. Wavelet-Based Audio Embedding and Audio /Video Compression. MS

  4. Investment horizon heterogeneity and wavelet: Overview and further research directions (United States)

    Chakrabarty, Anindya; De, Anupam; Gunasekaran, Angappa; Dubey, Rameshwar


    Wavelet based multi-scale analysis of financial time series has attracted much attention, lately, from both the academia and practitioners from all around the world. The unceasing metamorphosis of the discipline of finance from its humble beginning as applied economics to the more sophisticated depiction as applied physics and applied psychology has revolutionized the way we perceive the market and its complexities. One such complexity is the presence of heterogeneous horizon agents in the market. In this context, we have performed a generous review of different aspects of horizon heterogeneity that has been successfully elucidated through the synergy between wavelet theory and finance. The evolution of wavelet has been succinctly delineated to bestow necessary information to the readers who are new to this field. The migration of wavelet into finance and its subsequent branching into different sub-divisions have been sketched. The pertinent literature on the impact of horizon heterogeneity on risk, asset pricing and inter-dependencies of the financial time series are explored. The significant contributions are collated and classified in accordance to their purpose and approach so that potential researcher and practitioners, interested in this subject, can be benefited. Future research possibilities in the direction of "agency cost mitigation" and "synergy between econophysics and behavioral finance in stock market forecasting" are also suggested in the paper.

  5. Study on serum fluorescence spectra based on wavelet transform ...

    African Journals Online (AJOL)

    Serum fluorescence emission intensity is closely related with the excitation wavelength; when the excitation wavelength is 230 nm, the blood lipid concentration and fluorescence intensity was significantly correlated. On the contrary, blood sugar was almost with no effect on the strength. Wavelet analysis was used in signal ...

  6. Recruiting leaders: an analysis of leadership advertisements

    NARCIS (Netherlands)

    den Hartog, D.N.; Caley, A.; Dewe, P.


    Recruiting the right leaders is an important challenge for organisations. How do organisations find these leaders? This article looks at the recruitment of leaders through advertisements. We address to what extent the 'vocabulary of leadership' originating in influential leadership theories is

  7. The Conductor as Servant-Leader. (United States)

    Wis, Ramona M.


    Focuses on how conductors can gain leadership skills. Discusses the process of becoming a leader, beginning with developing a personal philosophy. Describes the differences between leadership and management, a specific approach to leadership called the servant-leader, and the characteristics of a servant-leader. Includes a bibliography of…

  8. Addressing Deficiencies in Army Civilian Leader Development (United States)


    competencies the Army and Nation requires. A well managed , comparable, and integrated Army leader training, education, and development framework, designed...Leavenworth, KS or Fort Belvoir, VA. The Intermediate Course targets Army civilian leaders who already reside in supervisory, management , or project...Leadership and Management Program (DLAMP), a competitively selected DOD- sponsored and DOD–funded leader development program that provided enhanced

  9. A Phenomenology of Outdoor Education Leader Experiences (United States)

    Field, Stephanie C.; Lauzon, Lara L.; Meldrum, John T.


    Limited qualitative research exists on the experiences of outdoor education leaders. The purpose of this phenomenological study was to explore the job-related experiences of outdoor education leaders within and outside the workplace. Five participants who had experience as outdoor education leaders completed in-depth, one-on-one interviews about…

  10. Wavelet Transforms of Flickering Light Curves in Cataclysmic Variables (United States)

    Fritz, T.; Bruch, A.

    The flickering in CVs is composed of a stochastic superposition of flares, causing continuous erratic magnitude variations between a few times $0.01$ mag up to $>1$ mag, depending on the observed system (Bruch 1992). Power spectra based on Fourier transformations rise continuously from high to low frequencies (red noise). However, Fourier techniques -- based on sinusoids as fundamental functions -- are not ideally suited to analyse flickering. Since flickering flares are not sinusoidal, frequencies are smeared out over a large range, making it difficult to detect deviations from smooth distribution functions. Rather than sinusoidal the flare shape is triangular with a symmetrical rise and decline (albeit occasionally with strong deviations; Bruch 1992). Therefore a triangular base function would be more appropriate for analysing the collective properties of the flickering. This suggests that a wavelet-transformation should be well suited for this purpose since its base functions -- the wavelets -- can be chosen to enhance particular structures in the investigated signal. Some known wavelets have shapes well resembling flickering flares. We have applied a discrete wavelet transformation to 843 light curves of 75 CVs. Minimization of the information entropy showed the $C12$ coiflet to be the best suited wavelet for the study of flickering. The use of orthonormal bases enables a mathematically rigorous treatment of noise sources such as Poisson noise and atmospheric scintillation. While the wavelet transformation is a representation of the signal in frequency {\\it and\\/} time, we are not interested in exactly when a flare occurs in a light curve. Therefore, we use the scalegram (Scargle et al.\\ 1993), which is the mean square sum of the wavelet coefficients at a given time scale -- basically the strength of the signal -- as a function of the time scale, to characterize the flickering. The normalized scalegram measures the power of the flickering in relation to the

  11. Followers feel valued - When leaders' regulatory focus makes leaders exhibit behavior that fits followers' regulatory focus

    NARCIS (Netherlands)

    Hamstra, M.R.W.; Sassenberg, K.; van Yperen, N.W.; Wisse, B.


    When do followers feel valued by their leader? We propose that leaders' regulatory focus can make followers feel valued when leaders' regulatory focus is the same as followers' regulatory focus, that is, when there is regulatory fit between leaders and followers. We further propose that the reason

  12. Followers feel valued : When leaders' regulatory focus makes leaders exhibit behavior that fits followers' regulatory focus

    NARCIS (Netherlands)

    Hamstra, Melvyn; Sassenberg, K.; Van Yperen, Nico W.; Wisse, Barbara

    When do followers feel valued by their leader? We propose that leaders' regulatory focus can make followers feel valued when leaders' regulatory focus is the same as followers' regulatory focus, that is, when there is regulatory fit between leaders and followers. We further propose that the reason

  13. Kansas nurse leader residency programme: advancing leader knowledge and skills. (United States)

    Shen, Qiuhua; Peltzer, Jill; Teel, Cynthia; Pierce, Janet


    To evaluate the effectiveness of the Kansas Nurse Leader Residency (KNLR) programme in improving nurses' leadership knowledge and skills and its acceptability, feasibility and fidelity. The Future of Nursing Report (Institute of Medicine, 2011) calls for nurses to lead change and advance health. The 6-month KNLR programme was developed by the Kansas Action Coalition to support nurses' leadership development. Nurses (n = 36) from four nursing specialties (acute care, long-term care, public health and school health) participated in the programme. The adapted Leader Knowledge and Skill Inventory was used to assess leadership knowledge and skills. Programme acceptability, feasibility and implementation fidelity also were evaluated. The programme completion rate was 67.7% (n = 24). Programme completers had significantly improved self-assessed and mentor-assessed leadership knowledge and skills (p programme gains were maintained 3 months after programme completion. The KNLR programme effectively improved leadership knowledge and skills and was positively evaluated by participants. The implementation of the KNLR programme using a hybrid format of in-person sessions and online modules was feasible across four specialty areas in both rural and urban regions. The next steps include the development of an advanced programme. Residency programmes for new nurse leaders are critical for successful transition into management positions. © 2017 John Wiley & Sons Ltd.

  14. Bayesian wavelet PCA methodology for turbomachinery damage diagnosis under uncertainty (United States)

    Xu, Shengli; Jiang, Xiaomo; Huang, Jinzhi; Yang, Shuhua; Wang, Xiaofang


    Centrifugal compressor often suffers various defects such as impeller cracking, resulting in forced outage of the total plant. Damage diagnostics and condition monitoring of such a turbomachinery system has become an increasingly important and powerful tool to prevent potential failure in components and reduce unplanned forced outage and further maintenance costs, while improving reliability, availability and maintainability of a turbomachinery system. This paper presents a probabilistic signal processing methodology for damage diagnostics using multiple time history data collected from different locations of a turbomachine, considering data uncertainty and multivariate correlation. The proposed methodology is based on the integration of three advanced state-of-the-art data mining techniques: discrete wavelet packet transform, Bayesian hypothesis testing, and probabilistic principal component analysis. The multiresolution wavelet analysis approach is employed to decompose a time series signal into different levels of wavelet coefficients. These coefficients represent multiple time-frequency resolutions of a signal. Bayesian hypothesis testing is then applied to each level of wavelet coefficient to remove possible imperfections. The ratio of posterior odds Bayesian approach provides a direct means to assess whether there is imperfection in the decomposed coefficients, thus avoiding over-denoising. Power spectral density estimated by the Welch method is utilized to evaluate the effectiveness of Bayesian wavelet cleansing method. Furthermore, the probabilistic principal component analysis approach is developed to reduce dimensionality of multiple time series and to address multivariate correlation and data uncertainty for damage diagnostics. The proposed methodology and generalized framework is demonstrated with a set of sensor data collected from a real-world centrifugal compressor with impeller cracks, through both time series and contour analyses of vibration

  15. Cumulative Effect of Depression on Dementia Risk

    Directory of Open Access Journals (Sweden)

    J. Olazarán


    Full Text Available Objective. To analyze a potential cumulative effect of life-time depression on dementia and Alzheimer’s disease (AD, with control of vascular factors (VFs. Methods. This study was a subanalysis of the Neurological Disorders in Central Spain (NEDICES study. Past and present depression, VFs, dementia status, and dementia due to AD were documented at study inception. Dementia status was also documented after three years. Four groups were created according to baseline data: never depression (nD, past depression (pD, present depression (prD, and present and past depression (prpD. Logistic regression was used. Results. Data of 1,807 subjects were investigated at baseline (mean age 74.3, 59.3% women, and 1,376 (81.6% subjects were evaluated after three years. The prevalence of dementia at baseline was 6.7%, and dementia incidence was 6.3%. An effect of depression was observed on dementia prevalence (OR [CI 95%] 1.84 [1.01–3.35] for prD and 2.73 [1.08–6.87] for prpD, and on dementia due to AD (OR 1.98 [0.98–3.99] for prD and OR 3.98 [1.48–10.71] for prpD (fully adjusted models, nD as reference. Depression did not influence dementia incidence. Conclusions. Present depression and, particularly, present and past depression are associated with dementia at old age. Multiple mechanisms, including toxic effect of depression on hippocampal neurons, plausibly explain these associations.

  16. A pebble count procedure for assessing watershed cumulative effects (United States)

    Gregory S. Bevenger; Rudy M. King


    Land mangement activities can result in the delivery of fine sediment to streams. Over time, such delivery can lead to cumulative impacts to the aquactic ecosystem. Because numerous laws require Federal land managers to analyze watershed cumulative effects, field personnel need simple monitoring procedures that can be used directly and consistently. One approach to...

  17. A Framework for Treating Cumulative Trauma with Art Therapy (United States)

    Naff, Kristina


    Cumulative trauma is relatively undocumented in art therapy practice, although there is growing evidence that art therapy provides distinct benefits for resolving various traumas. This qualitative study proposes an art therapy treatment framework for cumulative trauma derived from semi-structured interviews with three art therapists and artistic…

  18. 25. Cumulative effects assessment impact thresholds: myths and realities (United States)

    Robert R. Ziemer


    A cumulative impact has been commonly defined as: ""...the impact on the environment which results from the incremental impact of the action when added to other past, present, and reasonably foreseeable future actions regardless of what agency or person undertakes such other actions. Cumulative impacts can result from individually minor but collectively...

  19. Cumulative Effects of Human Activities on Marine Mammal Populations (United States)


    related fields that are exploring approaches to dealing with cumulative effects ; for example, terrestrial ecology and human health . IMPACT/ application on laws regulating anthropogenic noise , pollutants , etc. RELATED PROJECTS None. ...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Cumulative Effects of Human Activities on Marine Mammal

  20. Cumulative Estrogen Exposure and Prospective Memory in Older Women (United States)

    Hesson, Jacqueline


    This study looked at cumulative lifetime estrogen exposure, as estimated with a mathematical index (Index of Cumulative Estrogen Exposure (ICEE)) that included variables (length of time on estrogen therapy, age at menarche and menopause, postmenopausal body mass index, time since menopause, nulliparity and duration of breastfeeding) known to…