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Wavelet transform

Yana Su, Yongzhong Sha, Guangyu Zhai, Shengliang Zong, Jiehua Jia
For a long-period comparative analysis of air pollution in coastal and inland cities, we analyzed the continuous Morlet wavelet transform on the time series of a 5274-day air pollution index in Shanghai and Lanzhou during 15 years and studied the multi-scale variation characteristic, main cycle, and impact factor of the air pollution time series. The analysis showed that (1) air pollution in the two cities was non-stationary and nonlinear, had multiple timescales, and exhibited the characteristics of high in winter and spring and low in summer and autumn...
April 21, 2017: Environmental Science and Pollution Research International
Miguel Martínez-Iniesta, Juan Ródenas, Raúl Alcaraz, José J Rieta
Atrial fibrillation (AF) is the most common arrhythmia in clinical practice with an increasing prevalence of about 15% in the elderly. Despite other alternatives, catheter ablation is currently considered as the first-line therapy for the treatment of AF. This strategy relies on cardiac electrophysiology systems, which use intracardiac electrograms (EGM) as the basis to determine the cardiac structures contributing to sustain the arrhythmia. However, the noise-free acquisition of these recordings is impossible and they are often contaminated by different perturbations...
April 18, 2017: Annals of Biomedical Engineering
C J Keylock
An algorithm is described that can generate random variants of a time series while preserving the probability distribution of original values and the pointwise Hölder regularity. Thus, it preserves the multifractal properties of the data. Our algorithm is similar in principle to well-known algorithms based on the preservation of the Fourier amplitude spectrum and original values of a time series. However, it is underpinned by a dual-tree complex wavelet transform rather than a Fourier transform. Our method, which we term the iterated amplitude adjusted wavelet transform can be used to generate bootstrapped versions of multifractal data, and because it preserves the pointwise Hölder regularity but not the local Hölder regularity, it can be used to test hypotheses concerning the presence of oscillating singularities in a time series, an important feature of turbulence and econophysics data...
March 2017: Physical Review. E
Ganggang Dong, Gangyao Kuang, Na Wang, Wei Wang
Automatic target recognition has been studied widely over the years, yet it is still an open problem. The main obstacle consists in extended operating conditions, e.g., depression angle change, configuration variation, articulation, occlusion. To deal with them, this paper proposes a new classification strategy. We develop a new representation model via the steerable wavelet frames. The proposed representation model is entirely viewed as an element on Grassmann manifolds. To achieve target classification, we embed Grassmann manifolds into an implicit Reproducing Kernel Hilbert Space (RKHS), where the kernel sparse learning can be applied...
April 7, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Arash Pourtaherian, Harm Scholten, Lieneke Kusters, Svitlana Zinger, Nenad Mihajlovic, Alexander Kolen, Fei Zou, Gary Ng, Hendrikus Korsten, Peter de With
Ultrasound-guided medical interventions are broadly applied in diagnostics and therapy, e.g. regional anesthesia or ablation. A guided intervention using 2D ultrasound is challenging due to the poor instrument visibility, limited field of view and the multi-fold coordination of the medical instrument and ultrasound plane. Recent 3D ultrasound transducers can improve the quality of the image-guided intervention if an automated detection of the needle is used. In this paper, we present a novel method for detecting medical instruments in 3D ultrasound data that is solely based on image processing techniques and validated on various ex-vivo and in-vivo datasets...
April 7, 2017: IEEE Transactions on Medical Imaging
Onder Aydemir
There are various kinds of brain monitoring techniques, including local field potential, near-infrared spectroscopy, magnetic resonance imaging (MRI), positron emission tomography, functional MRI, electroencephalography (EEG), and magnetoencephalography. Among those techniques, EEG is the most widely used one due to its portability, low setup cost, and noninvasiveness. Apart from other advantages, EEG signals also help to evaluate the ability of the smelling organ. In such studies, EEG signals, which are recorded during smelling, are analyzed to determine the subject lacks any smelling ability or to measure the response of the brain...
April 14, 2017: Neural Computation
Nima Beheshtizadeh, Amir Mostafapour
In this article, acoustic emission method was used for monitoring of flexural loading of GFRP (Glass fiber/epoxy composite) and CFRP (Carbon fiber/epoxy composite) via one acoustical sensor. In order to signal processing, various methods were employed such as wavelet transform, Short time Fourier transform, Choi - Williams transform and etc. Using two signal processing methods, wavelet transform and Choi - Williams transform, for monitoring of GFRP and CFRP specimens, determines strengths and weaknesses of each method and appointed the best analysis for signal processing of three point bending load of this type of composites...
April 5, 2017: Ultrasonics
Nicolas Roehri, Francesca Pizzo, Fabrice Bartolomei, Fabrice Wendling, Christian-George Bénar
High-frequency oscillations (HFO) have been suggested as biomarkers of epileptic tissues. While visual marking of these short and small oscillations is tedious and time-consuming, automatic HFO detectors have not yet met a large consensus. Even though detectors have been shown to perform well when validated against visual marking, the large number of false detections due to their lack of robustness hinder their clinical application. In this study, we developed a validation framework based on realistic and controlled simulations to quantify precisely the assets and weaknesses of current detectors...
2017: PloS One
Junbo Long, Haibin Wang, Daifeng Zha, Peng Li, Huicheng Xie, Lili Mao
Stockwell transform(ST) time-frequency representation(ST-TFR) is a time frequency analysis method which combines short time Fourier transform with wavelet transform, and ST time frequency filtering(ST-TFF) method which takes advantage of time-frequency localized spectra can separate the signals from Gaussian noise. The ST-TFR and ST-TFF methods are used to analyze the fault signals, which is reasonable and effective in general Gaussian noise cases. However, it is proved that the mechanical bearing fault signal belongs to Alpha(α) stable distribution process(1 < α < 2) in this paper, even the noise also is α stable distribution in some special cases...
2017: PloS One
C Scheel, I Traulsen, W Auer, K Müller, E Stamer, J Krieter
The objective of this study was to develop an automated monitoring system to detect lameness in group-housed sows early and reliably on the basis of acceleration data sampled from ear tags. To this end, acceleration data from ear tags were acquired from an experimental system deployed at the Futterkamp Agriculture Research Farm from May 2012 until November 2013. The developed method performs a wavelet transform for each individual sow's time series of total acceleration. Feature series are then computed by locally estimating the energy, variation and variance in a small moving window...
April 10, 2017: Animal: An International Journal of Animal Bioscience
Luis Antonio Salazar-Licea, Jesús Carlos Pedraza-Ortega, Alberto Pastrana-Palma, Marco A Aceves-Fernandez
BACKGROUND AND OBJECTIVE: There are many work related with segmentation techniques, including nearest neighbor algorithm, fuzzy rules, morphological filters, image entropy, thresholding, machine learning, wavelet analysis, and so on. Such methods carry out the segmentation, but take a lot of processing time by modifying the content of the image or showing discern problems in homogeneous areas, and the segmentation technique is designed to work efficiently only with the techniques used...
May 2017: Computer Methods and Programs in Biomedicine
Tianhua Chen, Shuo Zhao, Siqi Shao, Siqun Zheng
The heart sound is the characteristic signal of cardiovascular health status. The objective of this project is to explore the correlation between Wavelet Transform and noise performance of heart sound and the adaptability of classifying heart sound using bispectrum estimation. Since the wavelet has multi-scale and multi-resolution characteristics, in this paper, the heart sound signal with different frequency ranges is decomposed through wavelet and displayed on different scales of the resolving wavelet result...
March 2017: Saudi Journal of Biological Sciences
Xu Ma, Dongxiang Shi, Zhiqiang Wang, Yanqiu Li, Gonzalo R Arce
This paper proposes to use the a-priori knowledge of the target layout patterns to design data-adaptive compressive sensing (CS) methods for efficient source optimization (SO) in lithography systems. A set of monitoring pixels are selected from the target layout based on blue noise random patterns. The SO is then formulated as an under-determined linear problem to improve image fidelity according to the monitoring pixels. Adaptive projections are then designed, based on the a-priori knowledge of the target layout, in order to further reduce the dimension of the optimization problem, while trying to retain the SO performance...
March 20, 2017: Optics Express
Rui Song, Xiyuan Chen
The fiber optic gyroscope (FOG), one version of an all solid-state rotation sensor, has been widely used in navigation and position applications. However, the elastic-optic effect of fiber will introduce a non-negligible error in the output of FOG in a vibration and shock environment. To overcome the limitations of mechanism structure improvement methods and the traditional nonlinear analysis approaches, a hybrid algorithm of an optimized local mean decomposition-kernel principal component analysis (OLMD-KPCA) method is proposed in this paper...
March 10, 2017: Applied Optics
Nilesh Bhaskarrao Bahadure, Arun Kumar Ray, Har Pal Thethi
The segmentation, detection, and extraction of infected tumor area from magnetic resonance (MR) images are a primary concern but a tedious and time taking task performed by radiologists or clinical experts, and their accuracy depends on their experience only. So, the use of computer aided technology becomes very necessary to overcome these limitations. In this study, to improve the performance and reduce the complexity involves in the medical image segmentation process, we have investigated Berkeley wavelet transformation (BWT) based brain tumor segmentation...
2017: International Journal of Biomedical Imaging
Jian Zhang, Dibo Hou, Ke Wang, Pingjie Huang, Guangxin Zhang, Hugo Loáiciga
The detection of organic contaminants in water distribution systems is essential to protect public health from potential harmful compounds resulting from accidental spills or intentional releases. Existing methods for detecting organic contaminants are based on quantitative analyses such as chemical testing and gas/liquid chromatography, which are time- and reagent-consuming and involve costly maintenance. This study proposes a novel procedure based on discrete wavelet transform and principal component analysis for detecting organic contamination events from ultraviolet spectral data...
April 1, 2017: Environmental Science and Pollution Research International
Sohag Biswas, Bhabani S Mallik
The fluctuation dynamics of amine stretching frequencies, hydrogen bonds, dangling N-D bonds, and the orientation profile of the amine group of methylamine (MA) were investigated under ambient conditions by means of dispersion-corrected density functional theory-based first principles molecular dynamics (FPMD) simulations. Along with the dynamical properties, various equilibrium properties such as radial distribution function, spatial distribution function, combined radial and angular distribution functions and hydrogen bonding were also calculated...
April 12, 2017: Physical Chemistry Chemical Physics: PCCP
Joel E W Koh, U Rajendra Acharya, Yuki Hagiwara, U Raghavendra, Jen Hong Tan, S Vinitha Sree, Sulatha V Bhandary, A Krishna Rao, Sobha Sivaprasad, Kuang Chua Chua, Augustinus Laude, Louis Tong
Vision is paramount to humans to lead an active personal and professional life. The prevalence of ocular diseases is rising, and diseases such as glaucoma, Diabetic Retinopathy (DR) and Age-related Macular Degeneration (AMD) are the leading causes of blindness in developed countries. Identifying these diseases in mass screening programmes is time-consuming, labor-intensive and the diagnosis can be subjective. The use of an automated computer aided diagnosis system will reduce the time taken for analysis and will also reduce the inter-observer subjective variabilities in image interpretation...
March 16, 2017: Computers in Biology and Medicine
A Ebrahimkhanlou, S Salamone
This paper presents a new acoustic emission (AE) source localization for isotropic plates with reflecting boundaries. This approach that has no blind spot leverages multimodal edge reflections to identify AE sources with only a single sensor. The implementation of the proposed approach involves three main steps. First, the continuous wavelet transform (CWT) and the dispersion curves of the fundamental Lamb wave modes are utilized to estimate the distance between an AE source and a sensor. This step uses a modal acoustic emission approach...
March 14, 2017: Ultrasonics
U Rajendra Acharya, Muthu Rama Krishnan Mookiah, Joel E W Koh, Jen Hong Tan, Sulatha V Bhandary, A Krishna Rao, Yuki Hagiwara, Chua Kuang Chua, Augustinus Laude
The cause of diabetic macular edema (DME) is due to prolonged and uncontrolled diabetes mellitus (DM) which affects the vision of diabetic subjects. DME is graded based on the exudate location from the macula. It is clinically diagnosed using fundus images which is tedious and time-consuming. Regular eye screening and subsequent treatment may prevent the vision loss. Hence, in this work, a hybrid system based on Radon transform (RT), discrete wavelet transform (DWT) and discrete cosine transform (DCT) are proposed for an automated detection of DME...
March 19, 2017: Computers in Biology and Medicine
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