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Wavelet transform

Azmat Ullah, Suheel Abdullah Malik, Khurram Saleem Alimgeer
In this paper, a hybrid heuristic scheme based on two different basis functions i.e. Log Sigmoid and Bernstein Polynomial with unknown parameters is used for solving the nonlinear heat transfer equations efficiently. The proposed technique transforms the given nonlinear ordinary differential equation into an equivalent global error minimization problem. Trial solution for the given nonlinear differential equation is formulated using a fitness function with unknown parameters. The proposed hybrid scheme of Genetic Algorithm (GA) with Interior Point Algorithm (IPA) is opted to solve the minimization problem and to achieve the optimal values of unknown parameters...
2018: PloS One
Hongmin Cai, Peihua Chen, Jiazhou Chen, Jiulun Cai, Yan Song, Guoqiang Han
Copy-number variations (CNVs) are associated with complex diseases and particular tumor types. Array-based comparative genomic hybridization (aCGH) is a common approach for the detection of CNVs. Traditional CNV detection methods for multiple aCGH samples mainly use batch samples to find common variations, not accounting for the individual characteristics of each sample. Accurately differentiating both the commonly shared and the individual CNV patterns is pivotal to identify cell populations, or to distinguish cell growth (as in cancer) from invasion of new cells...
February 2018: IEEE Transactions on Bio-medical Engineering
Andreu González-Calabuig, Xavier Cetó, Manel Del Valle
This work reports the applicability of a voltammetric sensor array able to quantify the content of 2,4-dinitrophenol, 4-nitrophenol, and picric acid in artificial samples using the electronic tongue (ET) principles. The ET is based on cyclic voltammetry signals, obtained from an array of metal disk electrodes and a graphite epoxy composite electrode, compressed using discrete wavelet transform with chemometric tools such as artificial neural networks (ANNs). ANNs were employed to build the quantitative prediction model...
January 13, 2018: Sensors
Qianying Liu, Bitian Wang, Ying Liu, Zeping Lv, Wenhao Li, Zengyong Li, Yubo Fan
A connectivity-based approach can highlight the network reorganization in the chronic phases after stroke and contributes to the development of therapeutic interventions. Using dynamic Bayesian inference, this study aimed to assess the effective connectivity(EC)in various frequency bands through the near-infrared spectroscopy(NIRS) method in subjects with cerebral infarction(CI). A phase-coupling model was established based on phase information extracted using the wavelet transform of NIRS signals. Coupling strength and the main coupling direction were estimated using dynamic Bayesian inference...
January 11, 2018: Neuroscience
Yingxia Liu, Ziad Saleh, Yulin Song, Maria Chan, Xiang Li, Chengyu Shi, Xin Qian, Xiaoli Tang
Segmentation of prostate Cone Beam CT (CBCT) images is an essential step towards real-time adaptive radiotherapy (ART). It is challenging for Calypso patients, as more artifacts generated by the beacon transponders are present on the images. We herein propose a novel wavelet-based segmentation algorithm for rectum, bladder, and prostate of CBCT images with implanted Calypso transponders. For a given CBCT, a Moving Window-Based Double Haar (MWDH) transformation is applied first to obtain the wavelet coefficients...
August 2017: International Journal of Medical Physics, Clinical Engineering and Radiation Oncology
Mahsa Khalili, Mahmoud Reza Sohrabi, Vahid Mirzabeygi, Nahid Torabi Ziaratgahi
Partial least squares (PLS), different families of continuous wavelet transform (CWT), and first derivative spectrophotometry (DS) techniques were studied for quantification of Sofosbuvir (SFB) and Ledipasvir (LDV) simultaneously without separation step. The components were dissolved in Acetonitrile and the spectral behaviors were evaluated in the range of 200 to 400nm. The ultraviolet (UV) absorbance of LDV exhibits no interferences between 300 and 400nm and it was decided to predict the LDV amount through the classic spectrophotometry (CS) method in this spectral region as well...
January 6, 2018: Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
M Ibrahim, C I Pardi, T W C Brown, P J McDonald
Improvement in the signal-to-noise ratio of Nuclear Magnetic Resonance (NMR) systems may be achieved either by increasing the signal amplitude or by decreasing the noise. The noise has multiple origins - not all of which are strictly "noise": incoherent thermal noise originating in the probe and pre-amplifiers, probe ring down or acoustic noise and coherent externally broadcast radio frequency transmissions. The last cannot always be shielded in open access experiments. In this paper, we show that pulsed, low radio-frequency data communications are a significant source of broadcast interference...
January 7, 2018: Journal of Magnetic Resonance
Pavel A Cheremkhin, Ekaterina A Kurbatova
Compression of digital holograms can significantly help with the storage of objects and data in 2D and 3D form, its transmission, and its reconstruction. Compression of standard images by methods based on wavelets allows high compression ratios (up to 20-50 times) with minimum losses of quality. In the case of digital holograms, application of wavelets directly does not allow high values of compression to be obtained. However, additional preprocessing and postprocessing can afford significant compression of holograms and the acceptable quality of reconstructed images...
January 1, 2018: Applied Optics
Christopher Moufawad El Achkar, Constanze Lenbole-Hoskovec, Anisoara Paraschiv-Ionescu, Kristof Major, Kamiar Aminian, Christophe Büla
The frequency and quality of sit-to-stand and stand-to-sit postural transitions decrease with age and are highly relevant for fall risk assessment. Accurate classification and characterization of these transitions in daily life of older adults are therefore needed. In this study, we propose to use instrumented shoes for postural transition classification as well as transition duration estimation from insole force signals. In the first part, data were collected with 10 older adults and 10 young participants performing transitions in the laboratory while wearing the instrumented shoes, without arm assistance...
January 12, 2018: Medical & Biological Engineering & Computing
Lyndia C Wu, Calvin Kuo, Jesus Loza, Mehmet Kurt, Kaveh Laksari, Livia Z Yanez, Daniel Senif, Scott C Anderson, Logan E Miller, Jillian E Urban, Joel D Stitzel, David B Camarillo
Accumulation of head impacts may contribute to acute and long-term brain trauma. Wearable sensors can measure impact exposure, yet current sensors do not have validated impact detection methods for accurate exposure monitoring. Here we demonstrate a head impact detection method that can be implemented on a wearable sensor for detecting field football head impacts. Our method incorporates a support vector machine classifier that uses biomechanical features from the time domain and frequency domain, as well as model predictions of head-neck motions...
December 21, 2017: Scientific Reports
Yue Hu, Xiaotong Tu, Fucai Li, Guang Meng
Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions...
January 7, 2018: Sensors
Andreu González-Calabuig, Manel Del Valle
This work reports the applicability of a voltammetric sensor array able to evaluate the content of the metabolites of the Brett defect: 4-ethylphenol, 4-ethylguaiacol and 4-ethylcatechol in spiked wine samples using the electronic tongue (ET) principles. The ET used cyclic voltammetry signals, obtained from an array of six graphite epoxy modified composite electrodes; these were compressed using Discrete Wavelet transform while chemometric tools, among these artificial neural networks (ANNs), were employed to build the quantitative prediction model...
March 1, 2018: Talanta
Apit Hemakom, Katarzyna Powezka, Valentin Goverdovsky, Usman Jaffer, Danilo P Mandic
A highly localized data-association measure, termed intrinsic synchrosqueezing transform (ISC), is proposed for the analysis of coupled nonlinear and non-stationary multivariate signals. This is achieved based on a combination of noise-assisted multivariate empirical mode decomposition and short-time Fourier transform-based univariate and multivariate synchrosqueezing transforms. It is shown that the ISC outperforms six other combinations of algorithms in estimating degrees of synchrony in synthetic linear and nonlinear bivariate signals...
December 2017: Royal Society Open Science
Tingting Liu, Ling Zhang, Shutao Wang, Yaoyao Cui, Yutian Wang, Lingfei Liu, Zhe Yang
Qualitative and quantitative analysis of polycyclic aromatic hydrocarbons (PAHs) was carried out by three-dimensional fluorescence spectroscopy combining with Alternating Weighted Residue Constraint Quadrilinear Decomposition (AWRCQLD). The experimental subjects were acenaphthene (ANA) and naphthalene (NAP). Firstly, in order to solve the redundant information of the three-dimensional fluorescence spectral data, the wavelet transform was used to compress data in preprocessing. Then, the four-dimensional data was constructed by using the excitation-emission fluorescence spectra of different concentration PAHs...
December 12, 2017: Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
Chu Zhang, Tingting Shen, Fei Liu, Yong He
We linked coffee quality to its different varieties. This is of interest because the identification of coffee varieties should help coffee trading and consumption. Laser-induced breakdown spectroscopy (LIBS) combined with chemometric methods was used to identify coffee varieties. Wavelet transform (WT) was used to reduce LIBS spectra noise. Partial least squares-discriminant analysis (PLS-DA), radial basis function neural network (RBFNN), and support vector machine (SVM) were used to build classification models...
December 31, 2017: Sensors
Yong Xia, Naren Wulan, Kuanquan Wang, Henggui Zhang
BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia. The incidence of AF increases with age, causing high risks of stroke and increased morbidity and mortality. Efficient and accurate diagnosis of AF based on the ECG is valuable in clinical settings and remains challenging. In this paper, we proposed a novel method with high reliability and accuracy for AF detection via deep learning. METHOD: The short-term Fourier transform (STFT) and stationary wavelet transform (SWT) were used to analyze ECG segments to obtain two-dimensional (2-D) matrix input suitable for deep convolutional neural networks...
December 15, 2017: Computers in Biology and Medicine
Qi Wei Oung, Hariharan Muthusamy, Shafriza Nisha Basah, Hoileong Lee, Vikneswaran Vijean
Parkinson's disease (PD) is a type of progressive neurodegenerative disorder that has affected a large part of the population till now. Several symptoms of PD include tremor, rigidity, slowness of movements and vocal impairments. In order to develop an effective diagnostic system, a number of algorithms were proposed mainly to distinguish healthy individuals from the ones with PD. However, most of the previous works were conducted based on a binary classification, with the early PD stage and the advanced ones being treated equally...
December 29, 2017: Journal of Medical Systems
Yanyan Yu, Yang Xiao, Jieyu Cheng, Bernard Chiu
Supersonic shear-wave elastography (SWE) has emerged as a useful imaging modality for breast lesion assessment. Regions of interest (ROIs) were required to be specified for extracting features that characterize malignancy of lesions. Although analyses have been performed in small rectangular ROIs identified manually by expert observers, the results were subject to observer variability and the analysis of small ROIs would potentially miss out important features available in other parts of the lesion. Recent investigations extracted features from the entire lesion segmented by B-mode ultrasound images either manually or semi-automatically, but lesion delineation using existing techniques is time-consuming and prone to variability as intensive user interactions are required...
December 15, 2017: Computers in Biology and Medicine
A Sharmila, Suman Aman Raj, Pandey Shashank, P Mahalakshmi
In this work, we have used a time-frequency domain analysis method called discrete wavelet transform (DWT) technique. This method stand out compared to other proposed methods because of its algorithmic elegance and accuracy. A wavelet is a mathematical function based on time-frequency analysis in signal processing. It is useful particularly because it allows a weak signal to be recovered from a noisy signal without much distortion. A wavelet analysis works by analysing the image and converting it to mathematical function which is decoded by the receiver...
December 18, 2017: Journal of Medical Engineering & Technology
J Reena Benjamin, T Jayasree
PURPOSE: In the medical field, radiologists need more informative and high-quality medical images to diagnose diseases. Image fusion plays a vital role in the field of biomedical image analysis. It aims to integrate the complementary information from multimodal images, producing a new composite image which is expected to be more informative for visual perception than any of the individual input images. The main objective of this paper is to improve the information, to preserve the edges and to enhance the quality of the fused image using cascaded principal component analysis (PCA) and shift invariant wavelet transforms...
December 18, 2017: International Journal of Computer Assisted Radiology and Surgery
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