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Relevant bibliographies by topics / Wavelet-based functional model

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Academic literature on the topic 'Wavelet-based functional model'

Author: Grafiati

Published: 29 June 2021

Last updated: 11 February 2022

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Journal articles on the topic "Wavelet-based functional model"

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ABRAMOVICH, FELIX, ANESTIS ANTONIADIS, THEOFANIS SAPATINAS, and BRANI VIDAKOVIC. "OPTIMAL TESTING IN A FIXED-EFFECTS FUNCTIONAL ANALYSIS OF VARIANCE MODEL." International Journal of Wavelets, Multiresolution and Information Processing 02, no. 04 (2004): 323–49. http://dx.doi.org/10.1142/s0219691304000639.

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We consider the testing problem in a fixed-effects functional analysis of variance model. We test the null hypotheses that the functional main effects and the functional interactions are zeros against the composite nonparametric alternative hypotheses that they are separated away from zero in L2-norm and also possess some smoothness properties. We adapt the optimal (minimax) hypothesis testing procedures for testing a zero signal in a Gaussian "signal plus noise" model to derive optimal (minimax) non-adaptive and adaptive hypothesis testing procedures for the functional main effects and the fu

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Lee, Gihyoun, Seung Hyun Lee, Sang Hyeon Jin, and Jinung An. "Robust functional near infrared spectroscopy denoising using multiple wavelet shrinkage based on a hemodynamic response model." Journal of Near Infrared Spectroscopy 26, no. 2 (2018): 79–86. http://dx.doi.org/10.1177/0967033518757231.

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Functional near infrared spectroscopy can measure hemodynamic signals, and the results are similar to functional magnetic resonance imaging of blood-oxygen-level-dependent signals. Thus, functional near infrared spectroscopy can be employed to investigate brain activity by measuring the absorption of near infrared light through an intact skull. Recently, a general linear model, which is a standard method for functional magnetic resonance imaging, was applied to functional near infrared spectroscopy imaging analysis. However, the general linear model fails when functional near infrared spectros

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KABEER, V., and N. K. NARAYANAN. "WAVELET-BASED ARTIFICIAL LIGHT RECEPTOR MODEL FOR HUMAN FACE RECOGNITION." International Journal of Wavelets, Multiresolution and Information Processing 07, no. 05 (2009): 617–27. http://dx.doi.org/10.1142/s0219691309003124.

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This paper presents a novel biologically-inspired and wavelet-based model for extracting features of faces from face images. The biological knowledge about the distribution of light receptors, cones and rods, over the surface of the retina, and the way they are associated with the nerve ends for pattern vision forms the basis for the design of this model. A combination of classical wavelet decomposition and wavelet packet decomposition is used for simulating the functional model of cones and rods in pattern vision. The paper also describes the experiments performed for face recognition using t

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Xie, Shengkun, and Sridhar Krishnan. "Wavelet-based sparse functional linear model with applications to EEGs seizure detection and epilepsy diagnosis." Medical & Biological Engineering & Computing 51, no. 1-2 (2012): 49–60. http://dx.doi.org/10.1007/s11517-012-0967-8.

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CUI, YIBO, CHI ZHANG, LINYUAN WANG, BIN YAN, and LI TONG. "DENSE-GWP: AN IMPROVED PRIMARY VISUAL ENCODING MODEL BASED ON DENSE GABOR FEATURES." Journal of Mechanics in Medicine and Biology 21, no. 05 (2021): 2140017. http://dx.doi.org/10.1142/s0219519421400170.

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Brain visual encoding models based on functional magnetic resonance imaging are growing increasingly popular. The Gabor wavelet pyramid model (GWP) is a classic example, exhibiting a good prediction performance for the primary visual cortex (V1, V2, and V3). However, the local variations in the visual stimulation are quite convoluted in terms of spatial frequency, orientation, and position, posing a challenge for visual encoding models. Whether the GWP model can thoroughly extract informative and effective features from visual stimulus remains unclear. To this end, this paper proposes a dense

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Jian, Zini, Xianpei Wang, Xueting Liu, Meng Tian, Quande Wang, and Jiangxi Xiao. "Research on BOLD-fMRI Data Denoising Based on Bayesian Estimation and Adaptive Wavelet Threshold." Oxidative Medicine and Cellular Longevity 2021 (February 5, 2021): 1–10. http://dx.doi.org/10.1155/2021/8819384.

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The acquisition of functional magnetic resonance imaging (fMRI) images of blood oxygen level-dependent (BOLD) effect and the signals to be analyzed is based on weak changes in the magnetic field caused by small changes in blood oxygen physiological levels, which are weak signals and complex in noise. In order to model and analyze the pathological and hemodynamic parameters of BOLD-fMRI images effectively, it is urgent to use effective signal analysis techniques to reduce the interference of noise and artifacts. In this paper, the noise characteristics of functional magnetic resonance imaging a

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Inoussa, Garba, Hui Peng, and Jun Wu. "Nonlinear time series modeling and prediction using functional weights wavelet neural network-based state-dependent AR model." Neurocomputing 86 (June 2012): 59–74. http://dx.doi.org/10.1016/j.neucom.2012.01.010.

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Al-Hiyali, Mohammed Isam, Norashikin Yahya, Ibrahima Faye, and Ahmed Faeq Hussein. "Identification of Autism Subtypes Based on Wavelet Coherence of BOLD FMRI Signals Using Convolutional Neural Network." Sensors 21, no. 16 (2021): 5256. http://dx.doi.org/10.3390/s21165256.

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The functional connectivity (FC) patterns of resting-state functional magnetic resonance imaging (rs-fMRI) play an essential role in the development of autism spectrum disorders (ASD) classification models. There are available methods in literature that have used FC patterns as inputs for binary classification models, but the results barely reach an accuracy of 80%. Additionally, the generalizability across multiple sites of the models has not been investigated. Due to the lack of ASD subtypes identification model, the multi-class classification is proposed in the present study. This study aim

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BARDET, JEAN-MARC, and PIERRE BERTRAND. "DEFINITION, PROPERTIES AND WAVELET ANALYSIS OF MULTISCALE FRACTIONAL BROWNIAN MOTION." Fractals 15, no. 01 (2007): 73–87. http://dx.doi.org/10.1142/s0218348x07003356.

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In some applications, for instance, finance, biomechanics, turbulence or internet traffic, it is relevant to model data with a generalization of a fractional Brownian motion for which the Hurst parameter H is dependent on the frequency. In this contribution, we describe the multiscale fractional Brownian motions which present a parameter H as a piecewise constant function of the frequency. We provide the main properties of these processes: long-memory and smoothness of the paths. Then we propose a statistical method based on wavelet analysis to estimate the different parameters and prove a fun

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Fernandez Rojas, Raul, Mingyu Liao, Julio Romero, Xu Huang, and Keng-Liang Ou. "Cortical Network Response to Acupuncture and the Effect of the Hegu Point: An fNIRS Study." Sensors 19, no. 2 (2019): 394. http://dx.doi.org/10.3390/s19020394.

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Acupuncture is a practice of treatment based on influencing specific points on the body by inserting needles. According to traditional Chinese medicine, the aim of acupuncture treatment for pain management is to use specific acupoints to relieve excess, activate qi (or vital energy), and improve blood circulation. In this context, the Hegu point is one of the most widely-used acupoints for this purpose, and it has been linked to having an analgesic effect. However, there exists considerable debate as to its scientific validity. In this pilot study, we aim to identify the functional connectivit

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Dissertations / Theses on the topic "Wavelet-based functional model"

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Tang, Man. "Statistical methods for variant discovery and functional genomic analysis using next-generation sequencing data." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/104039.

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The development of high-throughput next-generation sequencing (NGS) techniques produces massive amount of data, allowing the identification of biomarkers in early disease diagnosis and driving the transformation of most disciplines in biology and medicine. A greater concentration is needed in developing novel, powerful, and efficient tools for NGS data analysis. This dissertation focuses on modeling ``omics'' data in various NGS applications with a primary goal of developing novel statistical methods to identify sequence variants, find transcription factor (TF) binding patterns, and decode the

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Lin, Shih-Di, and 林士迪. "Design of Fuzzy-Cerebellar Model Articulation Controller Based on Wavelet Function for IM Direct Torque Control System." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/fuj8bc.

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碩士<br>國立臺北科技大學<br>電機工程系研究所<br>95<br>In this thesis, the Fuzzy Cerebellar Model Articulation PI Controller (FCMAPIC) is proposed, which was designed with the fuzzy cerebellar model articulation controller on the basis of the wavelet function for membership functions, and the projection algorithm in adaptive theory was adopted to tune the parameters. The advantages of the FCMAPIC include on-line PI parameters adjustment, rapid learning ability, and simple structure. The drawbacks of the conventional fixed-parameter PI controller are overcome. Based on the direct torque control (DTC), the spe

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Book chapters on the topic "Wavelet-based functional model"

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Xin, Xiu, and Xiaoyi Xiong. "Financial Distress Prediction of Chinese-Listed Companies Based on PCA and WNNs." In Global Applications of Pervasive and Ubiquitous Computing. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2645-4.ch023.

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The operating status of an enterprise is disclosed periodically in a financial statement. Financial distress prediction is important for business bankruptcy prevention, and various quantitative prediction methods based on financial ratios have been proposed. This paper presents a financial distress prediction model based on wavelet neural networks (WNNs). The transfer functions of the neurons in WNNs are wavelet base functions which are determined by dilation and translation factors. Back propagation algorithm was used to train the WNNs. Principal component analysis (PCA) method was used to reduce the dimension of the inputs of the WNNs. Multiple discriminate analysis (MDA), Logit, Probit, and WNNs were employed to a dataset selected from Chinese-listed companies. The results demonstrate that the proposed WNNs-based model performs well in comparison with the other three models.

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Conference papers on the topic "Wavelet-based functional model"

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"Predicting Molecular Functions in Plants using Wavelet-based Motifs." In International Conference on Bioinformatics Models, Methods and Algorithms. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004234201400145.

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Robertson, A. N., K. C. Park, and K. F. Alvin. "Identification of Structural Dynamics Models Using Wavelet-Generated Impulse Response Data." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0380.

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Abstract This paper addresses the use of discrete wavelet tranforms for the identification of structural dynamics models. First, the discrete temporal impulse response functions are obtained from vibration records by the discrete wavelet transforms (DWTs), which are then utilized for system realizations. From the realized state space models, structural modes, mode shapes and damping parameters are extracted. Attention has been focused on a careful comparison of the present DWT system identification approach to the FFT-based approach and a rational criterion for truncating realized singular val

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Wei, Huiming, G. H. Su, S. Z. Qiu, and Xingbo Yang. "Study on the Onset of Nucleate Boiling in Narrow Annular Channel by Using Wavelet and Wavelet Neural Network." In 17th International Conference on Nuclear Engineering. ASMEDC, 2009. http://dx.doi.org/10.1115/icone17-75475.

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In this study, the local modulus maxima of cubic B-spline wavelet transform are introduced to determine the location of onset of nucleate boiling (ONB). Wavelet transformation has the ability of representing a function and revealing the properties of the function in the joint local regions of the time frequency space. Based on wavelet and artificial neural network, a Wavelet Neural Network (WNN) model predicting ONB for upward flow in vertical narrow annuli with bilateral heating has been developed. The WNN mode combining the properties of the wavelet transform and the advantages of Artificial

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Daneshmand, Farhang, Abdolaziz Abdollahi, Mehdi Liaghat, and Yousef Bazargan Lari. "Free Vibration Analysis of Frame Structures Using BSWI Method." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-68417.

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Vibration analysis for complicated structures, or for problems requiring large numbers of modes, always requires fine meshing or using higher order polynomials as shape functions in conventional finite element analysis. Since it is hard to predict the vibration mode a priori for a complex structure, a uniform fine mesh is generally used which wastes a lot of degrees of freedom to explore some local modes. By the present wavelets element approach, the structural vibration can be analyzed by coarse mesh first and the results can be improved adaptively by multi-level refining the required parts o

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Rueda Villanoba, Sergio Alberto, and Carlos Borrás Pinilla. "Neural Network Based Fault Tolerant Control for a Semi-Active Suspension." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11516.

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Abstract In this study a Neural Network based fault tolerant control is proposed to accommodate oil leakages in a magnetorheological suspension system based in a half car dynamic model. This model consists of vehicle body (spring mass) connected by the MR suspension system to two lateral wheels (unsprung mass). The semi-active suspension system is a four states nonlinear model; it can be written as a state space representation. The main objectives of a suspension are: Isolate the chassis from road disturbances (passenger comfort) and maintain contact between tire and road to provide better man

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Miao, Qiang, and Dong Wang. "Fast Bayesian Inference on Optimal Wavelet Parameters for Bearing Fault Diagnosis." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-51394.

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Rolling element bearings are widely used in various machinery to support rotation shaft and they are prone to failures. Once a bearing fails, it accelerates failures of other adjacent components and results in unexpected machine breakdown. To prevent machine breakdown and reduce unnecessary economic loss, bearing fault must be detected as early as possible. Besides spectral kurtosis, empirical mode decomposition, cyclostationarity, etc., wavelet transform has proven to be an effective method for identification of different bearing faults because it aims to highlight the inner product between a

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Zuo, Hao, Xuefeng Chen, Zhibo Yang, and Laihao Yang. "Modeling of Lamb Wave Propagation in Beam-Like Structures via Wavelet Finite Element Method." In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-65366.

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Beam-like structure is known as one of crucial engineering structures in practical application of aerospace, vessel, civil and machinery. The damages have a great influence on machine performance and may cause a serious threat for security of mechanical structures and systems. Thus it is very significant to identify the damage of beam-like structures for security of mechanical structures and systems. This paper presents a novel application of wavelet finite element method (WFEM) in Lamb wave propagation of beam-like structures. The WFEM, adopting excellent B-spline wavelet on interval (BSWI) b

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Romeo, Francesco, Vincenzo Gattulli, and Francesco Benedettini. "Nonlinear Parametric Identification of Oscillating Cables Using Wavelets." In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/vib-21405.

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Abstract In the present study a wavelet-based procedure is applied for the parametric identification of a nonlinear discrete cable model on the basis of experimental data obtained from free-vibration dynamic tests. The 3D cable dynamics is described by two partial integro-differential equations in the transversal planar and nonplanar displacement components. By expanding such variables in series of linear eigenfunctions, a discrete model is obtained by applying a classical Galerkin procedure. The resulting set of nonlinear ODEs contains quadratic and cubic coupling terms. The core of the ident

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Hu, Dinghan, Jiuwen Cao, Xiaoping Lai, and Junbiao Liu. "Epileptic State Classification based on Intrinsic Mode Function and Wavelet Packet Decomposition." In 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2019. http://dx.doi.org/10.1109/embc.2019.8856282.

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Wang, Likun, Jian Li, Ke Peng, Shijiu Jin, and Zhuang Li. "Petroleum Pipe Leakage Detection and Location Embeded in SCADA." In 2004 International Pipeline Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/ipc2004-0717.

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With the increase of the age of the transport oil pipeline and the man-made destruction to pipeline, leaks are often found. The system for pipeline leakage detection and location must be established to find leakage and locate the leak positions to reduce serious environmental pollution and economic loss caused by leakage. The negative pressure wave method is an effective way to locate the leak position, because over 98 percent pipe leakage in China is paroxysmal. There is a SCADA (supervisory control and data acquisition) system to monitor operation for long transport petroleum pipe, but the f

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