Results 61 to 70 of about 84,910 (313)
Journal of Finance and Data Science, 2016 Many researchers documented that if stock markets' returns series are significantly skewed, linear-GARCH(1,1) grossly underestimates the forecast values of the returns. However, this study showed that the linear Maximal Overlap Discreet Wavelet Transform
Mohd Tahir Ismail +2 more
doaj +1 more source
Wavelet analysis of temporal data [PDF]
, 2008 This thesis considers the application of wavelets to problems involving multiple series of temporal data. Wavelets have proven to be highly effective at extracting frequency information from data.
Goodwin, David Alexander
core
Wavelet transform in stock prices forecasting and related financial data [PDF]
, 2023 The aim of this systematic review is to give attention towards the use of wavelet transform in denoising financial time series. This is important to deliver an accurate option pricing for the use of investors or other market practitioners. In this paper,
Abdullah, Mimi Hafizah +1 more
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A Compact Spin‐Coated Graphene UWB Antenna for Breast Tumor Detection
Advanced Engineering Materials, EarlyView.A compact, spin‐coated graphene ultra‐wideband patch antenna designed for breast tumor detection, capable of distinguishing between malignant and benign tumors. This innovative antenna can serve as an effective initial screening tool, particularly in resource‐limited settings such as rural areas, where access to advanced medical equipment like MRI and ...
Raja Rashidul Hasan +9 more
wiley +1 more source
Medical image denoising using dual tree complex thresholding wavelet transform and Wiener filter
Journal of King Saud University: Computer and Information Sciences, 2015 Image denoising is the process to remove the noise from the image naturally corrupted by the noise. The wavelet method is one among various methods for recovering infinite dimensional objects like curves, densities, images, etc.
Hilal Naimi +2 more
doaj +1 more source
Wavelet Estimators in Nonparametric Regression: A Comparative Simulation Study [PDF]
, 2001 Wavelet analysis has been found to be a powerful tool for the nonparametric estimation of spatially-variable objects. We discuss in detail wavelet methods in nonparametric regression, where the data are modelled as observations of a signal contaminated ...
Theofanis Sapatinas +5 more
core +1 more source
Karl Popper and the Mechanisms of Hydrogen Embrittlement
Advanced Engineering Materials, EarlyView.Representation of the beginning of loss of ductility rather than embrittlement. Small concentrations of hydrogen in a diffusible form within iron are well‐established to harm the mechanical integrity of steels. There are theories that attempt to explain the pernicious role of hydrogen.
H. K. D. H. Bhadeshia
wiley +1 more source
Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying
Advanced Engineering Materials, EarlyView.An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara +8 more
wiley +1 more source
Shock and Vibration, 2016 Effective signal processing in fault detection and diagnosis (FDD) is an important measure to prevent failure and accidents of machinery. To address the end distortion and frequency aliasing issues in conventional lifting wavelet transform, a Volterra ...
Lixiang Duan +4 more
doaj +1 more source
M-RWTL: Learning Signal-Matched Rational Wavelet Transform in Lifting Framework
IEEE Access, 2018 Transform learning is being extensively applied in several applications because of its ability to adapt to a class of the signals of interest. Often, a transform is learned using a large amount of training data, while only limited data may be available ...
Naushad Ansari, Anubha Gupta
doaj +1 more source