Search results for "wavelet."
showing 10 items of 327 documents
Volatility co-movements: a time scale decomposition analysis
2013
In this paper we investigate short-run co-movements before and after the Lehman Brothers’ collapse among the volatility series of US and a number of European countries. The series under investigation (implied and realized volatility) exhibit long-memory and, in order to avoid missspecification errors related to the parameterization of a long memory multivariate model, we rely on wavelet analysis. More specifically, we retrieve the time series of wavelet coefficients for each volatility series for high frequency scales, using the Maximal Overlapping Discrete Wavelet transform and we apply Maximum Likelihood for a factor decomposition of the short-run covariance matrix. The empirical evidence…
Volatility co-movements: a time scale decomposition analysis
2014
In this paper we are interested in detecting contagion from US to European stock market volatilities in the period immediately after the Lehman Brothers’ collapse. The analysis, based on a factor decomposition of the covariance matrix of implied and realized volatilities, is carried for different sub-samples (identified as normal and crisis periods) and across different (high) frequency bands. In particular, the analysis is split in two stages. In the first stage, we retrieve the time series of wavelet coefficients for each volatility series for high frequency scales, using the Maximal Overlapping Discrete Wavelet transform and, in a second stage, we apply Maximum Likelihood for a factor de…
Wavelet analysis of asset price misalignments
2011
Asset price misalignments are analyzed through wavelet decomposition. The analysis, carried within the time-frequency domain, allows us to detect how far, in a given time period, financial time series, such as house or stock prices, are from their fundamental value. The latter is associated with the low frequency component of a given time series. Moreover, using wavelet analysis, we explore whether monetary policy can contribute to asset price misalignments.
WAVELET-BASED ESTIMATION OF MODAL PARAMETERS OF A VEHICLE INVOLVED IN A FULL-SCALE IMPACT
2012
In this paper, a wavelet-based approach is presented for estimation of vehicle modal parameters. The acceleration of a colliding vehicle is measured in its center of gravity — this crash pulse contains detailed information about vehicle behavior throughout a collision. Three types of signal analysis are elaborated here: time domain analysis (i.e. description of kinematics of a vehicle in time domain), the frequency analysis (identification of the parameters of the crash pulse in frequency domain), and the time-frequency analysis, which comprises those techniques that study a signal in both the time and frequency domains simultaneously, using Morlet wavelet properties. The frequency compone…
SIGNAL ANALYSIS AND PERFORMANCE EVALUATION OF A VEHICLE CRASH TEST WITH A FIXED SAFETY BARRIER BASED ON HAAR WAVELETS
2011
Author's version of an article published in the journal: International Journal of Wavelets, Multiresolution and Information Processing. Also available from the publisher at: http://dx.doi.org/10.1142/s0219691311003979 This paper deals with the wavelet-based performance analysis of the safety barrier for use in a full-scale test. The test involves a vehicle, a Ford Fiesta, which strikes the safety barrier at a prescribed angle and speed. The vehicle speed before the collision was measured. Vehicle accelerations in three directions at the center of gravity were measured during the collision. The yaw rate was measured with a gyro meter. Using normal speed and high-speed video cameras, the beha…
On the Design of Fast Wavelet Transform Algorithms With Low Memory Requirements
2008
In this paper, a new algorithm to efficiently compute the two-dimensional wavelet transform is presented. This algorithm aims at low memory consumption and reduced complexity, meeting these requirements by means of line-by-line processing. In this proposal, we use recursion to automatically place the order in which the wavelet transform is computed. This way, we solve some synchronization problems that have not been tackled by previous proposals. Furthermore, unlike other similar proposals, our proposal can be straightforwardly implemented from the algorithm description. To this end, a general algorithm is given which is further detailed to allow its implementation with a simple filter bank…
Design of Multiresolution Operators Using Statistical Learning Tools: Application to Compression of Signals
2012
Using multiresolution based on Harten's framework [J. Appl. Numer. Math., 12 (1993), pp. 153---192.] we introduce an alternative to construct a prediction operator using Learning statistical theory. This integrates two ideas: generalized wavelets and learning methods, and opens several possibilities in the compressed signal context. We obtain theoretical results which prove that this type of schemes (LMR schemes) are equal to or better than the classical schemes. Finally, we compare traditional methods with the algorithm that we present in this paper.
Signal reconstruction, modeling and simulation of a vehicle full-scale crash test based on Morlet wavelets
2012
Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this paper a novel wavelet-based approach is introduced to reproduce acceleration pulse of a vehicle involved in a crash event. The acceleration of a colliding vehicle is measured in its center of gravity-this crash pulse contains detailed information about vehicle behavior throughout a collision. Three types of signal analysis are elaborated here: time domain analysis (i.e. description of kinematics of…
Event signal characterization for disturbance interpretation in power grid
2018
This paper presents the signal processing approach to detect and characterize the physical events that occur in power system using PMUs signals. A small window is applied so that the extracted spectral features belong to a stationary signal. This is based on applying empirical mode decomposition, followed by square root of spectral kurtosis (SRSK) for computation of statistical indices to indicate the event occurrence. Subsequently, features from these events are extracted using mel frequency cepstral coefficients on SRSK. © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/re…
Locally Supported Wavelets on Manifolds with Applications to the 2D Sphere
1999
Abstract In this paper we present a construction principle for locally supported wavelets on manifolds once a multiresolution analysis is given. The wavelets provide a stable (or unconditional) basis for a scale of Sobolev spaces H s , 0 ≤ s ≤ s . We examine a fast wavelet transform with almost optimal complexity. For the two-dimensional sphere we construct a multiresolution analysis generated by continuous splines that are bilinear with respect to some special spherical grid. In our approach the poles are not exceptional points concerning the approximation power or the stability of the wavelet basis. Finally we present some numerical applications to singularity detection and the analysis o…