Essential wavelets for statistical applications and data analysis
RT Ogden - 1997 - Springer
I once heard the book by Meyer (1993) described as a" vulgarization" of wavelets. While this
is true in one sense of the word, that of making a sub ject popular (Meyer's book is one of the …
is true in one sense of the word, that of making a sub ject popular (Meyer's book is one of the …
[图书][B] Ondas e ondaletas Vol. 23
PA Morettin - 1999 - books.google.com
Page 1 Ondas e Ondaletas Da Análise de Fourier à Análise de Ondaletas Pedro A. Morettin
edusp Page 2 Page 3 Page 4 O objetivo do autor ao escrever este livro foi tornar acessível, em …
edusp Page 2 Page 3 Page 4 O objetivo do autor ao escrever este livro foi tornar acessível, em …
An introduction to wavelets for economists
C Schleicher - 2002 - bankofcanada.ca
Wavelets are mathematical expansions that transform data from the time domain into
different layers of frequency levels. Compared to standard Fourier analysis, they have the …
different layers of frequency levels. Compared to standard Fourier analysis, they have the …
A wavelet analysis for time series
C Chiann, PA Morettin - Journal of Nonparametric Statistics, 1998 - Taylor & Francis
In this paper we develop a wavelet spectral analysis for a stationary discrete process. Some
basic ideas on wavelets are given and the concept of wavelet spectrum is introduced …
basic ideas on wavelets are given and the concept of wavelet spectrum is introduced …
[图书][B] Financial market risk: measurement and analysis
C Los - 2003 - taylorfrancis.com
This new book uses advanced signal processing technology to measure and analyze risk
phenomena of the financial markets. It explains how to scientifically measure, analyze and …
phenomena of the financial markets. It explains how to scientifically measure, analyze and …
[HTML][HTML] Time series forecasting using wavelet denoising an application to saudi stock index
RM Alrumaih, MA Al-Fawzan - Journal of King Saud University-Engineering …, 2002 - Elsevier
In recent years, wavelet transform has become very popular in many application areas such
as physics, engineering, biomedical, signal processing, mathematics, and statistics. In this …
as physics, engineering, biomedical, signal processing, mathematics, and statistics. In this …
Optimal signal multi-resolution by genetic algorithms to support artificial neural networks for exchange-rate forecasting
Detecting the features of significant patterns from historical data is crucial for good
performance in time-series forecasting. Wavelet analysis, which processes information …
performance in time-series forecasting. Wavelet analysis, which processes information …
[HTML][HTML] Efficient implementation of a wavelet neural network model for short-term traffic flow prediction: Sensitivity analysis
The concept of a smart city is emerging to address significant challenges arising from rapid
urbanization, economic growth, and climate change. Innovative technologies can be used …
urbanization, economic growth, and climate change. Innovative technologies can be used …
From Fourier to wavelet analysis of time series
PA Morettin - … in Computational Statistics 12th Symposium held in …, 1996 - Springer
It is well known that Fourier analysis is suited to the analysis of stationary series. If Xt, t=
0,±1,… is a weakly stationary process, it can be decomposed into a linear combination of …
0,±1,… is a weakly stationary process, it can be decomposed into a linear combination of …
[图书][B] Latent structure in non-stationary time series
R Prado - 1998 - search.proquest.com
The class of time-varying autoregressions (TVAR) constitutes a suitable class of models to
describe long series that exhibit non-stationarities. Signals experiencing changes in …
describe long series that exhibit non-stationarities. Signals experiencing changes in …