Search results for "Wavelet"
showing 10 items of 329 documents
A wavelet Methodology for EEG Time-frequency Analysis in a Time Discrimination Task
2009
EEG signals recorded by surface electrodes placed on the scalp can be thought as non- stationary stochastic processes in both time and space, especially in response to external stimuli. Cognitive tasks, in particular, are reflected by changes in EEG dynamics concerning both rhythms energy and connectivity across different brain regions. In the frequency-domain, EEG analysis is complicated and time-frequency methodologies are needed. The Wavelet Transform, in particular, represents a powerful tool for analysing, within a time-frequency embedding, the EEG. In this study we applied a wavelet-based methodology to extract quantitative time-frequency parameters from EEG signals recorded during a …
Prefiltering for pattern recognition using wavelet transform and neural networks
2003
Publisher Summary Neural networks are built from simple units interlinked by a set of weighted connections. Generally, these units are organized in layers. Each unit of the first layer (input layer) corresponds to a feature of a pattern that is to be analyzed. The units of the last layer (output layer) produce a decision after the propagation of information. Before feeding the computational data to neural networks, the signal must undergo a preprocessing in order to (1) define the initial transformation to represent the measured signal, (2) retain important features for class discrimination and discard that is irrelevant, and (3) reduce the volume of data to be processed, for example, data …
Hydro-Acoustic Target Detection
2014
This chapter presents an example of utilization of the discrete–time wavelet packets, which are described in Sect. 9.1, to classification of acoustic signals and detection of a target. The methodology based on wavelet packets is applied to a problem of detection of a boat of a certain type when other background noises are present. The solution is obtained via analysis of boat’s hydro-acoustic signature against an existing database of recorded and processed hydro-acoustic signals. The signals are characterized by the distribution of their energies among blocks of wavelet packet coefficients.
An Improved Forecasting Model from Satellite Imagery Based on Optimum Wavelet Bases and Adam Optimized LSTM Methods
2021
This paper proposes a new hybrid approach I-WT-LSTM (i.e., Improved Wavelet Long Short-Term Memory (LSTM) Model) for forecasting non-stationary time series (TS) from satellite imagery. The proposed approach consists of two steps: The first step aims at decomposing TS using Multi-Resolution Analysis wavelet (MRA-WT) into inter-and intra-annual components using 18 different mother wavelets (MW). Then, the energy to Shannon entropy ratio criterion is calculated to select the best MW. The second step is based on the LSTM model using Adam optimizer to predict the future. The proposed approach is tested using TS derived from Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2001 t…
Time-Frequency behaviour of the a-wave of the human electroretinogram
2007
The electroretinogram is the record of the electrical response of the retina to a light stimulus. The two main components are the a-wave and the b-wave, the former is related to the early photoreceptoral activity. Aim of this paper is to acquire useful information about the time-frequency features of the human a-wave, by means of the wavelet analysis. This represents a proper approach in dealing with nonstationary signals. We have used the Mexican Hat as mother wavelet. The analysis, carried out for four representative values of the luminance, comprehends the frequency dependence of the variance and the skeleton. The results indicate a predominance of low frequency components, their time di…
Wavelet Analysis and Denoising: New Tools for Economists
2007
This paper surveys the techniques of wavelets analysis and the associated methods of denoising. The Discrete Wavelet Transform and its undecimated version, the Maximum Overlapping Discrete Wavelet Transform, are described. The methods of wavelets analysis can be used show how the frequency content of the data varies with time. This allow us to pinpoint in time such events as major structural breaks. The sparse nature of the wavelets representation also facilitates the process of noise reduction by nonlinear \textit{wavelet shrinkage,} which can be used to reveal the underlying trends in economic data. An application of these techniques to the UK real GDP (1873--2001) is described. The purpo…
Wavelet data analysis of EXAFS spectra
2009
Abstract The application of wavelet transform to the analysis of the extended X-ray absorption fine structure (EXAFS) from perovskite-type compounds is presented on the example of the Re L 3 -edge in ReO 3 and Co K-edge in LaCoO 3 . We propose a modified wavelet transform procedure, which allows better discrimination of the overlapped contributions into the EXAFS signal.
Polynomial Spline-Wavelets
2015
This chapter presents wavelets in the spaces of polynomial splines. The wavelets’ design is based on the Zak transform, which provides an integral representation of spline-wavelets. The exponential wavelets which participate in the integral representation are counterparts of the exponential splines that were introduced in Chap. 4. Fast algorithms for the wavelet transforms of splines are presented. Generators of spline-wavelet spaces are described, such as the B-wavelets and their duals and the Battle-Lemarie wavelets whose shifts form orthonormal bases of the spline-wavelet spaces.
Analysis of Low-Altitude Aerial Sequences for Road Traffic Diagnosis using Graph Partitioning and Markov Hierarchical Models
2016
International audience; This article focuses on an original approach aiming the processing of low-altitude aerial sequences taken from an helicopter (or drone) and presenting a road traffic. Proposed system attempts to extract vehicles from acquired sequences. Our approach begins with detecting the primitives of sequence images. At the time of this step of segmentation, the system computes dominant motion for each pair of images. This motion is computed using wavelets analysis on optical flow equation and robust techniques. Interesting areas (areas not affected by the dominant motion) are detected thanks to a Markov hierarchical model. Primitives stemming from segmentation and interesting a…
An evaluation framework and a benchmark for multi/hyperspectral image compression
2011
International audience; This paper benchmarks three multi/hyperspectral image compression approaches: the classic Multi-2D compression approach and two different implementations of 3D approach (Full 3D and Hybrid). All approaches are combined with a spectral PCA decorrelation stage to optimize performance. These three compression approaches are compared within a larger comparison framework than the conventionally used PSNR, which includes eight metrics divided into three families. The comparison is carried out with regard to variations in bitrates, spatial, and spectral dimensions variations of images. The time and memory consumption difference between the three approaches is also discussed…