Feature Extraction Accuracy Improvement of Acoustic Signals Based on Reassigned Wavelet Scalogram

2011 ◽  
Vol 55-57 ◽  
pp. 2065-2068
Author(s):  
Pan Li ◽  
Ping He ◽  
Hui Qi Sun ◽  
Wei Shang ◽  
Nan Xiang Sun
Keyword(s):  
Feature Extraction ◽  
High Reliability ◽  
Acoustic Signals ◽  
Morlet Wavelet ◽  
Frequency Error ◽  
Accuracy Improvement ◽  
Characteristic Frequencies ◽  
Location Method ◽  
Simulation Results ◽  
Morlet Wavelet Transform

Based on the wavelet scalogram obtained by Morlet wavelet transform and hard threshold de-noising filtering for typical acoustic emission signals, region segmented location method is introduced to get the number and accurate values of the characteristic frequencies, therefore the error induced by misjudgment and misreading can be avoided effectively. Then considering the weakness of large characteristic frequency error in Morlet wavelet scalogram, the feature extraction accuracy has been improved by combing region segmented location method and reassigned wavelet scalogram. Simulation results show that the proposed method has the merits of well rapidity, high reliability and briefness, hence can realize high precision feature extraction and has great practical value.

339 Morlet wavelet transform in EEG during perceptuo-motor tasks

1998 ◽  
Vol 30 (1-2) ◽  
pp. 131-132
Author(s):  
S. Slobounovl ◽  
R. Tutwiler ◽  
E. Slobounova
Keyword(s):  
Wavelet Transform ◽  
Morlet Wavelet ◽  
Motor Tasks ◽  
Morlet Wavelet Transform

A unified framework for the design of low-complexity wavelet filters

2017 ◽  
Vol 15 (06) ◽  
pp. 1750054 ◽  
Author(s):  
Ameya K. Naik ◽  
Raghunath S. Holambe
Keyword(s):  
Feature Extraction ◽  
Compact Support ◽  
Low Complexity ◽  
Design Parameters ◽  
Unified Framework ◽  
Vanishing Moments ◽  
Wavelet Filters ◽  
Design Variables ◽  
Optimum Filter ◽  
Simulation Results

An outline is presented for construction of wavelet filters with compact support. Our approach does not require any extensive simulations for obtaining the values of design variables like other methods. A unified framework is proposed for designing halfband polynomials with varying vanishing moments. Optimum filter pairs can then be generated by factorization of the halfband polynomial. Although these optimum wavelets have characteristics close to that of CDF 9/7 (Cohen-Daubechies-Feauveau), a compact support may not be guaranteed. Subsequently, we show that by proper choice of design parameters finite wordlength wavelet construction can be achieved. These hardware friendly wavelets are analyzed for their possible applications in image compression and feature extraction. Simulation results show that the designed wavelets give better performances as compared to standard wavelets. Moreover, the designed wavelets can be implemented with significantly reduced hardware as compared to the existing wavelets.

scholarly journals Survey of Marine Organisms Based on Passive Acoustic Technology

2020 ◽  
Vol 15 (5) ◽  
pp. 729-737
Author(s):  
Gong Chen ◽  
Lei Cai ◽  
Lv Zong ◽  
Yan Wang ◽  
Xin Yuan
Keyword(s):  
Feature Extraction ◽  
Acoustic Signal ◽  
Extraction Method ◽  
Acoustic Signals ◽  
Marine Organisms ◽  
Decomposition Algorithm ◽  
Sparse Decomposition ◽  
Feature Extraction Method ◽  
Fish Detection ◽  
Passive Acoustic

Passive acoustic technology (PAT) is an important tool to acquire the passive acoustic signals from marine organisms. In this paper, PAT fish detection is introduced at great length, including the relevant instruments, signal processing methods, and workflow. Focusing on the key tasks of PAT fish detection, the authors proposed a sparse decomposition algorithm that extracts coherent ratio of passive fish acoustic signal, and designed a feature extraction method for that signal based on speech imitation technology. Experimental results demonstrate that the proposed sparse decomposition algorithm can detect fish acoustic signal accurately at low signal-to-noise ratios (SNRs), and the proposed feature extraction method can effectively extract fish acoustic signals from the marine background. The research results shed important new light on the protection and management of fishery resources in the seas and oceans.

scholarly journals Body size information in large-scale acoustic bat databases

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5370 ◽  
Author(s):  
Caterina Penone ◽  
Christian Kerbiriou ◽  
Jean-François Julien ◽  
Julie Marmet ◽  
Isabelle Le Viol
Keyword(s):  
Body Size ◽  
Large Scale ◽  
Principal Component ◽  
Acoustic Signals ◽  
Species Traits ◽  
Climatic Variables ◽  
Characteristic Frequencies ◽  
Acoustic Data ◽  
Forearm Length ◽  
Broad Scale

Background Citizen monitoring programs using acoustic data have been useful for detecting population and community patterns. However, they have rarely been used to study broad scale patterns of species traits. We assessed the potential of acoustic data to detect broad scale patterns in body size. We compared geographical patterns in body size with acoustic signals in the bat species Pipistrellus pipistrellus. Given the correlation between body size and acoustic characteristics, we expected to see similar results when analyzing the relationships of body size and acoustic signals with climatic variables. Methods We assessed body size using forearm length measurements of 1,359 bats, captured by mist nets in France. For acoustic analyses, we used an extensive dataset collected through the French citizen bat survey. We isolated each bat echolocation call (n = 4,783) and performed automatic measures of signals, including the frequency of the flattest part of the calls (characteristic frequency). We then examined the relationship between forearm length, characteristic frequencies, and two components resulting from principal component analysis for geographic (latitude, longitude) and climatic variables. Results Forearm length was positively correlated with higher precipitation, lower seasonality, and lower temperatures. Lower characteristic frequencies (i.e., larger body size) were mostly related to lower temperatures and northern latitudes. While conducted on different datasets, the two analyses provided congruent results. Discussion Acoustic data from citizen science programs can thus be useful for the detection of large-scale patterns in body size. This first analysis offers a new perspective for the use of large acoustic databases to explore biological patterns and to address both theoretical and applied questions.

scholarly journals A study on Electron Oscillations in the Magnetosheath of Mars with Mars Express observations

2016 ◽  
Vol 12 (S328) ◽  
pp. 230-232
Author(s):  
Adriane M. de Souza ◽  
Ezequiel Echer ◽  
Mauricio J. A. Bolzam ◽  
Markus Fränz
Keyword(s):  
Wavelet Transform ◽  
Electron Density ◽  
Low Frequency ◽  
Morlet Wavelet ◽  
Space Plasmas ◽  
Density Data ◽  
Mars Express ◽  
Preliminary Study ◽  
Morlet Wavelet Transform ◽  
Low Frequency Waves

AbstractWavelet analysis was employed to identify the major frequencies of low-frequency waves present in the Martian magnetosheath. The Morlet wavelet transform was selected and applied to the electron density data, obtained from the Analyzer of Space Plasmas and Energetic Atoms experiment (ASPERA-3), onboard the Mars Express (MEX) spacecraft. We have selected magnetosheath crossings and analyzed electron density data. From a preliminary study of 502 magnetosheath crossings (observed during the year of 2005), we have found 1409 periods between 0.005 and 0.06Hz. The major frequencies observed were in the range 0.005-0.02 Hz with 58.5% of the 1409 frequencies identified.

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