Multiplication-free architecture for Daubechies wavelet transforms using algebraic integers

2003 ◽  
Author(s):  
Khan Wahid ◽  
Vassil Dimitrov ◽  
Graham A. Jullien
Keyword(s):  
Wavelet Transforms ◽  
Daubechies Wavelet ◽  
Algebraic Integers

Daubechies Wavelets Based Robust Audio Fingerprinting for Content-Based Audio Retrieval

2012 ◽  
Vol 4 (2) ◽  
pp. 49-69
Author(s):  
Wei Sun ◽  
Zhe-Ming Lu ◽  
Fa-Xin Yu ◽  
Rong-Jun Shen
Keyword(s):  
Wavelet Transforms ◽  
Wavelet Decomposition ◽  
Experimental Results ◽  
Daubechies Wavelet ◽  
Linear Speed ◽  
Time Frequency ◽  
Audio Fingerprinting ◽  
Audio Retrieval ◽  
Audio Clip ◽  
Frequency Features

Audio fingerprinting is the process to obtain a compact content-based signature that summarizes the essence of an audio clip. In general, existing audio fingerprinting schemes based on wavelet transforms are not robust against large linear speed changes. The authors present a novel framework for content-based audio retrieval based on the audio fingerprinting scheme that is robust against large linear speed changes. In the proposed scheme, 8 levels Daubechies wavelet decomposition is adopted for extracting time-frequency features and two fingerprint extraction algorithms are designed. The experimental results from this study are discussed further into the article.

scholarly journals VLSI Architectures for the 4-Tap and 6-Tap 2-D Daubechies Wavelet Filters Using Algebraic Integers

2013 ◽  
Vol 60 (6) ◽  
pp. 1455-1468 ◽  
Author(s):  
Shiva Kumar Madishetty ◽  
Arjuna Madanayake ◽  
Renato J. Cintra ◽  
Vassil S. Dimitrov ◽  
Dale H. Mugler
Keyword(s):  
Daubechies Wavelet ◽  
Algebraic Integers ◽  
Wavelet Filters ◽  
Vlsi Architectures

Daubechies Wavelets Based Robust Audio Fingerprinting for Content-Based Audio Retrieval

2013 ◽  
pp. 50-63
Author(s):  
Wei Sun ◽  
Zhe-Ming Lu ◽  
Fa-Xin Yu ◽  
Rong-Jun Shen
Keyword(s):  
Wavelet Transforms ◽  
Experimental Results ◽  
Daubechies Wavelet ◽  
Daubechies Wavelets ◽  
Linear Speed ◽  
Time Frequency ◽  
Audio Fingerprinting ◽  
Audio Retrieval ◽  
Audio Clip ◽  
Frequency Features

Audio fingerprinting is the process to obtain a compact content-based signature that summarizes the essence of an audio clip. In general, existing audio fingerprinting schemes based on wavelet transforms are not robust against large linear speed changes. The authors present a novel framework for content-based audio retrieval based on the audio fingerprinting scheme that is robust against large linear speed changes. In the proposed scheme, 8 levels Daubechies wavelet decomposition is adopted for extracting time-frequency features and two fingerprint extraction algorithms are designed. The experimental results from this study are discussed further into the article.

The Morlet and Daubechies Wavelet Transforms for Fatigue Strain Signal Analysis

2013 ◽  
Vol 471 ◽  
pp. 197-202 ◽  
Author(s):  
T.E. Putra ◽  
S. Abdullah ◽  
Mohd Zaki Nuawi ◽  
Mohd Faridz Mod Yunoh
Keyword(s):  
Wavelet Transforms ◽  
Signal Analysis ◽  
Wavelet Coefficient ◽  
Discrete Wavelet ◽  
Daubechies Wavelet ◽  
Wavelet Coefficients ◽  
Public Road ◽  
Road Surfaces ◽  
Strain Signal ◽  
Wavelet Family

This paper presents the convenient wavelet family for the fatigue strain signal analysis based on the wavelet coefficients. This study involves the Morlet and Daubechies wavelet coefficients using both the Continuous and Discrete Wavelet Transforms, respectively. The signals were collected from a front lower suspension arm of a passenger car by placing strain gauges at the highest stress locations. The car was driven over public road surfaces, i. e. pavé, highway and UKM roads. In conclusion, the Daubechies wavelet was the convenient wavelet family for the analysis. It was because the wavelet gave the higher wavelet coefficient values indicating that the resemblance between the wavelet and the signals was stronger, closer and more similar.

Fatigue Road Signal Denoising Process Using the 4th Order of Daubechies Wavelet Transforms

2008 ◽  
Vol 8 (14) ◽  
pp. 2496-2509 ◽  
Author(s):  
S. Abdullah ◽  
S.N. Sahadan ◽  
M.Z. Nuawi ◽  
Z.M. Nopiah
Keyword(s):  
Wavelet Transforms ◽  
Signal Denoising ◽  
Daubechies Wavelet
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