Wavelet-based denoising of acoustic transients

Barsanti, R.J.; Fargues, M.P.

doi:10.1109/acssc.1996.599064

Cited by 3 publications

(4 citation statements)

References 12 publications

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“…However, in previous studies that have used wavelet thresholding for the de-noising of communications signals the universal threshold, (16), has been used directly [4][5][6][7][8]. To provide a basis for comparisons of the results in this study with prior work the universal threshold has also been used as defined in (16).…”

Section: The Wavelet Thresholdsmentioning

confidence: 99%

“…Wavelet-based de-noising of acoustic transients has also been developed with the use of the universal threshold [6], and has led to the application of this threshold to common underwater acoustic communications signals [7], as well as BPSK and QPSK signals [8]. All of these studies have made use of soft-thresholding the wavelet coefficients, and the results of these studies illustrate that wavelet thresholding is a viable method for the de-noising of communications signals prior to demodulation.…”

Section: Introductionmentioning

confidence: 99%

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Improved Demodulation of Phase Shift Keyed Signals Using Wavelet Thresholding

Vaz

Daut

2008

2008 IEEE Sarnoff Symposium

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In this study the use of wavelet transform-based techniques to de-noise Phase Shift Keyed (PSK) signals is investigated. Specifically, Binary Phase Shift Keyed (BPSK), Quadrature Phase Shift Keyed (QPSK) and 8-PSK signals are considered in the presence of Additive White Gaussian Noise (AWGN). Wavelet-domain decomposition of the received signals is carried out via the Discrete Wavelet Transform (DWT). The Haar, Daubechies5, Coiflet5 and Symmlet4 wavelets are used, along with both hard-and soft-thresholding techniques. The improvements realized by matched filter-based demodulation in conjunction with the use of wavelet thresholding techniques are shown by Bit Error Rate (BER) curves for each of the three modulation schemes. It has been found that by using appropriate wavelets and wavelet thresholding methods improvements in BER of over three orders of magnitude are achievable within the range of bit energy-to-noise spectral density ratios ( ) b 0 E N from -5 dB to 8 dB.Index Terms-Phase shift keying, wavelet transforms, matched filters, noise.

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Section: The Wavelet Thresholdsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improved Demodulation of Phase Shift Keyed Signals Using Wavelet Thresholding

Vaz

Daut

2008

2008 IEEE Sarnoff Symposium

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“…The short-time Fourier transform (STFT)-based method [14] and wavelet-based filtering methods [15][16][17] have also been used by the researchers for transient removal. Most of the filtering methods follow the general procedure as the noise signal decomposition [14,[18][19][20] and then the noise reduction.…”

Section: Introductionmentioning

confidence: 99%

Hard component detection of transient noise and its removal using empirical mode decomposition and wavelet‐based predictive filter

Tanwar

Somkuwar

2018

IET signal process.

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In this study, the authors propose a novel method that provides weapon sound (WS) interference reduction of military instruction sound or instructions sound (IS). This method comprises of the following steps. In the first step, the mixed signal is split into its basic constituents using principal component analysis. The second step provides the intrinsic mode functions using the empirical mode decomposition method. In the third step, the fundamental frequency component is extracted by cepstrum analysis. The localisation of WS is done using the grid search window-dominant signal subspace-based method in the fourth step. Multiscale prediction and filtering using Daubechies wavelet-based prediction are applied in the final step. The proposed method provides better results than existing baseline methods, for various signal-to-noise ratios. The simulations have also been performed on recorded WS corrupted IS signals from three different distances for the various input signal-to-weapon noise ratios, to verify the accuracy of the proposed method.

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“…Two thresholds value of and are predefined ( . Semi-soft thresholding sets zero for all coefficients below the threshold and retain the magnitude of remaining coefficients that are greater than threshold , and a weighted average of and is assigned to the rest coefficients that fall between and , defined in [25,12]:…”

Section: Wavelet Coefficients Thresholding Methodsmentioning

confidence: 99%

Development of Vibration Loading Profiles for Accelerated Durability Tests of Ground Vehicles

2011

ASME 2011 Dynamic Systems and Control Conference and Bath/Asme Symposium on Fluid Power and Motion Control, Volume 2

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The accelerated durability test is an important part for design and manufacturing ground vehicles. It consists of test designed to quantify the life characteristics of a ground vehicle component under normal use conditions by testing the unit at higher stress levels to accelerate the occurrence of failures. The challenge of conducting accelerated durability tests is to create the driven profile. In general, the mission profiles of the accelerated durability test can be generated via the acceleration data of the events experienced by the vehicle during the field test.Accurately separating the time series signal that correlate the load events becomes essential to efficiently generate the mission profiles for the accelerated test analysis. The representative Power Spectrum Density (PSD) profile can be generated based on the mission profiles. Then, the driven profile for the sub-scaled accelerated durability test, i.e., the acceleration data can be generated based on the PSD data.ii

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Wavelet-based denoising of acoustic transients

Abstract: This study investigates the application of orthonormal wavelet analysis to the removal of noise from acoustic transients. Results show that Wavelet based denoising schemes perform better than classical Wiener fdtering.

Cited by 3 publications

References 12 publications

Improved Demodulation of Phase Shift Keyed Signals Using Wavelet Thresholding

Improved Demodulation of Phase Shift Keyed Signals Using Wavelet Thresholding

Hard component detection of transient noise and its removal using empirical mode decomposition and wavelet‐based predictive filter

Development of Vibration Loading Profiles for Accelerated Durability Tests of Ground Vehicles

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