Appendix 3:The quadrature representation of narrowband noise

2011 ◽  
pp. 300-303
Keyword(s):  
Narrowband Noise

Method of estimation of hidden correlation of narrowband noise signals

2019 ◽  
pp. 34-39 ◽  
Author(s):  
E.I. Chernov ◽  
N.E. Sobolev ◽  
A.A. Bondarchuk ◽  
L.E. Aristarhova
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
New Technology ◽  
Digital Signal ◽  
Measuring Instruments ◽  
Central Frequency ◽  
Pearson Criterion ◽  
Useful Signal ◽  
Band Limited ◽  
Narrowband Noise

The concept of hidden correlation of noise signals is introduced. The existence of a hidden correlation between narrowband noise signals isolated simultaneously from broadband band-limited noise is theoretically proved. A method for estimating the latent correlation of narrowband noise signals has been developed and experimentally investigated. As a result of the experiment, where a time frag ent of band-limited noise, the basis of which is shot noise, is used as the studied signal, it is established: when applying the Pearson criterion, there is practically no correlation between the signal at the Central frequency and the sum of signals at mirror frequencies; when applying the proposed method for the analysis of the same signals, a strong hidden correlation is found. The proposed method is useful for researchers, engineers and metrologists engaged in digital signal processing, as well as developers of measuring instruments using a new technology for isolating a useful signal from noise – the method of mirror noise images.

scholarly journals Comparing Tinnitus Tuning Curves and Psychoacoustic Tuning Curves

2019 ◽  
Vol 23 ◽  
pp. 233121651987853 ◽  
Author(s):  
Philippe Fournier ◽  
Malgorzata Wrzosek ◽  
Michel Paolino ◽  
Fabien Paolino ◽  
Anne Quemar ◽  
...  
Keyword(s):  
Related Activity ◽  
Tuning Curves ◽  
Sound Levels ◽  
Tinnitus Masking ◽  
Narrowband Noise

Tinnitus masking patterns have long been known to differ from those used for masking external sound. In the present study, we compared the shape of tinnitus tuning curves (TTCs) to psychophysical tuning curves (PTCs), the latter using as a target, an external sound that mimics the tinnitus characteristics. A secondary goal was to compare sound levels required to mask tinnitus to those required to mask tinnitus-mimicking sounds. The TTC, PTC, audiometric thresholds, tinnitus pitch, and level matching results of 32 tinnitus patients were analyzed. Narrowband noise maskers were used for both PTC and TTC procedures. Patients were categorized into three groups based on a combination of individual PTC–TTC results. Our findings indicate that in 41% of cases, the PTC was sharp (V shape), but the TTC showed a flat configuration, suggesting that the tinnitus-related activity in that subgroup does not behave as a regular stimulus-induced activity. In 30% of cases, V-shape PTC and TTC were found, indicating that the tinnitus-related activity may share common properties with stimulus-induced activity. For a masker centered at the tinnitus frequency, the tinnitus was more difficult to mask than the mimicking tone in 72% of patients; this was particularly true for the subset with V-shape PTCs and flat TTCs. These results may have implications for subtyping tinnitus and acoustic therapies, in particular those targeting the tinnitus frequency.

scholarly journals Active Suppression of Narrowband Noise by Multiple Secondary Sources

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Seokhoon Ryu ◽  
Yun Jung Park ◽  
Young-Sup Lee
Keyword(s):  
Quality Factor ◽  
Quality Factors ◽  
Real Time Control ◽  
Active Suppression ◽  
Secondary Sources ◽  
Time Control ◽  
Narrowband Signal ◽  
Dspace 1104 ◽  
Path Models ◽  
Narrowband Noise

This study presents theoretical and experimental investigation on the active suppression of narrowband noise with C1, C1.5, and C2 components by using multichannel secondary sources in a duct. The quality manipulation in the duct was controlled by changing quality factors which were incorporated into a multichannel FxLMS algorithm. The algorithm is extensively investigated in both theory and real-time control experiment. After analysing the primary and secondary paths of the duct system, an acoustic narrowband signal was chosen as a primary noise and the impulse responses were implemented as the secondary path models. Control results show that the quality factors in the algorithm that was implemented in a dSPACE 1104 provide a stable and excellent response compared to before control. It is obvious that the lower quality factor cancels the more primary noise as defined in the theory although the attenuation levels are not exactly and inversely proportional to the quality factor. The results in this study can be used for practical active sound quality control systems.

An experimental study of reducing narrowband noise of a slat using chevrons

2012 ◽  
Vol 58 (4) ◽  
pp. 411-419 ◽  
Author(s):  
M. Yu. Zaitsev ◽  
I. V. Belyaev ◽  
V. F. Kopiev ◽  
M. A. Mironov
Keyword(s):  
Experimental Study ◽  
Narrowband Noise

scholarly journals Extraction of Partial Discharge Pulses from the Complex Noisy Signals of Power Cables Based on CEEMDAN and Wavelet Packet

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3242 ◽  
Author(s):  
Sun ◽  
Zhang ◽  
Shi ◽  
Gou
Keyword(s):  
White Noise ◽  
Arrival Time ◽  
Wavelet Packet ◽  
Partial Discharge ◽  
Gaussian White Noise ◽  
Power Cable ◽  
Sampling Point ◽  
Power Cables ◽  
Threshold Method ◽  
Narrowband Noise

While both periodic narrowband noise and white noise are significant sources of interference in the detection and localization of partial discharge (PD) signals in power cables, existing research has focused nearly exclusively on white noise suppression. This paper addresses this issue by proposing a new signal extraction method for effectively detecting random PD signals in power cables subject to complex noise environments involving both white noise and periodic narrowband noise. Firstly, the power cable signal was decomposed using complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and the periodic narrowband noise and frequency aliasing in the obtained signal components were suppressed using singular value decomposition. Then, signal components contributing significantly to the PD signal were determined according to the cross-correlation coefficient between each component and the original PD signal, and the PD signal was reconstructed solely from the obtained significant components. Finally, the wavelet packet threshold method was used to filter out residual white noise in the reconstructed PD signal. The performance of the proposed algorithm was demonstrated by its application to synthesized PD signals with complex noise environments composed of both Gaussian white noise and periodic narrowband noise. In addition, the time-varying kurtosis method was demonstrated to accurately determine the PD signal arrival time when applied to PD signals extracted by the proposed method from synthesized signals in complex noise environments with signal-to-noise ratio (SNR) values as low as −6 dB. When the SNR was reduced to −23 dB, the arrival time error of the PD signal was only one sampling point.

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