scholarly journals An Approach to 1/f Noise Detection Based on Adaptive T-ATFPF Algorithm

CONVERTER ◽  
2021 ◽  
pp. 407-418
Author(s):  
Jie Wu, Xiaojuan Chen, Zhaohua Zhang
Keyword(s):  
White Noise ◽  
Thermal Noise ◽  
Low Frequency ◽  
Window Length ◽  
Time Frequency ◽  
Noise Characteristics ◽  
Small Window ◽  
Frequency Peak ◽  
Variable Window ◽  
Conventional Algorithm

The generation of 1/f noise is closely related to the quality defects of IGBT devices. In the process of detecting IGBT single tube noise, thermal noise and shot noise show obvious white noise characteristics in the low frequency band, which are detected under the background of strong white noise 1/f noise can characterize the performance of IGBT devices. Therefore, on the basis of the Time-Frequency Peak Filtering (TFPF) algorithm, a two-dimensional time-domain adaptive T-ATFPF algorithm is proposed, and the adaptive segmentation is realized by means of the confidence interval crossing criterion based on Chebyshev’s inequality. Variable window length,use a small window length to process the signal section, which retains more detailed information of the effective signal.Use a larger window length to process the buffer section to ensure a smooth transition.Use the large window length to process the noise section, which more effectively suppresses randomness for noise, apply T-ATFPF to artificial synthesis model and actual model. Experimental results indicate that compared with the conventional algorithm, the improved method can better recover 1/f noise, and the ratio of signal to noise is greatly improved by about 1.3dB.

ANALYSIS OF NOISE CHARACTERISTICS OF GaAs TUNNEL DIODES

2013 ◽  
Vol 12 (03) ◽  
pp. 1350014 ◽  
Author(s):  
VILIUS PALENSKIS ◽  
JONAS MATUKAS ◽  
JUOZAS VYŠNIAUSKAS ◽  
SANDRA PRALGAUSKAITĖ ◽  
HADAS SHTRIKMAN ◽  
...  
Keyword(s):  
White Noise ◽  
Shot Noise ◽  
Thermal Noise ◽  
Low Frequency ◽  
The Other ◽  
Frequency Noise ◽  
Tunnel Diodes ◽  
Low Frequency Noise ◽  
Noise Characteristics

An analysis and investigation of noises of GaAs tunnel diodes, which abrupt p+-n+ profile was obtained by using amphoteric nature of silicon, were performed. The main scope of this work was to verify the concepts of the explanation of white noise characteristics on the ground of shot noise and on the ground of the Gupta theorem of thermal noise in resistive elements. The other scope was to investigate the peculiarities of low frequency noise in p+-n+ junctions formed by using amphoteric silicon nature.

scholarly journals Removal of Random Noise in Seismic Data by Time-varying Window-length Time-frequency Peak Filtering

2016 ◽  
Vol 64 (5) ◽  
pp. 1703-1714 ◽  
Author(s):  
Pengjun Yu ◽  
Yue Li ◽  
Hongbo Lin ◽  
Ning Wu
Keyword(s):  
Seismic Data ◽  
Random Noise ◽  
Time Varying ◽  
Window Length ◽  
Time Frequency ◽  
Frequency Peak

Experimental Study of Jet Noise Characteristics of Series Connected Nozzles

2005 ◽  
Author(s):  
Qiang Xu
Keyword(s):  
Frequency Spectrum ◽  
Frequency Band ◽  
Low Frequency ◽  
Jet Noise ◽  
Steel Tube ◽  
The Other ◽  
Chamber Pressure ◽  
Band Frequency ◽  
Noise Characteristics ◽  
Frequency Peak

Put abstract text here. A serial of experiments were conducted to study the noise radiated from a series connected nozzle pair. The experiment results are presented in this paper. This nozzle pair consists of two nozzles, one is called source nozzle, and the other is a secondary nozzle. In these experiments, the structure of source nozzle was fixed while that of secondary nozzle was changeable. The source nozzle is mounted on a pressure chamber which is connected to an air compressor. A steel tube is fixed at the tail of source nozzle. The secondary nozzle is connected to the other end of the tube. Throat size of secondary nozzle is larger then that of source nozzle. 15 types of nozzles with different expansion ratio, length of expand segment, and throat structure were used as the secondary nozzle. Jet noise pressure of these nozzle pairs was measured by 40AF Free Field Microphone. The frequency spectrum of jet noise from source nozzle with steel tube under different chamber pressures was calculated. The pressure range is from 0.1 to 1.2 MPa. This result is compared with those spectrums of nozzle pair with different secondary nozzle under different chamber pressures. The trend of peak frequency shifts for different nozzle pair and different chamber pressure is presented in this paper. The secondary nozzles make frequency peak shift from the source nozzle, especially in low frequency band. Different structure of secondary nozzle has different influence on the frequency characteristics of jet noise. Length of expand segment has greater influence on low frequency peak than other two factors. Joint time-frequency analysis is also used in analyze the change of frequency spectrum during throat size decreased under fixed chamber pressure and various spectrograms are also presented. In low frequency band, frequency peak remains during the change of source nozzle throat size. But in higher frequency band, the frequency peak shifts from low frequency to higher ones as the throat size decreases.

scholarly journals Complex Principal Component Analysis of Antarctic Ice Sheet Mass Balance

2021 ◽  
Vol 13 (3) ◽  
pp. 480
Author(s):  
Jingang Zhan ◽  
Hongling Shi ◽  
Yong Wang ◽  
Yixin Yao
Keyword(s):  
Principal Component Analysis ◽  
Ice Sheet ◽  
Low Frequency ◽  
Principal Component ◽  
Equatorial Pacific ◽  
Mass Change ◽  
Frequency Variation ◽  
Periodic Signal ◽  
Time Frequency ◽  
The Antarctic

Ice sheet changes of the Antarctic are the result of interactions among the ocean, atmosphere, and ice sheet. Studying the ice sheet mass variations helps us to understand the possible reasons for these changes. We used 164 months of Gravity Recovery and Climate Experiment (GRACE) satellite time-varying solutions to study the principal components (PCs) of the Antarctic ice sheet mass change and their time-frequency variation. This assessment was based on complex principal component analysis (CPCA) and the wavelet amplitude-period spectrum (WAPS) method to study the PCs and their time-frequency information. The CPCA results revealed the PCs that affect the ice sheet balance, and the wavelet analysis exposed the time-frequency variation of the quasi-periodic signal in each component. The results show that the first PC, which has a linear term and low-frequency signals with periods greater than five years, dominates the variation trend of ice sheet in the Antarctic. The ratio of its variance to the total variance shows that the first PC explains 83.73% of the mass change in the ice sheet. Similar low-frequency signals are also found in the meridional wind at 700 hPa in the South Pacific and the sea surface temperature anomaly (SSTA) in the equatorial Pacific, with the correlation between the low-frequency periodic signal of SSTA in the equatorial Pacific and the first PC of the ice sheet mass change in Antarctica found to be 0.73. The phase signals in the mass change of West Antarctica indicate the upstream propagation of mass loss information over time from the ocean–ice interface to the southward upslope, which mainly reflects ocean-driven factors such as enhanced ice–ocean interaction and the intrusion of warm saline water into the cavities under ice shelves associated with ice sheets which sit on retrograde slopes. Meanwhile, the phase signals in the mass change of East Antarctica indicate the downstream propagation of mass increase information from the South Pole toward Dronning Maud Land, which mainly reflects atmospheric factors such as precipitation accumulation.

Investigation of Low-Frequency Noise Characteristics in Gated Schottky Diodes

2021 ◽  
Vol 42 (3) ◽  
pp. 442-445
Author(s):  
Dongseok Kwon ◽  
Wonjun Shin ◽  
Jong-Ho Bae ◽  
Suhwan Lim ◽  
Byung-Gook Park ◽  
...  
Keyword(s):  
Schottky Diodes ◽  
Low Frequency ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Noise Characteristics

Methods to isolate retrograde and prograde Rayleigh-wave signals

2019 ◽  
Vol 219 (2) ◽  
pp. 975-994 ◽  
Author(s):  
Gabriel Gribler ◽  
T Dylan Mikesell
Keyword(s):  
Rayleigh Wave ◽  
Time Domain ◽  
Fundamental Mode ◽  
Poisson Ratio ◽  
Low Frequency ◽  
Wave Dispersion ◽  
Low Frequencies ◽  
Retrograde Motion ◽  
Mode Identification ◽  
Time Frequency

SUMMARY Estimating shear wave velocity with depth from Rayleigh-wave dispersion data is limited by the accuracy of fundamental and higher mode identification and characterization. In many cases, the fundamental mode signal propagates exclusively in retrograde motion, while higher modes propagate in prograde motion. It has previously been shown that differences in particle motion can be identified with multicomponent recordings and used to separate prograde from retrograde signals. Here we explore the domain of existence of prograde motion of the fundamental mode, arising from a combination of two conditions: (1) a shallow, high-impedance contrast and (2) a high Poisson ratio material. We present solutions to isolate fundamental and higher mode signals using multicomponent recordings. Previously, a time-domain polarity mute was used with limited success due to the overlap in the time domain of fundamental and higher mode signals at low frequencies. We present several new approaches to overcome this low-frequency obstacle, all of which utilize the different particle motions of retrograde and prograde signals. First, the Hilbert transform is used to phase shift one component by 90° prior to summation or subtraction of the other component. This enhances either retrograde or prograde motion and can increase the mode amplitude. Secondly, we present a new time–frequency domain polarity mute to separate retrograde and prograde signals. We demonstrate these methods with synthetic and field data to highlight the improvements to dispersion images and the resulting dispersion curve extraction.

scholarly journals Multi-scale time-frequency domain full waveform inversion with a weighted local correlation-phase misfit function

2019 ◽  
Vol 16 (6) ◽  
pp. 1017-1031 ◽  
Author(s):  
Yong Hu ◽  
Liguo Han ◽  
Rushan Wu ◽  
Yongzhong Xu
Keyword(s):  
Frequency Domain ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Full Waveform Inversion ◽  
Local Correlation ◽  
Time Frequency ◽  
Model Dependence ◽  
Full Waveform ◽  
Frequency Components

Abstract Full Waveform Inversion (FWI) is based on the least squares algorithm to minimize the difference between the synthetic and observed data, which is a promising technique for high-resolution velocity inversion. However, the FWI method is characterized by strong model dependence, because the ultra-low-frequency components in the field seismic data are usually not available. In this work, to reduce the model dependence of the FWI method, we introduce a Weighted Local Correlation-phase based FWI method (WLCFWI), which emphasizes the correlation phase between the synthetic and observed data in the time-frequency domain. The local correlation-phase misfit function combines the advantages of phase and normalized correlation function, and has an enormous potential for reducing the model dependence and improving FWI results. Besides, in the correlation-phase misfit function, the amplitude information is treated as a weighting factor, which emphasizes the phase similarity between synthetic and observed data. Numerical examples and the analysis of the misfit function show that the WLCFWI method has a strong ability to reduce model dependence, even if the seismic data are devoid of low-frequency components and contain strong Gaussian noise.

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