A first arrival detection method for low SNR microseismic signal

A new method of pitch detection based on morphological filtering is proposed. Noisy speech signal is filtered by morphological filtering to remove the noise and highlight pitch, and then HHT is employed to get Hilbert-Huang spectrum and to calculate instantaneous energy and its derivative. The moment of glottal opening and closing can be accurately located through tracking mutation of instantaneous energy, so that variation of pitch period can be accurately tracked. Compared with other traditional method of pitch detection, this method not only truly describes non-stationary and non-linear characteristics of speech signal, but also it is an adaptive process for the analysis of the speech signal. The experiments showed that the method has strong anti-noise and can accurately detect the pitch of speech in low SNR.

Download Full-text

A robust detection method for micro-Doppler feature of rotating blades under low SNR

IEICE Communications Express ◽

10.1587/comex.2019xbl0074 ◽

2019 ◽

Vol 8 (8) ◽

pp. 363-368

Author(s):

Congshuang Xie ◽

Junjie Li ◽

Qin Chen ◽

Zihao Zhao ◽

Chunyi Song ◽

...

Keyword(s):

Detection Method ◽

Robust Detection ◽

Rotating Blades ◽

Low Snr

Download Full-text

An adaptive speech endpoint detection method in low SNR environments

International Journal of Speech Technology ◽

10.1007/s10772-017-9432-2 ◽

2017 ◽

Vol 20 (3) ◽

pp. 651-658 ◽

Cited By ~ 2

Author(s):

Linhui Sun ◽

Min Su ◽

Zhenzhen Yang

Keyword(s):

Detection Method ◽

Endpoint Detection ◽

Low Snr ◽

Speech Endpoint Detection

Download Full-text

Automatic picking method of microseismic signal first arrival time based on empirical wavelet transform

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/440/5/052055 ◽

2020 ◽

Vol 440 ◽

pp. 052055

Author(s):

Bo Xie ◽

Fuqiang Shi ◽

Sheng Ma ◽

Feng Li

Keyword(s):

Wavelet Transform ◽

Arrival Time ◽

Empirical Wavelet Transform ◽

Automatic Picking ◽

First Arrival ◽

First Arrival Time ◽

Microseismic Signal

Download Full-text

An adaptive change detection method for Pol-SAR images in low SNR circumstance

2013 International Conference on Computational Problem-Solving (ICCP) ◽

10.1109/iccps.2013.6893564 ◽

2013 ◽

Author(s):

Yulin Huang ◽

Yangchi Liu ◽

Xiaoyan Zeng ◽

Jianyu Yang ◽

Haiguang Yang

Keyword(s):

Change Detection ◽

Detection Method ◽

Adaptive Change ◽

Sar Images ◽

Low Snr

Download Full-text

An Improved Method for Pitch Detection

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1049-1050.1167 ◽

2014 ◽

Vol 1049-1050 ◽

pp. 1167-1170

Author(s):

Jin Li ◽

Kun Shen

Keyword(s):

Power Spectrum ◽

Linear Prediction ◽

Detection Method ◽

Pitch Detection ◽

Improved Method ◽

Noisy Environments ◽

Pitch Period ◽

Low Snr ◽

Prediction Residual ◽

Residual Power

Aiming at traditional methods cannot get good performance in noisy environments, an improved method for pitch detection was proposed. In this method, noisy speech was enhanced by using wiener filtering at first, and then analyzing linear prediction residual and power spectrum reprocessing, the feature of weighted residual power spectrum reprocessing was extracted to detect speech pitch period. Experimental results indicate that the proposed pitch detection method has higher reliability with lower computational complexity. It can detect pitch more accurately in low SNR environments and has better robustness.

Download Full-text

A sequential detection method for moving targets under low SNR environments

SICE 2001. Proceedings of the 40th SICE Annual Conference. International Session Papers (IEEE Cat. No.01TH8603) ◽

10.1109/sice.2001.977844 ◽

2002 ◽

Author(s):

H. Kameda ◽

M. Iwamoto ◽

T. Kirimoto ◽

Y. Kosuge

Keyword(s):

Detection Method ◽

Sequential Detection ◽

Moving Targets ◽

Low Snr

Download Full-text

An Efficient Profile Detection Method for Fiber Spectrum Images with Low SNR Based on Wigner Bispectrum

Publications of the Astronomical Society of Australia ◽

10.1071/as11012 ◽

2011 ◽

Vol 28 (2) ◽

pp. 144-149 ◽

Cited By ~ 1

Author(s):

Jia Zhu ◽

Zhangqin Zhu ◽

Zhongfu Ye

Keyword(s):

Fourier Transform ◽

Fast Fourier Transform ◽

Detection Method ◽

Higher Order ◽

Accurate Information ◽

Reconstruction Method ◽

Analysis Method ◽

Low Snr ◽

Higher Order Spectra ◽

Spectrum Data

AbstractAnovel profile detection method is proposed for astronomical fiber spectrum data with low signalto-noise ratio. This approach can be applied to the pretreatment for 2-D astronomical spectrum data before the extraction of spectra. The Wigner bispectrum, a classical higher-order spectrum analysis method, is introduced and applied to deal with the spectrumsignal in this article.After analyzing the Wigner higher-order spectra distribution of the target profile signal, the combination of the Wigner bispectrum algorithm and the fast Fourier transform algorithm is used to weaken the effect of the noise to obtain more accurate information. Both the reconstruction method of the Wigner bispectrum and inverse fast Fourier transform are used to acquire the detection signal. At the end of this paper, experiments with both simulated and observed data based on the Large Sky Area Multi-Object Fiber Spectroscopy Telescope project are presented to demonstrate the effectiveness of the proposed method.

Download Full-text