Automatic microseismic event detection by band-limited phase-only correlation

Wu, Shaojiang; Wang, Yibo; Zhan, Yi; Chang, Xu

doi:10.1016/j.pepi.2016.09.005

Cited by 13 publications

(6 citation statements)

References 13 publications

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“…However, when the main information of a given signal is clustered in a frequency band, the meaningless phase components of the signal reduce the efficiency of the method. In this sense, the Band-Limited Phase-Only Correlation (BLPOC) eliminates meaningless information by extracting an effective region obtained from the compared sequences [21][22][23][24][25][26]. The basic theory of the BLPOC function is described below.…”

Section: Band-limited Phase-only Correlation (Blpoc)mentioning

confidence: 99%

“…where G(k) denotes the complex conjugate of G(k). An effective region is calculated to eliminate the meaningless information in the cross-phase spectrum (depending on the input sequence) [19,26]. Thus, assuming the zero frequency component of the input sequence F(k) is shifted at the center of the spectrum, the range of the effective region (defined by the limits F 1 and F 2 ) is:…”

Section: Band-limited Phase-only Correlation (Blpoc)mentioning

confidence: 99%

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Acoustic Individual Identification in Birds Based on the Band-Limited Phase-Only Correlation Function

et al. 2020

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A new technique based on the Band-Limited Phase-Only Correlation (BLPOC) function to deal with acoustic individual identification is proposed in this paper. This is a biometric technique suitable for limited data individual bird identification. The main advantage of this new technique, in contrast to traditional algorithms where the use of large-scale datasets is assumed, is its ability to identify individuals by the use of only two samples from the bird species. The proposed technique has two variants (depending on the method used to analyze and extract the bird vocalization from records): automatic individual verification algorithm and semi-automatic individual verification algorithm. The evaluation of the automatic algorithm shows an average precision that is over 80% for the identification comparatives. It is shown that the efficiencies of the algorithms depend on the complexity of the vocalizations.

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Section: Band-limited Phase-only Correlation (Blpoc)mentioning

confidence: 99%

Section: Band-limited Phase-only Correlation (Blpoc)mentioning

confidence: 99%

Acoustic Individual Identification in Birds Based on the Band-Limited Phase-Only Correlation Function

et al. 2020

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“…In this sense, the BLPOC function (r f g ) proposes to eliminate the irrelevant information in the sequence by analyzing its inherent frequency band to calculate the cross-phase spectrum only in an effective frequency band [19,20]. In other words, it is intended to eliminate the irrelevant information in the calculation of Rn F G (k)…”

Section: Band-limited Phase-only Correlation (Blpoc)mentioning

confidence: 99%

Limited-data automatic speaker verification algorithm using band-limitedphase-only correlation function

Pedroza¹,

Vargas²,

Hernández³

et al. 2019

Turk J Elec Eng & Comp Sci

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In this paper, a new method to deal with automatic speaker verification based on band-limited phaseonly correlation (BLPOC) is proposed. The aim of this study is to validate the use of the BLPOC function as a new limited-data automatic speaker verification technique. Although some speaker verification techniques have high accuracy, efficiency usually depends on the extraction of complex theoretical information from speech signals and the amount of the data for training the algorithms. The BLPOC function is a high-accuracy biometric technique traditionally implemented in human identification by fingerprints (through image-matching). When applying the BLPOC function in automatic speaker verification through the proposed algorithms (under limited-data conditions), a 98.24% true acceptance rate (TAR) and 87.17% true rejection rate (TRR) in a custom database (and 93.75% TAR and 67.05% TRR in the ELSDSR database) were obtained. The proposed algorithm is a theoretically simple method for automatic speaker verification whose main advantage is that it can provide identification under limited-data conditions. In this sense, the BLPOC function could be applicable in other limited-data biometric identifications by sound signals.

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“…POC evaluates the similarity level by calculating the peak value of the cross-phase spectrum of two two-dimensional (2D) images. Later, POC was applied to identify the similarity of seismic events, diagnose complex diseases, and detect microseismic events [44][45][46]. The two main properties of the POC are as following: (1) the POC function is not influenced by the intensity difference of data because POC only uses the phase information of data; and (2) the peak position of POC will shift when one image is shifted, and the peak value is invariant [44].…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Relative Arrival Time of Microseismic Events Based on Phase-Only Correlation

2018

Self Cite

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The arrival time of a microseismic event is an important piece of information for microseismic monitoring. The accuracy and efficiency of arrival time identification is affected by many factors, such as the low signal-to-noise ratio (SNR) of the records, the vast amount of real-time monitoring records, and the abnormal situations of monitoring equipment. In order to eliminate the interference of these factors, we propose a method based on phase-only correlation (POC) to estimate the relative arrival times of microseismic events. The proposed method includes three main steps:(1) The SNR of the records is improved via time-frequency transform, which is used to obtain the time-frequency representation of each trace of a microseismic event.(2) The POC functions of all pairs of time-frequency representations are calculated. The peak value of the POC function indicates the similarity of the traces, and the peak position in the time lag axis indicates the relative arrival times between the traces. (3) Using the peak values as weighting coefficients of the linear equations, consistency processing is used to exclude any abnormal situations and obtain the optimal relative arrival times. We used synthetic data and field data to validate the proposed method. Comparing with Akaike information criterion (AIC) and cross-correlation, the proposed method is more robust at estimating the relative arrival time and excluding the influence of abnormal situations.

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Automatic microseismic event detection by band-limited phase-only correlation

Cited by 13 publications

References 13 publications

Acoustic Individual Identification in Birds Based on the Band-Limited Phase-Only Correlation Function

Acoustic Individual Identification in Birds Based on the Band-Limited Phase-Only Correlation Function

Limited-data automatic speaker verification algorithm using band-limitedphase-only correlation function

Estimation of the Relative Arrival Time of Microseismic Events Based on Phase-Only Correlation

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