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

Author(s):  
Bo Xie ◽  
Fuqiang Shi ◽  
Sheng Ma ◽  
Feng Li
2020 ◽  
Vol 17 (11) ◽  
pp. 2002-2006 ◽  
Author(s):  
Xiaofang Liao ◽  
Junxing Cao ◽  
Jiangtao Hu ◽  
Jiachun You ◽  
Xudong Jiang ◽  
...  

2018 ◽  
Vol 22 (4) ◽  
pp. 833-840 ◽  
Author(s):  
Yue Li ◽  
Yue Wang ◽  
Hongbo Lin ◽  
Tie Zhong

Genetics ◽  
1983 ◽  
Vol 105 (4) ◽  
pp. 1041-1059
Author(s):  
Takeo Maruyama ◽  
Paul A Fuerst

ABSTRACT The age of a mutant gene is studied using the infinite allele model in which every mutant is new and selectively neutral. Based on a time reversal theory of Markov processes, we develop a method of mathematical analysis that is considerably simpler for calculating the various statistics of the age than previous methods. Formulas for the mean and variance and for the distribution of age are presented together with some examples of relevance to cases in natural populations.—Theoretical studies of the first arrival time of an allele to a specified frequency, given an initially monomorphic condition of the locus, are presented. It is shown that, beginning with an allele that has frequency p = 1 or an allele with frequency p = 1/2N, there is an initial lag phase in which there is virtually no chance of an allele with a specified intermediate frequency appearing in the population. The distribution of the first arrival time is also presented. The distribution shows several characteristics that are not immediately obvious from a consideration of only the mean and variance of first arrival time. Especially noteworthy is the existence of a very long tail to the distribution. We have also studied the distribution of the age of an allele in the population. Again, the distribution of this measure is shown to be more informative for several questions than are the mean and variance alone.


2013 ◽  
Vol 722 ◽  
pp. 239-243 ◽  
Author(s):  
Xiao Hong Liu

The automatic pick of seismic first arrivals is a foundational problem in Seismic Exploration. Picking the first arrival of P-wave is an important problem in the seismic research field. The modulus maxima of wavelet transform is a useful method for picking up the singularities of function. For applying the modulus maxima method to investigate the arrival time of P-wave, it is necessary to eliminate the influence of random factors. Based on standard deviation, we present a method to reduce the influence of random factors. Then we get an approach to detect the arrival time of P-wave by means of window energy ratio factors. The results of data analysis indicate that our method is more effective.


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