For random noise suppression of seismic data, we present a non-local Bayes （NL- Bayes） filtering algorithm. The NL-Bayes algorithm uses the Gaussian model instead of the weighted average of all similar patches in th...For random noise suppression of seismic data, we present a non-local Bayes （NL- Bayes） filtering algorithm. The NL-Bayes algorithm uses the Gaussian model instead of the weighted average of all similar patches in the NL-means algorithm to reduce the fuzzy of structural details, thereby improving the denoising performance. In the denoising process of seismic data, the size and the number of patches in the Gaussian model are adaptively calculated according to the standard deviation of noise. The NL-Bayes algorithm requires two iterations to complete seismic data denoising, but the second iteration makes use of denoised seismic data from the first iteration to calculate the better mean and covariance of the patch Gaussian model for improving the similarity of patches and achieving the purpose of denoising. Tests with synthetic and real data sets demonstrate that the NL-Bayes algorithm can effectively improve the SNR and preserve the fidelity of seismic data.展开更多
The purpose of this work is to investigate the asymptotic properties of a stochastic Gilpin--Ayala population system under regime switching on patches. We establish the global stability and the extinction of the trivi...The purpose of this work is to investigate the asymptotic properties of a stochastic Gilpin--Ayala population system under regime switching on patches. We establish the global stability and the extinction of the trivial equilibrium state of the model. Further- more, we show the existence of the stationary distribution for our system model. The analytical results are illustrated by computer simulations.展开更多
文摘针对C语言白盒测试用例自动生成问题,提出一套基于过程间的动态符号执行框架,建立基于Def-Use链和函数执行树的模型。以函数为单位进行约束收集,解决函数调用中实参和形参的符号统一问题;对过程间动态符号执行的SMART(systematic modular automated random testing)算法进行改进,利用其计算和使用函数摘要,提高动态符号执行的效率和可行性。该方案为C语言过程间测试自动化工具的实现提供了详细的解决方案。
基金financially sponsored by Research Institute of Petroleum Exploration&Development(PETROCHINA)Scientific Research And Technology Development Projects(No.2016ycq02)China National Petroleum Corporation Science&Technology Development Projects(No.2015B-3712)Ministry of National Science&Technique(No.2016ZX05007-006)
文摘For random noise suppression of seismic data, we present a non-local Bayes （NL- Bayes） filtering algorithm. The NL-Bayes algorithm uses the Gaussian model instead of the weighted average of all similar patches in the NL-means algorithm to reduce the fuzzy of structural details, thereby improving the denoising performance. In the denoising process of seismic data, the size and the number of patches in the Gaussian model are adaptively calculated according to the standard deviation of noise. The NL-Bayes algorithm requires two iterations to complete seismic data denoising, but the second iteration makes use of denoised seismic data from the first iteration to calculate the better mean and covariance of the patch Gaussian model for improving the similarity of patches and achieving the purpose of denoising. Tests with synthetic and real data sets demonstrate that the NL-Bayes algorithm can effectively improve the SNR and preserve the fidelity of seismic data.
文摘The purpose of this work is to investigate the asymptotic properties of a stochastic Gilpin--Ayala population system under regime switching on patches. We establish the global stability and the extinction of the trivial equilibrium state of the model. Further- more, we show the existence of the stationary distribution for our system model. The analytical results are illustrated by computer simulations.
