Moment invariants firstly introduced by M. K Hu in 1962, has some shortcomings. After counting a large number of statistical distribution information of Chinese characters,the authors put forward the concept of inform...Moment invariants firstly introduced by M. K Hu in 1962, has some shortcomings. After counting a large number of statistical distribution information of Chinese characters,the authors put forward the concept of information moments and demonstrate its invariance to translation,rotation and scaling.Also they perform the experiment in which information moments compared with moment invaiants for the effects of similar Chinese characters and font recognition.At last they show the recognition rate of 88% by information moments,with 70% by moment inariants.展开更多
为研究串联系统下多部件应力-强度模型的可靠性问题,基于Kumaraswamy分布,采用极大似然法给出参数及应力-强度模型可靠度的极大似然估计(maximum likelihood estimation,MLE);再利用Jeffreys准则构造无信息先验分布,运用马尔可夫链蒙特...为研究串联系统下多部件应力-强度模型的可靠性问题,基于Kumaraswamy分布,采用极大似然法给出参数及应力-强度模型可靠度的极大似然估计(maximum likelihood estimation,MLE);再利用Jeffreys准则构造无信息先验分布,运用马尔可夫链蒙特卡洛(Markov chain Monte Carlo,MCMC)方法给出参数及应力-强度模型可靠度的贝叶斯估计;最后,利用逆矩估计方法给出参数及应力-强度模型可靠度的逆矩估计(inverse moment estimation,IME)。数值模拟结果表明,在不同系统可靠度及不同样本量条件下,通过对3种估计方法的数值进行比较发现贝叶斯估计效果最好,IME优于MLE。该研究为探讨串联系统多部件应力-强度模型可靠性提供了一定的理论基础。展开更多
Determining the number of components is a crucial issue in a mixture model. A moment-based criterion is considered to estimate the number of components arising from a normal mixture model. This criterion is derived fr...Determining the number of components is a crucial issue in a mixture model. A moment-based criterion is considered to estimate the number of components arising from a normal mixture model. This criterion is derived from an omnibus statistic involving the skewness and kurtosis of each component. The proposed criterion additionally provides a measurement for the model fit in an absolute sense. The performances of our criterion are satisfactory compared with other classical criteria through Monte-Carlo experiments.展开更多
Zernike moments (ZMs) are a set of orthogonal moments which have been successfully used in the fields of image processing and pattern recognition. A combination of edge blurring with ZMs computation was introduced. In...Zernike moments (ZMs) are a set of orthogonal moments which have been successfully used in the fields of image processing and pattern recognition. A combination of edge blurring with ZMs computation was introduced. In this study, several kinds of artificial binary stripe images were used to investigate the effects of edge blurring on the absolute mean error of reconstructed image from high-order ZMs. After the blurring process, the reconstruction errors were increased dramatically at edge pixels, but decreased on non-edge pixels. The experimental results demonstrated that 2-pixel blurring approach provided better performance for reducing reconstruction error. Finally, a template matching between two real images was simulated to illustrate the effectiveness of the proposed method.展开更多
The disadvantages of IR images mostly include high noise, blurry edge and so on. The characteristics make the existent smoothing methods ineffective in preserving edge. To solve this problem, a piecewise moment filter...The disadvantages of IR images mostly include high noise, blurry edge and so on. The characteristics make the existent smoothing methods ineffective in preserving edge. To solve this problem, a piecewise moment filter (PMF) is put forward. By using moment and piecewise linear theory, the filter can preserve edge. Based on the statistical model of random noise, a related-coefficient method is presented to estimate the variance of noise. The edge region and model are then detected by the estimated variance. The expectation of first-order derivatives is used in getting the reliable offset of edge. At last, a fast moment filter of double-stair edge model is used to gain the piecewise smoothing results and reduce the calculation. The experimental result shows that the new method has a better capability than other methods in suppressing noise and preserving edge.展开更多
基金supported by the Specical Fund of Taishan Scholar of Shandong Province
文摘Moment invariants firstly introduced by M. K Hu in 1962, has some shortcomings. After counting a large number of statistical distribution information of Chinese characters,the authors put forward the concept of information moments and demonstrate its invariance to translation,rotation and scaling.Also they perform the experiment in which information moments compared with moment invaiants for the effects of similar Chinese characters and font recognition.At last they show the recognition rate of 88% by information moments,with 70% by moment inariants.
文摘为研究串联系统下多部件应力-强度模型的可靠性问题,基于Kumaraswamy分布,采用极大似然法给出参数及应力-强度模型可靠度的极大似然估计(maximum likelihood estimation,MLE);再利用Jeffreys准则构造无信息先验分布,运用马尔可夫链蒙特卡洛(Markov chain Monte Carlo,MCMC)方法给出参数及应力-强度模型可靠度的贝叶斯估计;最后,利用逆矩估计方法给出参数及应力-强度模型可靠度的逆矩估计(inverse moment estimation,IME)。数值模拟结果表明,在不同系统可靠度及不同样本量条件下,通过对3种估计方法的数值进行比较发现贝叶斯估计效果最好,IME优于MLE。该研究为探讨串联系统多部件应力-强度模型可靠性提供了一定的理论基础。
基金supported by the National Natural Sciences Foundation of China(7137102271401193+2 种基金71671193)the Program for Innovation Research in Central University of Finance and Economicsthe Innovation Foundation of BUAA for Ph.D.Graduates
文摘Determining the number of components is a crucial issue in a mixture model. A moment-based criterion is considered to estimate the number of components arising from a normal mixture model. This criterion is derived from an omnibus statistic involving the skewness and kurtosis of each component. The proposed criterion additionally provides a measurement for the model fit in an absolute sense. The performances of our criterion are satisfactory compared with other classical criteria through Monte-Carlo experiments.
文摘Zernike moments (ZMs) are a set of orthogonal moments which have been successfully used in the fields of image processing and pattern recognition. A combination of edge blurring with ZMs computation was introduced. In this study, several kinds of artificial binary stripe images were used to investigate the effects of edge blurring on the absolute mean error of reconstructed image from high-order ZMs. After the blurring process, the reconstruction errors were increased dramatically at edge pixels, but decreased on non-edge pixels. The experimental results demonstrated that 2-pixel blurring approach provided better performance for reducing reconstruction error. Finally, a template matching between two real images was simulated to illustrate the effectiveness of the proposed method.
基金Aeronautic Basic Science Foundation of China(04I53067) .
文摘The disadvantages of IR images mostly include high noise, blurry edge and so on. The characteristics make the existent smoothing methods ineffective in preserving edge. To solve this problem, a piecewise moment filter (PMF) is put forward. By using moment and piecewise linear theory, the filter can preserve edge. Based on the statistical model of random noise, a related-coefficient method is presented to estimate the variance of noise. The edge region and model are then detected by the estimated variance. The expectation of first-order derivatives is used in getting the reliable offset of edge. At last, a fast moment filter of double-stair edge model is used to gain the piecewise smoothing results and reduce the calculation. The experimental result shows that the new method has a better capability than other methods in suppressing noise and preserving edge.
