In this paper we elaborate a general expression of the conditional expectation related to pricing problem of the American options using the Malliavin derivative （without localization）. This work is a generalization ...In this paper we elaborate a general expression of the conditional expectation related to pricing problem of the American options using the Malliavin derivative （without localization）. This work is a generalization of paper of Bally et al. （2005） [ 1 ] for the one dimensional case. Basing on the density function of the asset price, Bally and al. used the Malliavin calculus to evaluate the conditional expectation related to pricing American option problem, but in our work we use the Malliavin derivative to resolve the previous problem.展开更多
Separation density is one of the most concerned operating parameters in gravity beneficiation.Although equal-errors cut point or distribution density is usually used as practical separation density in gravity benefici...Separation density is one of the most concerned operating parameters in gravity beneficiation.Although equal-errors cut point or distribution density is usually used as practical separation density in gravity beneficiation, the gravity separating process complexly affected by many kinds of factors is actually carried out at a fluctuant density; namely, the practical separation density is essentially a random variable.The studied results show that the equal-errors cut point is the mathematical expectation of this random variable, and the distribution density corresponds to the highest separation efficiency in the gravity separation process.This shows that the distribution density is the best working point of the gravity separation equipment under a particular operating condition.Therefore,in order to fully develop the function of the gravity separation equipment, the distribution density should be close to the theoretical separation density unlimitedly in the range of minimum fluctuation.展开更多
文摘提出一种基于多示例学习(Multiple-instance learning)的图像检索方法,将多示例学习应用于图像检索中,以有效的处理图像的歧义性。该方法首先将图像作为多示例包,其次采用自适应k-means图像分割算法将图像自动分成多个示例,然后根据用户选择的实例图像生成正包和反包,再采用EM-DD(expectation maximization diverse density)算法进行多示例学习,实现图像检索和相关反馈,最终使用户得到比较满意的结果。
文摘In this paper we elaborate a general expression of the conditional expectation related to pricing problem of the American options using the Malliavin derivative （without localization）. This work is a generalization of paper of Bally et al. （2005） [ 1 ] for the one dimensional case. Basing on the density function of the asset price, Bally and al. used the Malliavin calculus to evaluate the conditional expectation related to pricing American option problem, but in our work we use the Malliavin derivative to resolve the previous problem.
基金Supported by the Young Science Foundation of China(50025411)the Doctoral Science Research Foundation of University(20030290015)
文摘Separation density is one of the most concerned operating parameters in gravity beneficiation.Although equal-errors cut point or distribution density is usually used as practical separation density in gravity beneficiation, the gravity separating process complexly affected by many kinds of factors is actually carried out at a fluctuant density; namely, the practical separation density is essentially a random variable.The studied results show that the equal-errors cut point is the mathematical expectation of this random variable, and the distribution density corresponds to the highest separation efficiency in the gravity separation process.This shows that the distribution density is the best working point of the gravity separation equipment under a particular operating condition.Therefore,in order to fully develop the function of the gravity separation equipment, the distribution density should be close to the theoretical separation density unlimitedly in the range of minimum fluctuation.
