为有效抑制电力线通信(power line communication,PLC)系统中的脉冲噪声,从信号被脉冲噪声影响后正态性被破坏的角度出发,文章提出一种基于广义幂变换的脉冲噪声抑制方法。该方法首先引入Box-Cox变换,通过对接收信号进行幂变换处理,使...为有效抑制电力线通信(power line communication,PLC)系统中的脉冲噪声,从信号被脉冲噪声影响后正态性被破坏的角度出发,文章提出一种基于广义幂变换的脉冲噪声抑制方法。该方法首先引入Box-Cox变换,通过对接收信号进行幂变换处理,使其分布更接近正态分布,又通过推导引入新的零记忆非线性(zero memory non-linearity,ZMNL)函数,以便进一步优化处理效果。此种结合ZMNL函数的Box-Cox变换可改善接收信号的正态性,实现对脉冲噪声的抑制。仿真结果验证所提广义幂变换方法对接收信号的正态性改善效果明显,对脉冲噪声有良好的抑制效果,并且与传统消隐法相比效果更好。展开更多
The case when the source of information provides precise belief function/mass, within the generalized power space, has been studied by many people. However, in many decision situations, the precise belief structure is...The case when the source of information provides precise belief function/mass, within the generalized power space, has been studied by many people. However, in many decision situations, the precise belief structure is not always available. In this case, an interval-valued belief degree rather than a precise one may be provided. So, the probabilistic transformation of imprecise belief function/mass in the generalized power space including Dezert-Smarandache （DSm） model from scalar transformation to sub-unitary interval transformation and, more generally, to any set of sub-unitary interval transformation is provided. Different from the existing probabilistic transformation algorithms that redistribute an ignorance mass to the singletons involved in that ignorance pro- portionally with respect to the precise belief function or probability function of singleton, the new algorithm provides an optimization idea to transform any type of imprecise belief assignment which may be represented by the union of several sub-unitary （half-） open intervals, （half-） closed intervals and/or sets of points belonging to [0,1]. Numerical examples are provided to illustrate the detailed implementation process of the new probabilistic transformation approach as well as its validity and wide applicability.展开更多
文摘为有效抑制电力线通信(power line communication,PLC)系统中的脉冲噪声,从信号被脉冲噪声影响后正态性被破坏的角度出发,文章提出一种基于广义幂变换的脉冲噪声抑制方法。该方法首先引入Box-Cox变换,通过对接收信号进行幂变换处理,使其分布更接近正态分布,又通过推导引入新的零记忆非线性(zero memory non-linearity,ZMNL)函数,以便进一步优化处理效果。此种结合ZMNL函数的Box-Cox变换可改善接收信号的正态性,实现对脉冲噪声的抑制。仿真结果验证所提广义幂变换方法对接收信号的正态性改善效果明显,对脉冲噪声有良好的抑制效果,并且与传统消隐法相比效果更好。
基金supported by the National Natural Science Foundation of China (60572161 60874105)+5 种基金the Excellent Ph.D. Paper Author Foundation of China (200443)the Postdoctoral Science Foundation of China (20070421094)the Program for New Century Excellent Talents in University (NCET-08-0345)the Shanghai Rising-Star Program(09QA1402900)the "Chenxing" Scholarship Youth Found of Shanghai Jiaotong University (T241460612)the Ministry of Education Key Laboratory of Intelligent Computing & Signal Processing (2009ICIP03)
文摘The case when the source of information provides precise belief function/mass, within the generalized power space, has been studied by many people. However, in many decision situations, the precise belief structure is not always available. In this case, an interval-valued belief degree rather than a precise one may be provided. So, the probabilistic transformation of imprecise belief function/mass in the generalized power space including Dezert-Smarandache （DSm） model from scalar transformation to sub-unitary interval transformation and, more generally, to any set of sub-unitary interval transformation is provided. Different from the existing probabilistic transformation algorithms that redistribute an ignorance mass to the singletons involved in that ignorance pro- portionally with respect to the precise belief function or probability function of singleton, the new algorithm provides an optimization idea to transform any type of imprecise belief assignment which may be represented by the union of several sub-unitary （half-） open intervals, （half-） closed intervals and/or sets of points belonging to [0,1]. Numerical examples are provided to illustrate the detailed implementation process of the new probabilistic transformation approach as well as its validity and wide applicability.
