This paper presents limit theorems for realized power variation of processes of the form Xt=t0φsdGs+ξt as the sampling frequency within a fixed interval increases to infinity.Here G is a Gaussian process with statio...This paper presents limit theorems for realized power variation of processes of the form Xt=t0φsdGs+ξt as the sampling frequency within a fixed interval increases to infinity.Here G is a Gaussian process with stationary increments,ξis a purely non-Gaussian L′evy process independent from G,andφis a stochastic process ensuring that the integral is well defined as a pathwise Riemann-Stieltjes integral.We obtain the central limit theorems for the case that both the continuous term and the jump term are presented simultaneously in the law of large numbers.展开更多
文摘对于快时变信道[1],基扩展模型(Basic Expansion Model,BEM)能很好地捕捉信道的时变特性,并能有效模拟信道的传输情况,进而常用于信道建模。本文提出了一种基于RLS自适应滤波跟踪的信道估计方法。自适应滤波器本身有一个重要的算法,即递归最小二乘(Recursive least squares,RLS)算法。文章利用RLS自适应滤波算法对BEM基系数g进行跟踪,并将其自适应的调整大小,然后对信道响应进行估计。为验证所提方法的性能,本文对所提算法与LS配合插值算法进行仿真对比。仿真结果表明,所提方法相较LS算法有很好的估计精度。
基金supported by National Natural Science Foundation of China(Grant Nos.11071045 and 11226201)Natural Science Foundation of Jiangsu Province of China(Grant No.BK20131340)+1 种基金Social Science Foundation of Chinese Ministry of Education(Grant No.12YJCZH128)QingLan Project ofthe Priority Academic Program Development of Jiangsu Higher Education Institutions(Auditing Science and Technology)
文摘This paper presents limit theorems for realized power variation of processes of the form Xt=t0φsdGs+ξt as the sampling frequency within a fixed interval increases to infinity.Here G is a Gaussian process with stationary increments,ξis a purely non-Gaussian L′evy process independent from G,andφis a stochastic process ensuring that the integral is well defined as a pathwise Riemann-Stieltjes integral.We obtain the central limit theorems for the case that both the continuous term and the jump term are presented simultaneously in the law of large numbers.
