Linear systems with fractional Brownian motion and Gaussian noise

被引:8
作者
Grigoriu, Mircea [1 ]
机构
[1] Cornell Univ, Sch Civil & Environm Engn, Ithaca, NY 14853 USA
关键词
fractional Brownian motion; linear random vibration; long range dependence; stochastic processes; stochastic integrals;
D O I
10.1016/j.probengmech.2007.02.004
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Methods are presented for calculating the evolution in time of the second moment properties of the output of linear systems subjected to fractional Brownian motion and fractional Gaussian noise, defined as the formal derivative of fractional Brownian motion. The study also examines whether the output of linear systems to fractional Brownian motion and fractional Gaussian noise exhibits long range dependence. Numerical examples are presented to illustrate the calculation of output statistics for some linear systems with fractional Brownian motion and fractional Gaussian noise input, and show that output of linear systems to these input processes may not have long memory. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:276 / 284
页数:9
相关论文
共 13 条
[1]  
[Anonymous], STOCHASTIC CALCULUS
[2]  
[Anonymous], SELFSIMILAR PROCESSE
[3]  
[Anonymous], 1989, Applied Statistics, DOI DOI 10.2307/2347679
[4]  
Beran J., 1994, Statistics for long-memory processes
[5]  
Brockwell P.J., 1991, Time Series: Theory and Methods
[6]  
Cheridito P, 2003, ELECTRON J PROBAB, V8, P1
[7]  
Mantegna R.N., 2000, INTRO ECONOPHYSICS C
[8]   Stochastic integral equations without probability [J].
Mikosch, T ;
Norvaisa, R .
BERNOULLI, 2000, 6 (03) :401-434
[9]   Integration questions related to fractional Brownian motion [J].
Pipiras, V ;
Taqqu, MS .
PROBABILITY THEORY AND RELATED FIELDS, 2000, 118 (02) :251-291
[10]  
Samorodnitsky G., 1994, STABLE NONGAUSSIAN R