Title :
Strong laws of large numbers under weak assumptions with application
Author_Institution :
Dept. of Electr. & Comput. Eng., Newcastle Univ., NSW, Australia
fDate :
11/1/2000 12:00:00 AM
Abstract :
The employment of "strong laws of large numbers" is instrumental to the analysis of system estimation and identification strategies. However, the vast bulk of such laws, as presented in the wider literature, assume independence or at least uncorrelatedness of random components, and these assumptions are quite restrictive from an engineering point of view. By way of contrast, the paper shows how to establish strong laws for possibly nonstationary random processes with very general dependence structure. A brief example is provided that illustrates the utility of the strong law of large numbers presented.
Keywords :
identification; random processes; possibly nonstationary random processes; random components; strong laws of large numbers; system estimation; Convergence; Employment; Estimation error; Independent component analysis; Instruments; Parameter estimation; Performance analysis; Random processes; Random variables; Stochastic processes;
Journal_Title :
Automatic Control, IEEE Transactions on