Title :
Maximum entropy models: convergence rates and applications in dynamic system monitoring
Author :
Liang, Gang ; Yu, Bin ; Taft, N.
Author_Institution :
California Univ., Berkeley, CA, USA
fDate :
27 June-2 July 2004
Abstract :
The convergence rates of generalized iterative scaling (GIS) and improved iterative scaling (IIS) algorithms for fitting maximum entropy (ME) models are investigated and also a particular linear dynamic system monitoring with partial active measurements is studied. An information-theoretic based measurement scheme is derived to select informative hidden states, which is validated on a problem of origin-destination matrix estimation for Internet traffic.
Keywords :
Internet; convergence; hidden Markov models; iterative methods; linear systems; matrix algebra; maximum entropy methods; system monitoring; telecommunication traffic; GIS; IIS; Internet traffic; convergence rate; generalized iterative scaling algorithm; improved iterative scaling algorithm; information-theory; linear dynamic system monitoring; maximum entropy model; origin-destination matrix estimation; Convergence; Entropy; Geographic Information Systems; Hidden Markov models; Internet; Iterative algorithms; Monitoring; Particle measurements; State estimation; Traffic control;
Conference_Titel :
Information Theory, 2004. ISIT 2004. Proceedings. International Symposium on
Print_ISBN :
0-7803-8280-3
DOI :
10.1109/ISIT.2004.1365207
