Probabilistic and Statistical Analysis of Complex Stochastic Networks

Abstract

The research objective of this proposal is on analyzing long time asymptotics, control and statistical inference problems for wide family of stochastic network systems to address fundamental issues arising from data-intensive network applications. Our methodology is based on weak convergence approximations for the network systems critical loading, stochastic simulations, applying statistical inference methods stochastic differential equations to the limit approximating models.

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Document Details

Document Type
Technical Report
Publication Date
Jun 02, 2017
Accession Number
AD1058676

Entities

People

  • Chihoon Lee

Organizations

  • Colorado State University

Tags

Communities of Interest

  • Biomedical
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Computational Science
  • Data Analysis
  • Data Science
  • Differential Equations
  • Engineering
  • Environment
  • Equations
  • Information Science
  • Markov Processes
  • Network Science
  • Operations Research
  • Probability
  • Queueing Theory
  • Random Variables
  • Simulations
  • Statistical Analysis
  • Statistical Inference
  • Statistics
  • Stochastic Processes
  • Weak Convergence

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Distributed Systems and Data Platform Development
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms