Change-Point Detection and Adaptive Control of Time-Varying Systems

Abstract

Fundamental progress was made in the sequential and fixed sample detection and estimation of abrupt changes in stochastic systems and in the related problem of adaptive control of dynamical systems with time varying parameters. Advances were also made in recursive estimation and adaptive control of linear stochastic systems, optimal sequential testing of composite hypotheses, and regression analysis of censored failure time data.

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Document Details

Document Type
Technical Report
Publication Date
Sep 08, 1993
Accession Number
ADA273509

Entities

People

  • David Siegmund

Organizations

  • Stanford University

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Asymptotic Normality
  • Change Detection
  • Composite Materials
  • Data Science
  • Decision Theory
  • Detection
  • High Resolution
  • Hypotheses
  • Information Science
  • Medical Genetics
  • Regression Analysis
  • Sequential Analysis
  • Statistical Analysis
  • Statistical Decision Theory
  • Statistics

Fields of Study

  • Engineering

Readers

  • Statistical inference.
  • Theoretical Analysis.