A Martingale Approach to Modeling, Estimation and Detection of Jump Processes.

Abstract

The study contains a systematic approach to problems of modeling, nonlinear estimation and detection of signals in jump-type observations, namely processes whose paths are discontinuous. It is shown that modern martingale theory provides a powerful tool for attacking these problems in a unified and rigorous manner. A general model for describing signals in jump observations is presented. It is shown that a martingale model includes all the previously proposed ones and also covers the difficult case of past-dependent signals that arises in feedback communication and control problems. (Modified author abstract)

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1973
Accession Number
AD0770554

Entities

People

  • Adrian Segall

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Detection
  • Feedback
  • Observation

Fields of Study

  • Engineering
  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Control Systems Engineering.
  • Underwater engineering and Marine Technology.

Technology Areas

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