Implementation of a Novel Multiple Model Algorithm Based on Neural Network

Abstract

In this project, a multiple model method using neural network has been developed. The multiple model method is a technique where the uncertainty is not modeled in only one model. First, multiple models are designed for the uncertainty. Second, each model is scored or estimated using statistical methods. Based on the score of models, the most suitable model is selected.

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Document Details

Document Type
Technical Report
Publication Date
Feb 08, 2005
Accession Number
ADA451744

Entities

People

  • Byung-ha Ahn
  • Daebum Choi

Organizations

  • Gwangju Institute of Science and Technology

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Artificial Intelligence
  • Artificial Intelligence Computing
  • Artificial Intelligence Software
  • Bayesian Networks
  • Computational Science
  • Geometry
  • Kalman Filters
  • Markov Processes
  • Multitarget Tracking
  • Neural Networks
  • Probability
  • Signal Processing
  • Simulations
  • Target Tracking
  • Uncertainty

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks