A Study of Weighted and Operator Modified LMSE Algorithms for Probabilistically Defined Inputs,

Abstract

An algorithmic process is developed which minimizes the least mean squared error resulting from a set of input vectors applied to a system such as communications, control, or guidance. These systems are characterized by the need for continual updating in order to remain adaptive to their environment. The results reported in the paper have helped to establish a unifying thread among algorithmic techniques for using probabilistic inputs in such adaptive systems as pattern recognition, control systems optimization techniques, and sequential estimation theory. (Author)

Document Details

Document Type
Technical Report
Publication Date
Apr 04, 1972
Accession Number
AD0740480

Entities

People

  • Lester A. Gerhardt
  • William J. Walbesser

Organizations

  • Bell Aircraft Corporation

Tags

DTIC Thesaurus Topics

  • Adaptive Systems
  • Algorithms
  • Control Systems
  • Cooperation
  • Electrical Engineering
  • Engineering
  • Environment
  • Guidance
  • Heuristic Methods
  • Interdisciplinary Science
  • Mathematics
  • New York
  • Optimization
  • Pattern Recognition
  • Recognition
  • Systems Engineering

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Systems Analysis and Design

Technology Areas

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