A Comparison of Two Noise Canceling System Algorithms.

Abstract

The purpose of this study is to compare two noise canceling system algorithms when the number of inputs to the system is small. The expected value algorithm is an estimate of the optimum solution for minimum mean square error analysis. The LMS (least mean square) algorithm was developed to avoid the matrix inversion inherent in the optimum solution given by the Wiener-Hopf equation. The comparison between the two algorithms is measured by the rate of convergence of the mean square error and the minimum error after five hundred iterations. A computer simulation of a dc signal in Gaussian noise provided the comparison between the two algorithms. The tradeoff in terms of performance for simplicity in the LMS algorithm was discovered to be great. The expected value algorithm consistently produced better results in terms of faster rates of convergence and smaller minimum errors after five hundred iterations.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1977
Accession Number
ADA055822

Entities

People

  • Rachel Patricia Messina

Organizations

  • Duke University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Closed Loop Systems
  • Computational Science
  • Computer Programs
  • Computer Simulations
  • Computers
  • Differential Equations
  • Electrical Engineering
  • Equations
  • Gaussian Noise
  • Information Theory
  • Military Research
  • Navy
  • Schools
  • Signal Detection
  • Signal Processing
  • Simulations

Fields of Study

  • Engineering

Readers

  • Calculus or Mathematical Analysis
  • Speech Processing/Speech Recognition.
  • Statistical inference.