Modeling and Classification of Biological Signals.

Abstract

This thesis examines a number of marine biological signals and the problem of modeling by autoregressive techniques using a prony-svd algorithm to accurately represent segments of biological signals. Two methods are employed to classify the biological signals from the model parameters. The first classification method is based on a Neural Network implementation using a commercial software package. The second method is accomplished by using a distance measure, based on spectral ratios, with respect to modeled reference signals.... Autoregressive modeling, Biological classification, Neural networks, Itakura distance measure.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1992
Accession Number
ADA260899

Entities

People

  • Martha M. Vanderkamp

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acoustic Signals
  • Algorithms
  • Artificial Intelligence Software
  • Computer Programs
  • Computers
  • Electrical Engineering
  • Engineering
  • Information Processing
  • Information Science
  • Machine Learning
  • Neural Networks
  • Schools
  • Signal Processing
  • Time Domain
  • United States
  • United States Naval Academy
  • Unsupervised Machine Learning

Fields of Study

  • Engineering

Readers

  • Neural Network Machine Learning.
  • Speech Processing/Speech Recognition.

Technology Areas

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