Class-Specific Iterated Subspace Classifier Cross-Reference to Related Patent Applications

Abstract

A method is provided for calculating a class-specific iterated subspace for a classification system utilized in a computing system. Training data in the specific class for the class-specific iterated subspace is collected. A linear orthogonal transform is applied transforming the data into at least one bin. Magnitude squared bins are calculated and used as columns of a matrix. Orthonormal vectors of this matrix are selected and a J function is calculated. The J function and orthonormal starting vectors are used to obtain the class-specific iterated subspace for each class. The method further applies these class-specific iterated subspaces in a classification system for determining the most likely class of a data signal of interest.

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Document Details

Document Type
Technical Report
Publication Date
Dec 30, 2009
Accession Number
ADD020426

Entities

People

  • Paul Baggenstoss

Organizations

  • United States Department of the Navy

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Automated Speech Recognition
  • Classification
  • Data Science
  • Dimensionality Reduction
  • Discrete Fourier Transforms
  • Hidden Markov Models
  • Information Science
  • Machine Learning
  • Markov Models
  • Patent Applications
  • Patents
  • Probabilistic Models
  • Probability
  • Probability Density Functions
  • Signal Processing
  • Training

Fields of Study

  • Engineering

Readers

  • Aerospace Engineering.
  • Calculus or Mathematical Analysis
  • Image Processing and Computer Vision.