Quantized Overcomplete Expansions: Analysis, Synthesis and Algorithms

Abstract

Linear transforms and expansions are the fundamental mathematical tools of signal processing. Yet the properties of linear expansions in the presence of coefficient quantization are not yet fully understood. These properties are most interesting when signal representations are with respect to redundant, or overcomplete, sets of vectors. Exploring the of quantization in overcomplete linear expansions is the unifying theme of this work. Two classes of overcomplete expansions were considered: fixed (frame) expansions and expansions that are adapted to the particular source sample, as given by matching pursuit.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1995
Accession Number
ADA637169

Entities

People

  • Vivek K Goyal

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Coding
  • Computational Science
  • Computer Programming
  • Computer Science
  • Eigenvalues
  • Engineering
  • Linear Programming
  • Mathematics
  • Notation
  • Numbers
  • Probability
  • Random Variables
  • Sequences
  • Simulations
  • Statistics
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Neural Network Machine Learning.