Simultaneous Approximation by Greedy Algorithms

Abstract

In this paper we study nonlinear approximation. The basic idea behind nonlinear approximation is that the elements used in the approximation do not come from a fixed linear space but are allowed to depend on the function being approximated. The classical problem in this regard is the problem of m-term approximation where one fixed a basis in the space, and seeks to approximate a target function f by a linear combination of m terms from that basis. When the basis is a wavelet basis or a basis of other waveforms, then this type of approximation is the starting point for compression algorithms.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2003
Accession Number
ADA619364

Entities

People

  • D. Leviatan
  • V. N. Temlyakov

Organizations

  • University of South Carolina

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Availability
  • Classification
  • Compression
  • Contracts
  • Data Compression
  • Information Operations
  • Instructions
  • Mathematics
  • Monitoring
  • Security
  • South Carolina
  • Standards
  • Universities
  • Waveforms

Readers

  • Approximation Theory.
  • Graph Algorithms and Convex Optimization.

Technology Areas

  • Space