Theory and Applications of Compressed Sensing (Q166746): Difference between revisions

From geokb
(‎Created a new Item: Added new OpenAlex topic claimed by USGS staff from API)
 
(‎Changed label, description and/or aliases in en, and other parts: modified description with assistance from Llama 3.1)
description / endescription / en
This cluster of papers focuses on the theory and applications of compressed sensing, including sparse representation, signal recovery, convex optimization, matrix completion, dictionary learning, orthogonal matching pursuit, robust reconstruction, an
"Analyzing sparse signals & recovering information from compressed data using mathematical optimization techniques."

Revision as of 13:14, 30 August 2024

"Analyzing sparse signals & recovering information from compressed data using mathematical optimization techniques."
  • Compressed Sensing
  • Sparse Representation
  • Signal Recovery
  • Convex Optimization
  • Matrix Completion
  • Sparse Approximation
  • Dictionary Learning
  • Orthogonal Matching Pursuit
  • Robust Reconstruction
  • Sparsity in Signal Processing
Language Label Description Also known as
English
Theory and Applications of Compressed Sensing
"Analyzing sparse signals & recovering information from compressed data using mathematical optimization techniques."
  • Compressed Sensing
  • Sparse Representation
  • Signal Recovery
  • Convex Optimization
  • Matrix Completion
  • Sparse Approximation
  • Dictionary Learning
  • Orthogonal Matching Pursuit
  • Robust Reconstruction
  • Sparsity in Signal Processing

Statements

 
Retrieved from "https://geokb.wikibase.cloud/w/index.php?title=Item:Q166746&oldid=1123049"