Sparse and Compressive Sensing Techniques

Sparse and Compressive Sensing Techniques is a research topic within Computational Mechanics. Science Explorer counts 27k research works in it since 1959. 9.7% of them reached the world's top 10% most cited for their field and year.

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, and sparsity in signal processing.

• Compressed Sensing
• Sparse Representation
• Signal Recovery
• Convex Optimization
• Matrix Completion
• Sparse Approximation
• Dictionary Learning
• Orthogonal Matching Pursuit
• Robust Reconstruction
• Sparsity in Signal Processing