API Docs

Contents:

• Linear Operators
  • Data types
  • Basic operators
  • Operator calculus
  • Signal processing operators
  • Orthonormal transforms and bases
  • Unions of bases
  • Random compressive sensing operators
  • Operators for special matrices
  • Derivatives (finite differences)
  • Convenience operators
  • Operator parts
  • Properties of a linear operator
  • Utilities
• Sparse Linear Systems
  • Solvers
  • Data types
• Sparsifying Dictionaries and Sensing Matrices
  • Functions for constructing sparsying dictionaries and sensing matrices
  • Dictionary properties
  • Dictionary comparison
  • Grassmannian frames
• Greedy Sparse Recovery
  • Basic Matching Pursuit Based Algorithms
  • Hard Thresholding Based Algorithms
  • Data Types
  • Utilities
  • Using the greedy algorithms
• Convex Relaxation
  • Truncated Newton Interior Points Method (TNIPM)
  • Alternating Directions Methods
  • FOcal Underdetermined System Solver (FOCUSS)
  • Spectral Projected Gradient L1 (SPGL1)
• Optimization
  • Indicator Function Generators
  • Projection Function Generators
  • Smooth Function Generators
  • Proximal Operator Generators
  • Simpler Projection Functions
  • Shrinkage
  • Conjugate Gradient Methods
• First Order Methods
  • API
  • First Order Methods
  • Smooth Conic Dual Problems
  • L1 regularized least square problem
  • LASSO
  • Ordered weighted L1 regularized least square problem
  • The Dantzig selector
• Block Sparsity
  • Problem Formulations
  • Block Sparse Bayesian Learning
• Data Clustering
  • Vector Quantization
  • Spectral Clustering
  • Data types
• Sparse Subspace Clustering
  • SSC-OMP
  • Metrics for quality of sparse subspace clustering
  • Tools for analyzing data (with ground truth)
  • Examples
• Sample Data Generation Utilities
  • Sparse Model Vectors
  • Subspaces
• Test Problems
  • Introduction
  • Problems API
  • List of Problems
• Miscellaneous Algorithms
  • 1-Bit Compressive Sensing
  • Geophysical Signal Processing
  • Computer Vision and Image Processing
• Evaluation Framework
  • Recovery performance of greedy solvers