CR-Sparse¶
A JAX/XLA based library of accelerated models and algorithms for inverse problems in sparse representation and compressive sensing. GITHUB.
Contents:
- Quick Start
- Introduction
- Tutorials
- API Docs
- Digital Signal Processing
- Wavelets
- Linear Operators
- Sparse Linear Systems
- Sparsifying Dictionaries and Sensing Matrices
- Greedy Sparse Recovery
- L1 Minimization
- First Order Conic Solvers
- Compressive Sensing
- Data Clustering
- Sparse Subspace Clustering
- Sample Data Generation Utilities
- Utilities in cr.sparse module
- Linear Algebra
- Optimization
- Geophysical Signal Processing
- Computer Vision and Image Processing
- Evaluation Framework
- Algorithms
- Theory
- Examples Gallery
- References
- Development
Concept Map
Wavelets
Haar, Daubechies, Symlets, Coiflets, Biorthogonal, Reverse biorthogonal, Discrete Meyer
dwt, idwt, upcoef, downcoef
wavedec, waverec
dwt2, idwt2
Linear Operators
identity, matrix, diagonal, zero, flipud, sum, pad_zeros, symmetrize, restriction
running_average, fir_filter
fourier_basis, dirac_fourier_basis, cosine_basis, walsh_hadamard_basis
gaussian_dict, rademacher_dict, random_onb_dict, random_orthonormal_rows_dict
circulant
first_derivative, second_derivative
neg, scale, add, subtract, compose, transpose, hermitian, hcat, power
Dictionaries
gaussian, rademacher, dirac fourier, dirac cosine,
Sparse Recovery
Greedy Recovery Algorithms: OMP, CoSaMP, SP, IHT, NIHT, HTP, NHTP,
Convex Optimization Algorithms: TNIPM, ADMM,
Linear Algebra Routines
Triangular systems
Evaluation Framework
Sample Data Generation
Utilities
