MATLAB Implementation of Regularized Orthogonal Matching Pursuit (ROMP) Algorithm
A MATLAB source code implementation of the Regularized Orthogonal Matching Pursuit (ROMP) algorithm packaged as a reusable function with comprehensive documentation
Sparse Representation Orthogonal Matching Pursuit Algorithm MATLAB Source Code
MATLAB implementation of the Orthogonal Matching Pursuit algorithm for sparse signal representation with detailed code documentation and practical applications
Optimized Orthogonal Matching Pursuit Algorithm for Compressed Sensing Signal Recovery
This implementation presents an enhanced compressed sensing signal recovery algorithm that improves upon the greedy iterative Orthogonal Matching Pursuit (OMP) method. The conventional OMP algorithm selects suboptimal atoms during each iteration, failing to maximize residual reduction. Our Optimised_OMP algorithm ensures selected atoms remain orthogonal to the subspace spanned by previously chosen atoms, enabling faster residual reduction and accelerated convergence. The code implements optimal atom selection through Gram-Schmidt orthogonalization or QR decomposition techniques.
Algorithms for Matching Pursuit and Orthogonal Matching Pursuit
Implementation of Matching Pursuit and Orthogonal Matching Pursuit algorithms for time-frequency analysis with code-level optimizations and mathematical foundations.
Compressive Sensing, MATLAB, Signal Reconstruction
Compressive Sensing, MATLAB, Signal Reconstruction, Orthogonal Matching Pursuit, Breaking Nyquist Theorem
A Recovery Algorithm for Compressed Sensing: Regularized Orthogonal Matching Pursuit
An exploration of compressed sensing recovery algorithms focusing on Regularized Orthogonal Matching Pursuit (ROMP), including implementation principles and application scenarios in signal processing and machine learning.
Orthogonal Matching Pursuit Source Code Implementation
MATLAB implementation of Orthogonal Matching Pursuit algorithm featuring clear, practical code structure with optimized signal reconstruction capabilities.
Signal Processing Applications of Compressed Sensing
Signal Processing Applications of Compressed Sensing with Algorithm Implementation Details