Explore MATLAB source code curated for "匹配追踪算法" with clean implementations, documentation, and examples.
A custom-built code implementation for compressive sensing based on the matching pursuit algorithm, ready for direct invocation with bilingual documentation including Chinese comments. The implementation demonstrates sparse signal recovery through iterative optimization, featuring modular functions for signal processing, dictionary generation, and residual minimization.
Compressive Sampling Matching Pursuit (CoSaMP) algorithm for sparse signal reconstruction in compressed sensing systems
Matching pursuit algorithm based on dictionary learning for sparse signal representation, including MATLAB implementation with detailed code examples and comprehensive theoretical explanations.
This implementation processes speech signals through a Gabor atom dictionary using matching pursuit algorithm. The program demonstrates excellent performance with successful simulation experiments on various speech signals, featuring efficient sparse representation and signal reconstruction capabilities.
Implementation of 2D image sparse decomposition based on matching pursuit algorithm using FFT acceleration for efficient feature extraction and representation.
A highly precise matching pursuit algorithm based on wavelet transform, recommended for signal decomposition applications with enhanced time-frequency resolution
OMP Algorithm: Implementation of Matching Pursuit method that takes dictionary and image as inputs to compute sparse coefficients representing the image in the dictionary space, with detailed explanations and code insights.
Matching Pursuit Algorithm for one-dimensional signals, capable of accurately reconstructing signals using relatively few atoms for comparison
Implementation of the Least Squares Matching Pursuit Algorithm Using Morlet Wavelet for Signal Processing
Implementation of matching pursuit algorithm using wavelet transform, delivering excellent performance and robust target tracking capabilities