Explore MATLAB source code curated for "重构信号" with clean implementations, documentation, and examples.
Signal Reconstruction via L1-Norm Minimization Algorithms and Orthogonal Matching Pursuit Method in Compressed Sensing with Code Implementation Insights
Orthogonal Matching Pursuit (OMP) Algorithm Based on Compressed Sensing - Efficient Signal Reconstruction with Code Implementation
Implementing singular value decomposition on a signal to identify optimal reconstruction points through differential spectrum analysis, achieving effective noise reduction while preserving key signal characteristics through selective component reconstruction.
Sparse Adaptive Matching Pursuit algorithm enables reconstruction of original signals without requiring prior knowledge of sparsity levels, with key functions involving iterative support detection and residual minimization.
A custom implementation of the fast wavelet transform based on Mallat algorithm using 'db1' wavelet function, featuring data truncation via wkeep command during convolution operations. The reconstructed signal demonstrates minimal error when compared with the original signal.
Perform wavelet packet decomposition on bearing fault signals, reconstruct the frequency band signal with maximum energy, and calculate sample entropy for the reconstructed signal