MATLAB Simulation Code for Signal Sparse Decomposition Reference Program Based on Matching Pursuit

In this document, we provide MATLAB simulation code for a reference program implementing signal sparse decomposition using Matching Pursuit (MP). This code serves as an educational tool for understanding and practicing MP-based signal sparse decomposition techniques. The MP algorithm is a fundamental signal processing method that efficiently represents signals as linear combinations of sparse basis functions. Through this simulation code, you can learn how to implement MP algorithm for signal processing and achieve optimal sparse representation results.

The reference program includes key implementation components such as: greedy iterative selection of basis functions, residual signal calculation, and coefficient update procedures. The code structure demonstrates the algorithmic workflow where at each iteration, the algorithm selects the basis function that best matches the current signal residual, then updates the coefficients and computes the new residual. This implementation provides a practical framework for studying sparse representation properties and allows for easy modification and extension for further research and development. We hope this code proves valuable for your learning and applications in the field of signal processing!