Description

This tutorial is a part of IEEE Education Week Sri Lanka which was held at TRACE Expert City on the 24 th & 25 th of April 2024. Abstract: This tutorial discusses techniques and methodologies aimed at analyzing and processing signals that exhibit sparsity. This tutorial focuses into mathematical foundations such as compressed sensing theory and sparse representation models like wavelets/dictionary learning. It addresses signal reconstruction challenges, exploring algorithms like l1-norm minimization (e.g., Lasso or Basis Pursuit) for sparse signal recovery. Further, it discusses applications of sparse signal processing such as image processing, communication, data compression, denoising, feature extraction, and signal reconstruction tasks.