
Sparse Wavenumber Analysis (SWA) Repository
Sparse Wavenumber Analysis (SWA) is a signal processing algorithm designed to extract high-resolution wavenumber information from spatial wavefield measurements—especially when that data is sparse, noisy, or irregularly sampled. Developed by Dr. Joel B. Harley and collaborators, SWA enables researchers and engineers to analyze wave propagation with unprecedented clarity, even in situations where traditional Fourier-based methods fall short.
This CodeOcean capsule contains a complete, reproducible implementation of the SWA algorithm, based on the foundational work in:
This CodeOcean capsule contains a complete, reproducible implementation of the SWA algorithm, based on the foundational work in: