Category: Code & Resources

Temporal Sparse Wavenumber Analysis Repository

Temporal Sparse Wavenumber Analysis (TSWA) is a novel technique that reconstructs high-resolution spatiotemporal wavefields using fewer temporal samples than traditional methods typically require. Developed by Soroosh Sabeti and Dr. Joel B. Harley, TSWA makes it possible to retrieve accurate guided wave information from temporally undersampled data, which is crucial in applications where high-speed sensing, data storage, or power consumption are limiting factors.

June 3, 2025 0
Data-driven matched field processing

Data-Driven Matched Field Processing (DDMFP) Repository

Data-Driven Matched Field Processing (DDMFP) is an innovative signal processing framework designed for localizing acoustic sources in complex environments, such as those encountered in structural health monitoring (SHM) using Lamb waves. Traditional matched field processing (MFP) techniques rely heavily on accurate physical models of the propagation medium, which can be challenging to obtain in real-world scenarios. DDMFP circumvents this limitation by constructing localization models directly from measured data, enhancing robustness and accuracy in complex, multimodal propagation environments.

May 17, 2025 0

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:

May 16, 2025 0

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