Hosted on MSN

Master signal processing with Python tools

Signal processing in Python is more approachable than ever with libraries like NumPy and SciPy. These tools make it easy to filter noise, analyze frequencies, and transform raw signals into meaningful ...

Quantum simulations that bypass resolution limits offer insights into high-temperature superconductivity

A new method developed at LMU overcomes fundamental resolution limits and may provide insights into high-temperature ...
IEEE

Spectral–Spatial Out-of-Distribution-Based Unsupervised Band Selection Method for Hyperspectral Anomaly Detection

Abstract: Hyperspectral anomaly detection (HAD) aims to highlight the pixels that are different from the surrounding pixels without any prior information. However, as a hyperspectral image (HSI) tends ...
GitHub

Musica — Structure-First Audio Source Separation

Dynamic mincut graph partitioning for real-time audio source separation. Zero-dependency, sub-millisecond, fully interpretable audio separation via graph Laplacian spectral clustering and dynamic ...
GitHub

Research: Rotation-invariant alternatives to pairwise_corr for Rust-vs-Python spectral init comparison

The 100K MERFISH benchmark (PR #216) showed that pairwise_corr_vs_python fails at 100K (0.987, below the 0.99 threshold) despite all other quality gates passing. The metric computes correlation ...
IEEE

A Spectral Change Enhancement Method Based on Self-Supervised Learning Framework

Abstract: Modern hearing aids often fail to benefit the wearer in noisy environments. In fact, the auditory processing of hearing impaired listeners usually leads to spectral smearing, and hearing ...