IEEE

Polynomial Phase Signal Denoising via Sparse Representations Over a SMAF-Based Dictionary Learning Algorithm

Abstract: In this paper, we address the problem of denoising polynomial phase signals (PPS) by removing additive white Gaussian noise. Our approach is based on sparse representation using a trained ...
GitHub

Sparse Autoencoders Learn Monosemantic Features in Vision-Language Models

Sparse Autoencoders (SAEs) have recently gained attention as a means to improve the interpretability and steerability of Large Language Models (LLMs), both of which are essential for AI safety. In ...
IEEE

Joint Sparse Dictionary Learning Method for Multi-mode Parameters of Distribution Transformer PD Signals

Abstract: Partial discharge (PD) can characterize and affect the insulation performance of distribution transformers. However, PD signals have the problem of a single-mode sparse dictionary with a ...