Robust Photoplethysmography Signal Denoising via Mamba Networks

arXiv:2510.11058 · cs.LG, eess.SP · Submitted 2025-10-13 · Read on arXiv

cs.LG, eess.SP

Submitted: 2025-10-13

Updated: 2026-09-22

Comments: Published in EMBC 2026

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Fidelity — 10× in this paper · explained in 2 episodes
• Transformer — 9× in this paper · explained in 2 episodes
• Consistency — 6× in this paper · explained in 3 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Robustness — 3× in this paper · explained in 5 episodes
• Wavelet Transform — 3× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Fast Wavelet Transform — 2× in this paper
• Loss Function — 2× in this paper · explained in 2 episodes
• Reconstruction Error — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Computes the Mean Absolute Error — 1× in this paper
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Mean Squared Error — 1× in this paper
• Objective Function — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• Jamba: A Hybrid Transformer-Mamba Language Model
• SPMamba: State-space model is all you need in speech separation
• Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks