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February 23, 2026Open Access

Real-Time Signal Processing for Distributed Acoustic Sensing and Acoustic Sensing Systems Under Non-Stationary Noise

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Authors

SMSamuel Yaw MensahTZTao ZhangXZXin Zhao

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Overview

Unified Bayesian-Kalman estimator shows up to +9.8 dB SNR improvement in speech enhancement under non-stationary noise.

Key Points

  • This research aims to enhance real-time acoustic signals in non-stationary noise using a unified Bayesian-Kalman estimator.
  • Developed a unified Bayesian-Kalman estimator that fuses spectral and temporal information.
  • Analyzed bias-variance behavior and stability conditions of the estimator.
  • Conducted experiments on standard speech corpora to validate performance.
  • Achieved up to +9.8 dB SNR improvement over baseline MMSE estimator.
  • Demonstrated approximately +17% improvement in PESQ scores.
  • Confirmed empirical performance closely aligns with theoretical predictions.

Cite This Study

Mensah et al. (2026) studied this question.

synapsesocial.com/papers/699ba08472792ae9fd8702f5https://doi.org/10.3390/s26041372
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