Topology-Independent GEVD-Based Distributed Adaptive Node-Specific Signal Estimation in Ad-Hoc Wireless Acoustic Sensor Networks

التفاصيل البيبلوغرافية
العنوان: Topology-Independent GEVD-Based Distributed Adaptive Node-Specific Signal Estimation in Ad-Hoc Wireless Acoustic Sensor Networks
المؤلفون: Didier, Paul, van Waterschoot, Toon, Moonen, Marc
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Sound
الوصف: A low-rank approximation-based version of the topology-independent distributed adaptive node-specific signal estimation (TI-DANSE) algorithm is introduced, using a generalized eigenvalue decomposition (GEVD) for application in ad-hoc wireless acoustic sensor networks. This TI-GEVD-DANSE algorithm as well as the original TI-DANSE algorithm exhibit a non-strict convergence, which can lead to numerical instability over time, particularly in scenarios where the estimation of accurate spatial covariance matrices is challenging. An adaptive filter coefficient normalization strategy is proposed to mitigate this issue and enable the stable performance of TI-(GEVD-)DANSE. The method is validated in numerical simulations including dynamic acoustic scenarios, demonstrating the importance of the additional normalization.
Comment: Presented in the 2024 32nd European Signal Processing Conference (EUSIPCO)
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2407.14172
رقم الأكسشن: edsarx.2407.14172
قاعدة البيانات: arXiv