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pyFDN: A Python Toolbox for Feedback Delay Network Design, Analysis, and Optimization
arXiv eess.AS0 views
arXiv:2610.27217v1 Announce Type: new Abstract: Feedback delay networks (FDNs) provide a compact representation of recursive audio systems for artificial reverberation and decorrelation. Their practical use spans structured matrix design, acoustic decay shaping, numerical simulation, and modal analysis, increasingly combined with differentiable optimization. We present pyFDN, an open-source Python toolbox that brings these operations into a common workflow. The library combines numerical design and analysis routines with block-based time-domain processing and integration with FLAMO for frequency-domain differentiable processing. Explicit network builds and JSON presets connect design, optimization, rendering, and reuse. This paper describes the software architecture, representative capabilities, and reproducibility mechanisms of version 0.5.0, providing a reference for research and teaching that use the toolbox.
Source:https://arxiv.org/abs/2610.27217PreviousBeam-Domain Channel Estimation for mmWave MIMO using Sub-6 GHz Out-of-Band InformationNextRealComm: Benchmarking and Adapting Audio Deepfake Detection over Real Communication Channels
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