SPSDASSYJul 14, 2020

Allpass Feedback Delay Networks

arXiv:2007.07337v212 citations
AI Analysis

This work provides incremental theoretical extensions for audio signal processing, particularly benefiting researchers and engineers in artificial reverberation and decorrelation.

The authors extended the theory of allpass systems to arbitrary feedback delay networks (FDNs), characterizing uniallpass FDNs and solving the completion problem to determine gain parameters for allpass behavior, which significantly expands the design space for applications like artificial reverberation.

In the 1960s, Schroeder and Logan introduced delay line-based allpass filters, which are still popular due to their computational efficiency and versatile applicability in artificial reverberation, decorrelation, and dispersive system design. In this work, we extend the theory of allpass systems to any arbitrary connection of delay lines, namely feedback delay networks (FDNs). We present a characterization of uniallpass FDNs, i.e., FDNs, which are allpass for an arbitrary choice of delays. Further, we develop a solution to the completion problem, i.e., given an FDN feedback matrix to determine the remaining gain parameters such that the FDN is allpass. Particularly useful for the completion problem are feedback matrices, which yield a homogeneous decay of all system modes. Finally, we apply the uniallpass characterization to previous FDN designs, namely, Schroeder's series allpass and Gardner's nested allpass for single-input, single-output systems, and, Poletti's unitary reverberator for multi-input, multi-output systems and demonstrate the significant extension of the design space.

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