Modal Excitation in Feedback Delay Networks

IF 3.2 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Signal Processing Letters Pub Date : 2024-09-23 DOI:10.1109/LSP.2024.3466790
Sebastian J. Schlecht;Matteo Scerbo;Enzo De Sena;Vesa Välimäki
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Abstract

Feedback delay networks (FDNs) are used in audio processing and synthesis. The modal shapes of the system describe the modal excitation by input and output signals. Previously, the Ehrlich-Aberth method was used to find modes in large FDNs. Here, the method is extended to the corresponding eigenvectors indicating the modal shape. In particular, the computational complexity of the proposed analysis method does not depend on the delay-line lengths and is thus suitable for large FDNs, such as artificial reverberators. We show the relation between the compact generalized eigenvectors in the delay state space and the spatially extended modal shapes in the state space. We illustrate this method with an example FDN in which the suggested modal excitation control does not increase the computational cost. The modal shapes can help optimize input and output gains. This letter teaches how selecting the input and output points along the delay lines of an FDN adjusts the spectral shape of the system output.
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反馈延迟网络中的模态激励
反馈延迟网络(FDN)用于音频处理和合成。系统的模态形状描述了输入和输出信号的模态激励。以前,人们使用 Ehrlich-Aberth 方法来寻找大型 FDN 的模态。在这里,该方法扩展到了表示模态形状的相应特征向量。特别是,所提分析方法的计算复杂度与延迟线长度无关,因此适用于大型 FDN,如人工混响器。我们展示了延迟状态空间中的紧凑广义特征向量与状态空间中的空间扩展模态形状之间的关系。我们用一个 FDN 例子来说明这种方法,其中建议的模态激励控制不会增加计算成本。模态振型有助于优化输入和输出增益。这封信介绍了如何沿着 FDN 的延迟线选择输入和输出点来调整系统输出的频谱形状。
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来源期刊
IEEE Signal Processing Letters
IEEE Signal Processing Letters 工程技术-工程:电子与电气
CiteScore
7.40
自引率
12.80%
发文量
339
审稿时长
2.8 months
期刊介绍: The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing. Papers published in the Letters can be presented within one year of their appearance in signal processing conferences such as ICASSP, GlobalSIP and ICIP, and also in several workshop organized by the Signal Processing Society.
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