Thalgorithm Research, Toronto, Ontario, L4X 1B1, Canada.
J Acoust Soc Am. 2012 Nov;132(5):3251-62. doi: 10.1121/1.4754550.
Room-acoustic energy decays often exhibit single-rate or multiple-rate characteristics in a wide variety of rooms/halls. Both the energy decay order and decay parameter estimation are of practical significance in architectural acoustics applications, representing two different levels of Bayesian probabilistic inference. This paper discusses a model-based sound energy decay analysis within a Bayesian framework utilizing the nested sampling algorithm. The nested sampling algorithm is specifically developed to evaluate the Bayesian evidence required for determining the energy decay order with decay parameter estimates as a secondary result. Taking the energy decay analysis in architectural acoustics as an example, this paper demonstrates that two different levels of inference, decay model-selection and decay parameter estimation, can be cohesively accomplished by the nested sampling algorithm.
在各种房间/大厅中，室内声能衰减通常表现出单速率或多速率特征。能量衰减顺序和衰减参数估计在建筑声学应用中都具有实际意义，代表了两种不同层次的贝叶斯概率推断。本文在贝叶斯框架内利用嵌套采样算法讨论了基于模型的声能衰减分析。嵌套采样算法是专门为评估确定能量衰减顺序所需的贝叶斯证据而开发的，其将衰减参数估计作为次要结果。以建筑声学中的能量衰减分析为例，本文证明嵌套采样算法可以将两个不同层次的推断，即衰减模型选择和衰减参数估计，紧密地结合起来。
