基于自组织地图的房间脉冲响应分类

D. Ristić, M. Pavlović, I. Reljin
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引用次数: 0

摘要

研究了一种利用多重分形和Kohonen神经网络对房间脉冲响应进行分类的方法。脉冲响应是室内声学的基本信息源;因此,它的分析是室内声印象的最重要的问题。本文提出的方法分为三个步骤。信号分类过程的第一步是计算信号的多重分形谱。第二步提取多重分形谱的主要特征。第三步根据提取的特征对相似信号进行分组。对于前一步形成的每一组信号,确定理想的多重分形谱模型。实验结果验证了所述算法的可用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification of room impulse responses with self-organizing maps
In this paper, a method for classifying room impulse responses using multifractals and Kohonen's neural networks is investigated. Impulse response is basic source of information in room acoustics; therefore its analysis is the most important issue regarding sound impression in the room. The method proposed in this paper consists of three steps. The first stage of signal classification process is computation multifractal spectrum of the signal. Main features of multifractal spectrum are extracted in the second step. Grouping of similar signals based on extracted features is done in the third step. For every group of signals formed in previous step, model of desirable multifractal spectrum is determined. The experimental results verify the usability of described algorithm.
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