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中文核心期刊

基于空间特征抽取与神经网络的人耳空间听觉模型

A spatial hearing model based on spatial feature extraction and artificial neural network

  • 摘要: 空间听觉中复数值的与头相关联的传递函数(HRTF)可用实数值的与头相关联的冲激响应(HRIR表示。对测量空间上归一化的HRIR进行Karhunen-Loeve展开可以提取其空间特征.用Von—Mises函数为基函数的神经网络逼近离散的HRIR空间特征函数得到连续听觉空间上的双耳时域模型.模型与实际测量得到的HRIR有较好的一致性。

     

    Abstract: In spatial hearing, a complex valued head--related transfer function (HRTF) can be represented as a real valued head--related impulse response (HRIR). Using Karhunen-Loeve expansion, the spatial features of the normalized HRIRs on measurement space can be extracted as spatial characteristic functions. A neural network model based on Von-Mises function is used to approximate the discrete spatial characteristic function of HRIR. As a result, a time domain binaural model is established which well fits the measured HRIRs.

     

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