Mapping the filtered MFCC to loudness the process of human perception is simulated.

将滤波后的参数映射为响度，由此模拟人的感知过程。

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In this paper, four neural networks, i. e. multi layer perception, radial basis function, learning vector quantization and self organizing feature mapping, are used to segment the flame image.

本文研究了多层感知器、径向基函数网络、学习向量量化网络和自组织特征映射网络等四种神经网络在回转窑火焰图像分割中的应用。

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This paper analyzes the visual graphic elements, and then set up the mapping between visual variables and data attributes and created the user perception model based on visual elements.

本文分析了可视化图形因素，建立了可视化变量与数据属性之间的映射关系，并提出基于可视化因素的用户感知模型。

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