Learning of sparse auditory receptive fields

Konrad Paul Kording, Peter König, David Klein
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引用次数: 24

Abstract

It is largely unknown how the properties of the auditory system relate to the properties of natural sounds. Here, we analyze representations of simulated neurons that have optimally sparse activity in response to spectro-temporal speech data. These representations share important properties with the auditory neurons determined in electrophysiological experiments.
稀疏听觉接受域的学习
听觉系统的特性与自然声音的特性之间的关系在很大程度上是未知的。在这里,我们分析了具有最佳稀疏活动的模拟神经元的表示,以响应光谱-时间语音数据。这些表征与电生理实验中确定的听觉神经元具有重要的特性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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