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Sparse time-frequency representations

机译:稀疏的时频表示

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摘要

Auditory neurons preserve exquisite temporal information about sound features, but we do not know how the brain uses this information to process the rapidly changing sounds of the natural world. Simple arguments for effective use of temporal information led us to consider the reassignment class of time-frequency representations as a model of auditory processing. Reassigned time frequency representations can track isolated simple signals with accuracy unlimited by the time-frequency uncertainty principle, but lack of a general theory has hampered their application to complex sounds. We describe the reassigned representations for white noise and show that even spectrally dense signals produce sparse reassignments: the representation collapses onto a thin set of lines arranged in a froth-like pattern. Preserving phase information allows reconstruction of the original signal. We define a notion of "consensus," based on stability of reassignment to time-scale changes, which produces sharp spectral estimates for a wide class of complex mixed signals. As the only currently known class of time-frequency representations that is always "in focus" this methodology has general utility in signal analysis. It may also help explain the remarkable acuity of auditory perception. Many details of complex sounds that are virtually undetectable in standard sonograms are readily perceptible and visible in reassignment.
机译:听觉神经元保留有关声音特征的精美时间信息,但是我们不知道大脑如何利用这些信息来处理自然界中迅速变化的声音。有效利用时间信息的简单论点使我们考虑将时频表示的重新分配类别视为听觉处理的模型。重新分配的时频表示形式可以跟踪孤立的简单信号,其准确性不受时频不确定性原理的限制,但是缺乏通用理论限制了它们在复杂声音中的应用。我们描述了白噪声的重新分配表示形式,并表明即使频谱密集的信号也会产生稀疏的重新分配:该表示形式折叠到以泡沫状图案排列的一组细线上。保留相位信息可以重建原始信号。基于重新分配对时标变化的稳定性,我们定义了“共识”的概念,这为各种复杂的混合信号产生了清晰的频谱估计。作为始终“关注”的当前唯一已知的时频表示类,此方法在信号分析中具有一般用途。它也可能有助于解释听觉感知的非凡敏锐度。在标准超声波检查中几乎无法检测到的复杂声音的许多细节在重新分配时很容易察觉并可见。

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