STFNets: Learning Sensing Signals from the Time-Frequency Perspective with Short-Time Fourier Neural NetworksEI

摘要

Recent advances in deep learning motivate the use of deep neural networks in Internet-of-Things (IoT) applications. These networks are modelled after signal processing in the human brain, thereby leading to significant advantages at perceptual tasks such as vision and speech recognition. IoT applications, however, often measure physical phenomena, where the underlying physics (such as inertia, wireless signal propagation, or the natural frequency of oscillation) are fundamentally a function of signal frequencies, offering better featu...更多
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pp. 2192-2202, 2019.

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