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Recurrent Neural Network-Assisted Adaptive Sampling for Approximate Computing

Publication ,  Conference
Feng, Y; Zhou, Y; Tarokh, V
Published in: Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019
December 1, 2019

We propose an adaptive signal sampling approach that dynamically adjusts the sampling rate to approximate the local Nyquist rate of the signal. The proposed adaptive sampling approach consists of a recurrent neural network-based change detector that detects the point of frequency change and a local Nyquist rate estimator based on a multi-rate signal processing scheme. We empirically demonstrate that our adaptive sampling approach significantly reduces the overall sampling rate for various types of signals and therefore improves the computational efficiency of subsequent signal processing.

Duke Scholars

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Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

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Publication Date

December 1, 2019

Start / End Page

2240 / 2246
 

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Feng, Y., Zhou, Y., & Tarokh, V. (2019). Recurrent Neural Network-Assisted Adaptive Sampling for Approximate Computing. In Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 (pp. 2240–2246). https://doi.org/10.1109/BigData47090.2019.9006504
Feng, Y., Y. Zhou, and V. Tarokh. “Recurrent Neural Network-Assisted Adaptive Sampling for Approximate Computing.” In Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019, 2240–46, 2019. https://doi.org/10.1109/BigData47090.2019.9006504.
Feng Y, Zhou Y, Tarokh V. Recurrent Neural Network-Assisted Adaptive Sampling for Approximate Computing. In: Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. 2019. p. 2240–6.
Feng, Y., et al. “Recurrent Neural Network-Assisted Adaptive Sampling for Approximate Computing.” Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019, 2019, pp. 2240–46. Scopus, doi:10.1109/BigData47090.2019.9006504.
Feng Y, Zhou Y, Tarokh V. Recurrent Neural Network-Assisted Adaptive Sampling for Approximate Computing. Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. 2019. p. 2240–2246.

Published In

Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

DOI

Publication Date

December 1, 2019

Start / End Page

2240 / 2246