Multi-level Binarized LSTM in EEG Classification for Wearable Devices

Nazari, N.University of Tehran, School of Electrical and Computer Engineering, Tehran, Iran (author)

Long Short-Term Memory (LSTM) is widely used in various sequential applications. Complex LSTMs could be hardly deployed on wearable and resourced-limited devices due to the huge amount of computations and memory requirements. Binary LSTMs are introduced to cope with this problem, however, they lead to significant accuracy loss in some applications such as EEG classification which is essential to be deployed in wearable devices. In this paper, we propose an efficient multi-level binarized LSTM which has significantly reduced computations whereas ensuring an accuracy pretty close to full precision LSTM. By deploying 5-level binarized weights and inputs, our method reduces area and delay of MAC operation about 31× and 27× in 65nm technology, respectively with less than 0.01% accuracy loss. In contrast to many compute-intensive deep-learning approaches, the proposed algorithm is lightweight, and therefore, brings performance efficiency with accurate LSTM-based EEG classification to realtime wearable devices.

Sinaei, SimaUniversity of Tehran, School of Electrical and Computer Engineering, Tehran, Iran,Malardalen University, Division of Intelligent Future Technologies, Vasteras, Sweden(Swepub:mdh)o.i (author)
Sinaei, SimaMalardalen University, Division of Intelligent Future Technologies, Vasteras, Sweden(Swepub:mdh)o.i (author)
Salehi, M. E.University of Tehran, School of Electrical and Computer Engineering, Tehran, Iran (author)
Daneshtalab, MasoudMälardalens högskola,Inbyggda system,Mälardalen University, Sweden(Swepub:mdh)mdb01 (author)
University of Tehran, School of Electrical and Computer Engineering, Tehran, IranMalardalen University, Division of Intelligent Future Technologies, Vasteras, Sweden (creator_code:org_t)

In:Proceedings - 2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2020: Institute of Electrical and Electronics Engineers Inc., s. 175-1819781728165820

By the author/editor: Nazari, N.; Sinaei, Sima; Salehi, M. E.; Daneshtalab, Mas ...

About the subject

NATURAL SCIENCES: NATURAL SCIENCES; and Computer and Inf ...; and Computer Enginee ...

NATURAL SCIENCES: NATURAL SCIENCES; and Computer and Inf ...; and Computer Science ...

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