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REFERENCES

1 
Sakamoto T., Imasaka R., Taki H., Sato T., Yoshioka M., Inoue K., Fukuda T., Sakai H., 2015, Accurate heartbeat monitoring using ultra-wideband radar, IEICE Electronics Express, Vol. 12, No. 3, pp. 20141197DOI
2 
Droitcour A. D., Boric-Lubecke O., Lubecke V. M., Lin J., Kovacs G. T. A., 2004, Range correlation and I/Q performance benefits in single-chip silicon doppler radars for noncontact cardiopulmonary monitoring, IEEE Transactions on Microwave Theory and Techniques, Vol. 52, No. 3, pp. 838-848DOI
3 
Droitcour A. D., Jan. 2006., Non-contact measurement of heart and respiration rates with single chip microwave doppler radarURL
4 
Jafferson A.-J., Ponnusamy V., Jovic J., Trajanovic M., June 2021, An IoT based cloud EEG signal analytic framework for thought to text mapping, IEIE Transactions on Smart Processing & Computing, Vol. 10, No. 3, pp. 183-188DOI
5 
Lee K., Kim Y., Oct. 2019, Hardware implementation of the simplified digital spiking neural network on FPGA, IEIE Transactions on Smart Processing & Computing, Vol. 8, No. 5, pp. 405-414DOI
6 
Nguyen X.-T., Nguyen T.-N., Lee H.-J., Kim H., Dec. 2020, An accurate weight binarization scheme for CNN object detectors with two scaling factors, IEIE Transactions on Smart Processing & Computing, Vol. 9, No. 6, pp. 497-503DOI
7 
Lee H.-B., Kim G., Kim J.-H., Kang Y.-S., Park C., June 2021, Optimal design of convolutional neural network for EEG-based authentication, IEIE Transactions on Smart Processing & Computing, Vol. 10, No. 3, pp. 199-203DOI
8 
Jhong S.-Y., Tseng P.-Y., Siriphockpirom N., Hsia C.-H., Huang M.-S., Hua K.-L., Chen Y.-Y., 2020, An automated biometric identification system using CNN-based palm vein recognition, in 2020 International Conference on Advanced Robotics and Intelligent Systems (ARIS), pp. 1-6DOI
9 
Lynn H. M., Pan S. B., Kim P., Oct. 2019, A deep bidirectional GRU network model for biometric electrocardiogram classification based on recurrent neural networks, IEEE Access, Vol. 7, pp. 145395-145405DOI
10 
Singh S., Pandey S.K., Pawar U., Janghel R.R., 2018, Classification of ECG arrhythmia using recurrent neural networks, Procedia Computer Science, Vol. 132, pp. 1290-1297DOI
11 
Salloum R., Kuo C.-C. J., 2017, ECG-based biometrics using recurrent neural networks, in 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2062-2066DOI
12 
Hochreiter S., Schmidhuber J., Dec. 1997, Long short-term memory, Neural Computation, Vol. 9, pp. 1735-1780DOI
13 
Saadatnejad S., Oveisi M., Hashemi M., 2020, LSTM-based ECG classification for continuous monitoring on personal wearable devices, IEEE Journal of Biomedical and Health Informatics, Vol. 24, No. 2, pp. 515-523DOI
14 
Han S., Lee W., Eom H., Kim J., Park C., Aug. 2020, Detection of arrhythmia using 1D convolution neural network with LSTM model, IEIE Transactions on Smart Processing & Computing, Vol. 9, No. 4, pp. 261-265DOI
15 
Yang C., Jiang W., Guo Z., Nov. 2019, Time series data classification based on dual path CNN-RNN cascade network, IEEE Access, Vol. 7, pp. 155304-155312DOI
16 
Guan Y., Yuan Z., Sun G., Cong J., 2017, FPGA-based accelerator for long short-term memory recurrent neural networks, in 2017 22nd Asia and South Pacific Design Automation Conference (ASP-DAC), Vol. , No. , pp. 629-634DOI
17 
Chang A. X. M., Martini B., Culurciello E., Nov. 2015, Recurrent neural networks hardware implementation on FPGA, arXiv e-prints, arXiv:1511.05552URL
18 
Yoshimura U., Inoue T., Tsuchiya A., Kishine K., Jan. 2021, Implementation of low-energy LSTM with parallel and pipelined algorithm in small-scale FPGA, in 2021 International Conference on Electronics, Information, and Communication (ICEIC 2021), Jeju, South Korea, pp. 114-117.DOI
19 
Chollet F., 2015, KerasURL
20 
Hao Y., Quigley S., Oct. 2017, The implementation of a deep recurrent neural network language model on a Xilinx FPGA, arXiv e-prints, arXiv:1710.10296URL