Split Learning Meets Koopman Theory for Wireless Remote Monitoring and Prediction

B. O. Koopman, “Hamiltonian systems and transformation in hilbert space,” Proceedings of the national academy of sciences of the united states of america , vol. 17, no. 5, p. 315, 1931

1931

Earlier work this paper cites.

G. D. Birkhoff and B. O. Koopman, “Recent contributions to the ergodic theory,” Proceedings of the National Academy of Sciences of the United States of America , vol. 18, no. 3, p. 279, 1932

1932

Earlier work this paper cites.

T. S. Schei, “A finite-difference method for linearization in nonlinear estimation algorithms,” Automatica , vol. 33, no. 11, pp. 2053–2058, 1997

1997

Earlier work this paper cites.

C. Meng, T. Wang, W. Chou, S. Luan, Y. Zhang, and Z. Tian, “Remote surgery case: robot-assisted teleneurosurgery,” in IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA’04. 2004 , vol. 1. IEEE, 2004, pp. 819–823

2004

Earlier work this paper cites.

L. Liu, R. Sun, Y. Sun, and S. Al-Sarawi, “A smart bushfire monitoring and detection system using GSM technology,” International Journal of Computer Aided Engineering and Technology , vol. 2, no. 2-3, pp. 218–233, 2010

2010

Earlier work this paper cites.

M. Hassanin, O. Fresnedo, J. Garcia-Frias, and L. Castedo, “Analog joint source channel coding for gaussian multiple access channels,” in International Workshop on Multiple Access Communications . Springer, 2013, pp. 21–32

2013

Earlier work this paper cites.

I. Sutskever, J. Martens, G. Dahl, and G. Hinton, “On the importance of initialization and momentum in deep learning,” in International conference on machine learning . PMLR, 2013, pp. 1139–1147

Original

2013

Earlier work this paper cites.

F. J. Vazquez-Araujo, O. Fresnedo, L. Castedo, and J. Garcia-Frias, “Analog joint source-channel coding over MIMO channels,” EURASIP Journal on Wireless Communications and Networking , vol. 2014, no. 1, pp. 1–10, 2014

2014

Earlier work this paper cites.

S. L. Brunton, B. W. Brunton, J. L. Proctor, and J. N. Kutz, “Koopman invariant subspaces and finite linear representations of nonlinear dynamical systems for control,” PloS one , vol. 11, no. 2, p. e0150171, 2016

2016

Cited alongside, same era.

I. Mezic, “Koopman operator spectrum and data analysis,” arXiv preprint arXiv:1702.07597 , 2017

Original

2017

Cited alongside, same era.

M. Bennis, M. Debbah, and H. V. Poor, “Ultrareliable and low-latency wireless communication: Tail, risk, and scale,” Proceedings of the IEEE , vol. 106, no. 10, pp. 1834–1853, 2018

2018

Cited alongside, same era.

B. Lusch, J. N. Kutz, and S. L. Brunton, “Deep learning for universal linear embeddings of nonlinear dynamics,” Nature communications , vol. 9, no. 1, pp. 1–10, 2018

2018

Cited alongside, same era.

J. Park, S. Samarakoon, M. Bennis, and M. Debbah, “Wireless network intelligence at the edge,” Proceedings of the IEEE , vol. 107, no. 11, pp. 2204–2239, 2019

2019

Later among the works it cites.

P. Morasso, T. Nomura, Y. Suzuki, and J. Zenzeri, “Stabilization of a cart inverted pendulum: improving the intermittent feedback strategy to match the limits of human performance,” Frontiers in computational neuroscience , vol. 13, p. 16, 2019

2019

Later among the works it cites.

M. Eisen, M. M. Rashid, K. Gatsis, D. Cavalcanti, N. Himayat, and A. Ribeiro, “Control aware communication design for time sensitive wireless systems,” in ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2019, pp. 4584–4588

2019

Later among the works it cites.

E. Yeung, S. Kundu, and N. Hodas, “Learning deep neural network representations for Koopman operators of nonlinear dynamical systems,” in 2019 American Control Conference (ACC) . IEEE, 2019, pp. 4832–4839

2019