Corpus ID: 233169171

Efficient state and parameter estimation for high-dimensional nonlinear system identification with application to MEG brain network modeling

@article{Singh2021EfficientSA,
  title={Efficient state and parameter estimation for high-dimensional nonlinear system identification with application to MEG brain network modeling},
  author={Matthew F. Singh and Chong Wang and Michael W. Cole and S. Ching},
  journal={ArXiv},
  year={2021},
  volume={abs/2104.02827}
}
  • Matthew F. Singh, Chong Wang, +1 author S. Ching
  • Published 2021
  • Computer Science, Engineering, Biology, Mathematics
  • ArXiv
System identification poses a significant bottleneck to characterizing and controlling complex systems. This challenge is greatest when both the system states and parameters are not directly accessible leading to a dual-estimation problem. Current approaches to such problems are limited in their ability to scale with many-parameter systems as often occurs in networks. In the current work, we present a new, computationally efficient approach to treat large dual-estimation problems. Our approach… Expand

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