Outlier-resistant variance-constrained $\mathit{H}_{\infty }$ state estimation for time-varying recurrent neural networks with randomly occurring deception attacks.
Yan GaoJun HuHui YuJunhua DuChaoqing JiaPublished in: Neural Comput. Appl. (2023)
Keyphrases
- recurrent neural networks
- state estimation
- kalman filter
- dynamic systems
- neural network
- particle filter
- kalman filtering
- feed forward
- state space model
- reservoir computing
- recurrent networks
- visual tracking
- echo state networks
- nonlinear dynamic systems
- particle filtering
- neural model
- artificial neural networks
- fuzzy logic
- search space
- cascade correlation
- search algorithm