Your selections:
Constrained subspace method for the identification of structured state-space models (COSMOS)
- Yu, Chengpu, Ljung, Lennart, Wills, Adrian, Verhaegen, Michel
Affinely parametrized state-space models: ways to maximize the likelihood function
- Wills, Adrian, Yu, Chengpu, Ljung, Lennart, Verhaegen, Michel
Identification of stochastic wiener systems using indirect inference
- Wahlberg, Bo, Welsh, James, Ljung, Lennart
Identification of Wiener systems with process noise is a nonlinear errors-in-variables problem
- Wahlberg, Bo, Welsh, James, Ljung, Lennart
Model Error Modeling and Stochastic Embedding
- Ljung, Lennart, Goodwin, Graham C., Agüero, Juan C., Chen, Tianshi
Stochastic embedding revisited: a modern interpretation
- Ljung, Lennart, Goodwin, Graham C., Aguero, Juan C.
Identification of Hammerstein-Wiener models
- Wills, Adrian, Schön, Thomas B., Ljung, Lennart, Ninness, Brett
A general convergence result for particle filtering
- Hu, Xiao-Li, Schon, Thomas B., Ljung, Lennart
Issues in sampling and estimating continuous-time models with stochastic disturbances
- Ljung, Lennart, Wills, Adrian
Wiener system identification using the maximum likelihood method
- Wills, Adrian, Ljung, Lennart
Maximum likelihood identification of Wiener models
- Hagenblad, Anna, Ljung, Lennart, Wills, Adrian
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