A data-driven approach to precise linearization of nonlinear dynamical systems in augmented latent space.
H. Harry AsadaFaye Y. WuAlexandre GirardMichaelle N. MayaluPublished in: ACC (2016)
Keyphrases
- nonlinear dynamical systems
- latent space
- dynamical systems
- latent variables
- low dimensional
- matrix factorization
- dimensionality reduction
- parameter space
- feature space
- gaussian process
- generative model
- manifold learning
- lower dimensional
- transfer learning
- gaussian processes
- high dimensional
- phase space
- gaussian process latent variable models
- distance metric
- probabilistic latent semantic analysis
- regression model
- high dimensional data
- prior knowledge
- feature vectors
- high dimensional spaces
- optimal solution