Approximation of Markov Processes by Lower Dimensional Processes via Total Variation Metrics.
Ioannis TzortzisCharalambos D. CharalambousThemistoklis CharalambousChristoforos N. HadjicostisMikael JohanssonPublished in: IEEE Trans. Autom. Control. (2017)
Keyphrases
- total variation
- markov processes
- lower dimensional
- stochastic processes
- image restoration
- denoising
- image denoising
- dimensionality reduction
- markov chain
- higher dimensional
- high dimensional
- low dimensional
- principal component analysis
- original data
- image processing
- random fields
- high dimensional data
- random projections
- non stationary
- feature space
- probability distribution
- natural images
- feature extraction
- random variables
- super resolution
- input image
- object recognition
- data sets