Using the Jensen-Shannon, Density Power, and Itakura-Saito Divergences to Implement an Evolutionary-Based Global Localization Filter for Mobile Robots.
Fernando Martín MonarJuan CarballeiraLuis MorenoSantiago GarridoPavel Gonzalez PrietoPublished in: IEEE Access (2017)
Keyphrases
- bregman divergences
- mobile robot
- information theoretic
- jensen shannon
- jensen shannon divergence
- relative entropy
- kullback leibler
- maximum entropy
- kl divergence
- mahalanobis distance
- loss function
- cost sensitive
- nearest neighbor
- kullback leibler divergence
- exponential family
- median filter
- mutual information
- cross entropy
- bayesian networks
- maximum likelihood
- theoretical guarantees
- information theory
- noise reduction