IEEE Transactions On Neural Networks And Learning Systems : Vol. 25, No. 1, January 2014

1. Compose: A Semisupervised learning framework for initially labeled nonstationary streaming data.
2. Active learning with drifting streaming data.
3. Online bayesian learning with natural sequential prior distribution.
4. PANFIS: A Novel incremental learning machine.
5. PCA Feature extraction for change detection in multidimensional unlabeled data.
6. Reacting to different types of concept drift: the accuracy updated ensemble algorithm.
7. Mining recurring concepts in a dynamic features space.
8. Dynamic learning from adaptive neural network control of a class of nonaffine nonlinear systems.
9. Learning in the model space for cognitive fault diagnosis.
10. Adaptive approximation for multiple sensor fault detection and isolation of nonlinier uncertain systems.
11. Dealing with concept drifts in process mining.
12. Adaptive convex combination approach for the identification of improoer quaternion processes.
13. Developmental perception of the self and action.
14. Lingustic decision making for robot route learning.
15. An Internal type-2 neural fuzzy chip with on-chip incremental learning ability for time-varying data sequence prediction and system control.
16. Learning geotemporal nonstationary failure and recovery of power distribution.

Etc.