The 'Neural' Phonetic Typewriter
Computer
Topology-conserving maps for learning visuo-motor-coordination
Neural Networks
Neural computation and self-organizing maps: an introduction
Neural computation and self-organizing maps: an introduction
Neural Networks
Interpreting the Kohonen self-organizing feature map using contiguity-constrained clustering
Pattern Recognition Letters
Visual Explorations in Finance
Visual Explorations in Finance
Neural and Adaptive Systems: Fundamentals through Simulations with CD-ROM
Neural and Adaptive Systems: Fundamentals through Simulations with CD-ROM
Self-Organizing Maps
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3 - Volume 3
A Hierarchical Neural Model in Short-Term Load Forecasting
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
Process Monitoring and Modeling Using the Self-Organizing Map
Integrated Computer-Aided Engineering
A method for automated temporal knowledge acquisition applied to sleep-related breathing disorders
Artificial Intelligence in Medicine
Topology constraint free fuzzy gated neural networks for pattern recognition
IEEE Transactions on Neural Networks
Self-organization of spiking neurons using action potential timing
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Clustering of the self-organizing map
IEEE Transactions on Neural Networks
Spatio-temporal feature maps using gated neuronal architecture
IEEE Transactions on Neural Networks
EnvSOM: a SOM algorithm conditioned on the environment for clustering and visualization
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
A Framework For State Transitions On The Self-Organizing Map: Some Temporal Financial Applications
International Journal of Intelligent Systems in Accounting and Finance Management
Hi-index | 0.00 |
This paper presents a taxonomy for Self-organizing Maps (SOMs) for temporal sequence processing. Four main application areas for SOMs with temporal processing have been identified. These are prediction, control, monitoring and data mining. Three main techniques have been used to model temporal relations in SOMs: 1) pre-processing or post-processing the data, but keeping the basic SOM algorithm; 2) modifying the activation and/or learning algorithm to take those temporal dependencies into account; 3) modifying the network topology, either by introducing feedback elements, or by using hierarchical SOMs. Each of these techniques is explained and discussed, and a more detailed taxonomy is proposed. Finally, a list of some of the existing and relevant papers in this area is presented, and the distinct approaches of SOMs for temporal sequence processing are classified into the proposed taxonomy. In order to handle complex domains, several of the adaptation forms are often combined.