Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Neural Networks
Temporal Kohonen Map and the Recurrent Self-Organizing Map: Analytical and Experimental Comparison
Neural Processing Letters
Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
Applying LSTM to Time Series Predictable through Time-Window Approaches
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
A Recurrent Self-Organizing Map for Temporal Sequence Processing
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
Recursive self-organizing maps
Neural Networks - New developments in self-organizing maps
A tutorial on support vector regression
Statistics and Computing
Learning Chaotic Attractors by Neural Networks
Neural Computation
Support Vector Machine with Composite Kernels for Time Series Prediction
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Neurocomputing
Language learnability by feedback self-organizing maps
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
A new SOM algorithm for electricity load forecasting
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
IEEE Transactions on Information Theory
Modular state space of echo state network
Neurocomputing
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Local models for regression have been the focus of a great deal of attention in the recent years. They have been proven to be more efficient than global models especially when dealing with chaotic time series. Many models have been proposed to cluster time series and they have been combined with several predictors. This paper presents an extension for recurrent neural networks applied to local models and a discussion about the obtained results.