Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Rescaling of variables in back propagation learning
Neural Networks
Adaptive filter theory (2nd ed.)
Adaptive filter theory (2nd ed.)
A New Weight Initialization Method for the MLP with the BP inMulticlass Classification Problems
Neural Processing Letters
Extended Kalman filter-based pruning method for recurrent neural networks
Neural Computation
Incremental Gradient Algorithms with Stepsizes Bounded Away from Zero
Computational Optimization and Applications
Dynamic Learning with the EM Algorithm for Neural Networks
Journal of VLSI Signal Processing Systems
Training fuzzy systems with the extended Kalman filter
Fuzzy Sets and Systems - Fuzzy systems
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Self-organised evolutionary neural networks: algorithms and applications
Highly parallel computaions
Dual extended Kalman filtering in recurrent neural networks
Neural Networks
Sequential Monte Carlo Methods to Train Neural Network Models
Neural Computation
Hierarchical Bayesian Models for Regularization in Sequential Learning
Neural Computation
Stock Index Prediction Based on Adaptive Training and Pruning Algorithm
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
The Local True Weight Decay Recursive Least Square Algorithm
Neural Information Processing
Nonlinear Bayesian Filters for Training Recurrent Neural Networks
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
An Adaptive Recursive Least Square Algorithm for Feed Forward Neural Network and Its Application
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
An adaptive speed controller for induction motor drives using adaptive neuro-fuzzy inference system
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Memory-efficient fully coupled filtering approach for observational model building
IEEE Transactions on Neural Networks
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
A Neuro-Fuzzy Identification of ECG Beats
Journal of Medical Systems
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The training of feedforward networks using the conventional back propagation algorithm is plagued by slow convergence and misadjustment. In this paper, we apply optimal filtering techniques to train feedforward networks in the standard supervised learning framework. We consider first the global problem of computing the synaptic weights all simultaneously, and then develop the idea of local linearization and partitioning. We present three algorithms which are computationally more expensive than standard back propagation, but local at the neuron level. These algorithms do not incorporate any tunable parameters and show excellent performance in comparison to the expensive approach of the global Extended Kalman Algorithm in terms of speed of convergence and quality of solution obtained on three benchmark problems.