Dynamic tunneling based regularization in feedforward neural networks
Artificial Intelligence
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Interactive Pattern Recognition
Interactive Pattern Recognition
Hybridization of gradient descent algorithms with dynamic tunnelingmethods for global optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
On neurobiological, neuro-fuzzy, machine learning, and statistical pattern recognition techniques
IEEE Transactions on Neural Networks
Dynamic tunneling technique for efficient training of multilayer perceptrons
IEEE Transactions on Neural Networks
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This paper presents the generalization capability of multilayer perceptrons (MLP). The learning algorithm is based on mixing the concepts of dynamic tunneling along with error backpropagation (EBPDT), which enables detrapping of the local minimum point. In this study, the generalization capability is presented on three standard datasets, and the k-fold cross validation results is presented for two of the datasets. A comparative study of the performance of the proposed method with EBP clearly demonstrates the power of tunneling applied in conjunction with EBP type of learning.