Alternating Transfer Functions to Prevent Overfitting in Non-Linear Regression with Neural Networks

The Universal Approximation Property

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Using perceptron feed-forward Artificial Neural Network (ANN) for predicting the thermal conductivity of graphene oxide-Al2O3/water-ethylene glycol hybrid nanofluid

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A feedforward neural network for direction-of-arrival estimation

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Transformed ℓ1 regularization for learning sparse deep neural networks

(2019) Rongrong Ma et al.   NEURAL NETWORKS

On Training Efficiency and Computational Costs of a Feed Forward Neural Network: A Review

(2015) Antonino Laudani et al.   Computational Intelligence and Neuroscience

Selection of Proper Neural Network Sizes and Architectures—A Comparative Study

(2012) David Hunter et al.   IEEE Transactions on Industrial Informatics

Computing Gradient Vector and Jacobian Matrix in Arbitrarily Connected Neural Networks

(2008) B.M. Wilamowski et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Optimized Approximation Algorithm in Neural Networks Without Overfitting

(2008) Yinyin Liu et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS