Pattern Recognition Letters
Pruning using parameter and neuronal metrics
Neural Computation
MLP in layer-wise form with applications to weight decay
Neural Computation
Simultaneous optimization of neural network function and architecture algorithm
Decision Support Systems
A neural network pruning approach based on compressive sampling
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
A Novel Pruning Algorithm for Optimizing Feedforward Neural Network of Classification Problems
Neural Processing Letters
Hybrid validation of handwriting process modelling
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
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An algorithm for constructing and training multilayer neural networks, dependence identification, is presented in this paper. Its distinctive features are that (i) it transforms the training problem into a set of quadratic optimization problems that are solved by a number of linear equations, (ii) it constructs an appropriate network to meet the training specifications, and (iii) the resulting network architecture and weights can be further refined with standard training algorithms, like backpropagation, giving a significant speedup in the development time of the neural network and decreasing the amount of trial and error usually associated with network development