Principles of computerized tomographic imaging
Principles of computerized tomographic imaging
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Shape Analysis and Classification: Theory and Practice
Shape Analysis and Classification: Theory and Practice
Neural Networks - 2005 Special issue: IJCNN 2005
Recurrent Neural Networks for Music Computation
INFORMS Journal on Computing
Neural Computation
Training Recurrent Networks by Evolino
Neural Computation
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This paper describes a method to initialize the LSTM network weights and estimate the configuration of hidden units in order to improve training time for function approximation tasks. The motivation of this method is based on the behavior of the hidden units and the complexity of the function to be approximated. The results obtained for 1-D and 2-D functions show that the proposed methodology improves the network performance, stabilizing the training phase.