A recalling-enhanced recurrent neural network: Conjugate gradient learning algorithm and its convergence analysis
Elman network is a classical recurrent neural network with an internal delay feedback. In this
paper, we propose a recalling-enhanced recurrent neural network (RERNN) which has a …
paper, we propose a recalling-enhanced recurrent neural network (RERNN) which has a …
Weak and strong convergence analysis of Elman neural networks via weight decay regularization
L Zhou, Q Fan, X Huang, Y Liu - Optimization, 2023 - Taylor & Francis
In this paper, we propose a novel variant of the algorithm to improve the generalization
performance for Elman neural networks (ENN). Here, the weight decay term, also called L 2 …
performance for Elman neural networks (ENN). Here, the weight decay term, also called L 2 …
A modified conjugate gradient-based Elman neural network
L Li, X **e, T Gao, J Wang - Cognitive Systems Research, 2021 - Elsevier
Elman recurrent network is a representative model with feedback mechanism. Although
gradient descent method has been widely used to train Elman network, it frequently leads to …
gradient descent method has been widely used to train Elman network, it frequently leads to …
A CNN-based neuromorphic model for classification and decision control
In this paper, an insect brain-inspired computational structure was developed. The
peculiarity of the core processing layer is the local connectivity among the spiking neurons …
peculiarity of the core processing layer is the local connectivity among the spiking neurons …
An efficient Elman neural networks based on improved conjugate gradient method with generalized Armijo search
M Zhu, T Gao, B Zhang, Q Sun, J Wang - … 15-18, 2018, Proceedings, Part I …, 2018 - Springer
Elman neural network is a typical class of recurrent network model. Gradient descent
method is the popular strategy to train Elman neural networks. However, the gradient …
method is the popular strategy to train Elman neural networks. However, the gradient …