Global convergence of neural networks with mixed time-varying delays and discontinuous neuron activations

2012 ◽  
Vol 183 (1) ◽  
pp. 92-105 ◽  
Author(s):  
Jun Liu ◽  
Xinzhi Liu ◽  
Wei-Chau Xie
Keyword(s):  
Neural Networks ◽  
Global Convergence ◽  
Time Varying ◽  
Discontinuous Neuron Activations

Long-Range Out-of-Sample Properties of Autoregressive Neural Networks

2009 ◽  
Vol 21 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Patrick Leoni
Keyword(s):  
Neural Networks ◽  
Global Convergence ◽  
Long Range ◽  
Sufficient Conditions ◽  
Time Varying ◽  
Out Of Sample

We consider already-trained discrete autoregressive neural networks in their most general representations, with the exclusion of time-varying input though, and we provide tight sufficient conditions and elementary proofs for the existence of an attractor, uniqueness, and global convergence. Those conditions can be used as easy-to-check criteria when convergence (or not) of long-range predictions is desirable.

scholarly journals Finite-time projective synchronization of stochastic complex-valued neural networks with probabilistic time-varying delays

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Meng Hui ◽  
Jiahuang Zhang ◽  
Jiao Zhang ◽  
Herbert Ho-Ching Iu ◽  
Rui Yao ◽  
...  
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Projective Synchronization ◽  
Time Varying ◽  
Complex Valued
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