Existence and Global Convergence of Periodic Solutions in Recurrent Neural Network Models with a General Piecewise Alternately Advanced and Retarded Argument

2013 ◽  
Vol 133 (1) ◽  
pp. 133-152 ◽  
Author(s):  
Kuo-Shou Chiu ◽  
Manuel Pinto ◽  
Jyh-Cheng Jeng
Keyword(s):  
Neural Network ◽  
Global Convergence ◽  
Periodic Solutions ◽  
Recurrent Neural Network ◽  
Network Models ◽  
Retarded Argument ◽  
Neural Network Models

Convergence Theory for Unified Discrete-Time RNNs with Quasi-Symmetric Connection

2014 ◽  
Vol 538 ◽  
pp. 167-170
Author(s):  
Hui Zhong Mao ◽  
Chen Qiao ◽  
Wen Feng Jing ◽  
Xi Chen ◽  
Jin Qin Mao
Keyword(s):  
Neural Network ◽  
Global Convergence ◽  
Discrete Time ◽  
Recurrent Neural Network ◽  
Symmetric Matrix ◽  
Network Models ◽  
Convergence Theory ◽  
Connection Matrix ◽  
Neural Network Models ◽  
Symmetric Connection

This paper presents the global convergence theory of the discrete-time uniform pseudo projection anti-monotone network with the quasi–symmetric matrix, which removes the connection matrix constraints. The theory widens the range of applications of the discrete–time uniform pseudo projection anti–monotone network and is valid for many kinds of discrete recurrent neural network models.

scholarly journals PHTNet: Characterization and Deep Mining of Involuntary Pathological Hand Tremor using Recurrent Neural Network Models

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Soroosh Shahtalebi ◽  
Seyed Farokh Atashzar ◽  
Olivia Samotus ◽  
Rajni V. Patel ◽  
Mandar S. Jog ◽  
...  
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Network Models ◽  
Neural Network Models ◽  
Hand Tremor ◽  
Deep Mining
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