scholarly journals Some properties of asymmetric Hopfield neural networks with finite time of transition between states

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Ibragim Suleimenov ◽  
Grigoriy Mun ◽  
Sergey Panchenko ◽  
Ivan Pak

AbstractThere were implemented samples of asymmetric Hopfield neural networks which have finite time of transition from one state to another. It was shown that in such systems, various oscillation modes could occur. It was revealed that the oscillation of the output signal of certain neuron could be treated as extra logical variable, which describes the state of the neuron. Asymmetric Hopfield neural networks are described in terms of ternary logic. Such logic may be employed in image recognition procedure.

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Li Liang

This paper is concerned with the problem of finite-time boundedness for a class of delayed Markovian jumping neural networks with partly unknown transition probabilities. By introducing the appropriate stochastic Lyapunov-Krasovskii functional and the concept of stochastically finite-time stochastic boundedness for Markovian jumping neural networks, a new method is proposed to guarantee that the state trajectory remains in a bounded region of the state space over a prespecified finite-time interval. Finally, numerical examples are given to illustrate the effectiveness and reduced conservativeness of the proposed results.


2015 ◽  
Vol 156 ◽  
pp. 193-198 ◽  
Author(s):  
Tianbo Wang ◽  
Shouwei Zhao ◽  
Wuneng Zhou ◽  
Weiqin Yu

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