Analytical study on the associative memory problem in coupled Hopfield neural networks

2005 ◽  
Author(s):  
Shouhei Yaghi ◽  
Toshihiro Shimizu
2019 ◽  
Vol 11 (2) ◽  
Author(s):  
Hao Tang ◽  
Zhen Feng ◽  
Ying-Han Wang ◽  
Peng-Cheng Lai ◽  
Chao-Yue Wang ◽  
...  

2018 ◽  
Vol 7 (3.12) ◽  
pp. 652
Author(s):  
Monurajan P ◽  
Ruhanbevi A ◽  
Manjula J

Artificial Neural Networks are interconnection of neurons inspired from the biological neural network of the brain. ANN is claimed to rule the future, spreads its wings to various areas of interest to name a few such as optimization, information technology, cryptography, image processing and even in medical diagnosis. There are devices which possess synaptic behaviour, one such device is memristor. Bridge circuit of memristors can be combined together to form neurons. Neurons can be made into a network with appropriate parameters to store data or images. Hopfield neural networks are chosen to store the data in associative memory. Hopfield neural networks are a significant feature in ANN which are recurrent in nature and in general are used as associative memory and in solving optimization problems such as the Travelling Salesman Problem. The paper deals on the construction of memristive Hopfield neural network using memristor bridging circuit and its application in the associative memory. This paper also illustrates the experiment with mathematical equations and the associative memory concept of the network using Matlab.  


2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yutian Zhang ◽  
Guici Chen ◽  
Qi Luo

AbstractIn this paper, the pth moment exponential stability for a class of impulsive delayed Hopfield neural networks is investigated. Some concise algebraic criteria are provided by a new method concerned with impulsive integral inequalities. Our discussion neither requires a complicated Lyapunov function nor the differentiability of the delay function. In addition, we also summarize a new result on the exponential stability of a class of impulsive integral inequalities. Finally, one example is given to illustrate the effectiveness of the obtained results.


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