Analysis of associative memories based on cellular neural networks with value-varying templates

ABSTRACT

In many research literatures, the dynamical behaviour of cellular neural networks (CNNs) is simplified by using cloning template. However, the flaws of cloning template are obvious, because the correlation between weights of cells in CNNs is enhanced. In order to overcome the shortcomings of cloning template, value-varying templates can be used in CNNs. In this paper, associative memories based on CNNs with value-varying templates are investigated. A criterion about stability of CNNs is presented. Then, the problem about obtaining parameters of CNNs can be translated into a problem of solving linear equations for each cell. A design procedure of associative memories is given by our theories and methods. From the procedure, the parameters of CNNs can be obtained. Finally, three examples are used to demonstrate the effectiveness of our theories and methods. And the results show that success rate of associative memories is higher than previous methods.

KEYWORDS:

• Cellular neural network
• associative memory
• value-varying template
• stability
• cloning template

2010 MATHEMATICS SUBJECT CLASSIFICATION:

• 34D20

Acknowledgements

The authors would like to thank the reviewers for their constructive comments that improve the paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China [61503050], in part by the Key Technology Project for Heavy Accident Prevention and Control of Safe Production in 2018 [chongqing-0004-2018AQ], in part by the Program of Chongqing Fundamental and Frontier Research Plan [cstc2017jcyjAX0115, cstc2018jcyjAX0583, cstc2017jcyjAX0379], in part by the Foundation of Chongqing University of Education [KY201702A], in part by the Chongqing Outstanding Youth Fund Project [cstc2014jcyjjq90002] and in part by the Research project on Humanities and Social Sciences of the Ministry of Education [18YJCZH018].