Dynamics for a Type of Differential-Algebraic Complex-Valued Neural Networks with Delay
Han Yu,
Ailong Wu and
Zi-Peng Wang
Discrete Dynamics in Nature and Society, 2022, vol. 2022, 1-11
Abstract:
In the article, we apply complex-valued neural networks (CVNNs) to differential-algebraic neural networks (DANNs) and establish a new type of differential-algebraic complex-valued neural network (DACVNN) with delay (DDACVNN). First of all, the focus of existence and uniqueness of the solution to DDACVNN is addressed. Additionally, a theorem of global exponential stability (GES) of DDACVNN is investigated. In particular, in the discussion of this article, there is no restriction on whether the activation function requires that the real and imaginary parts can be dissociated. Finally, we will give two examples, namely, the activation function can separate the real and imaginary parts, and the activation function cannot separate the real and imaginary parts, both of which can confirm the truth of the effectiveness of theoretical results.
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/ddns/2022/5759152.pdf (application/pdf)
http://downloads.hindawi.com/journals/ddns/2022/5759152.xml (application/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:5759152
DOI: 10.1155/2022/5759152
Access Statistics for this article
More articles in Discrete Dynamics in Nature and Society from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().