Exponential Stability Analysis of Mixed Delayed Quaternion-Valued Neural Networks Via Decomposed Approach
| Autor: | Shiping Wen, Jie Tan, Huamin Wang |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Cauchy's convergence test
exponential stability General Computer Science Artificial neural network Quaternion-valued neural networks General Engineering Order (ring theory) Monotonic function 02 engineering and technology 01 natural sciences Exponential stability Control theory 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Applied mathematics discrete and distributed delays 020201 artificial intelligence & image processing General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering Uniqueness generalized 2-norm Quaternion lcsh:TK1-9971 010301 acoustics Mathematics |
| Zdroj: | IEEE Access, Vol 8, Pp 91501-91509 (2020) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2020.2994554 |
| Popis: | With the application of quaternion in technology, quaternion-valued neural networks (QVNNs) have attracted many scholars' attention in recent years. For the existing results, dynamical behavior is an important studying side. In this paper, we mainly research the existence, uniqueness and exponential stability criteria of solutions for the QVNNs with discrete time-varying delays and distributed delays by means of generalized 2-norm. In order to avoid the noncommutativity of quaternion multiplication, the QVDNN system is firstly decomposed into four real-number systems by Hamilton rules. Then, we obtain the sufficient criteria for the existence, uniqueness and exponential stability of solutions by special Lyapunov-type functional, Cauchy convergence principle and monotone function. Furthermore, several corollaries are derived from the main results. Finally, we give one numerical example and its simulated figures to illustrate the effectiveness of the obtained conclusion. |
| Databáze: | OpenAIRE |
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