Work

Fixed-time synchronization of Clifford-valued neural networks with D operator via aperiodic semi-intermittent control

Year: 2025

Type: article

Abstract: As Clifford-valued neural networks (CVNNs) are more versatile than real-valued, complex-valued, or quaternion-valued neural networks; it is important to study their dynamical characteristics. In this paper, the fixed-time synchronization (FTS) problem for a class of delayed CVNNs with D operator via aperiodic semi-intermittent control is studied. The proposed models are first deconstructed real-valued models since Clifford numbers cannot be multiplied commutatively. To achieve the FTS result, a new controller with aperiodic and semi-intermittent characteristics is developed. The inequality technique and analytic method are utilized to identify many essential requirements in the innovative study, which contribute to the establishment of the FTS for the systems under consideration. Specifically, the settling time is accurately forecasted and is unaffected by the initial value. To validate the correctness of the obtained results, a numerical example is shown in the interim.

Source: Advances in Continuous and Discrete Models

DOI: 10.1186/s13662-025-03911-1

Authors: Pan Wang, Xuechen Li, Qianqian Zheng

Institutions: Xuchang University, Zhongyuan University of Science and Technology

Language: English

Topic: Neural Networks Stability and Synchronization

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $1,890

Funders: Henan University, Natural Science Foundation of Henan Province, Xuchang University