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Asymptotical Stability for a Class of Complex-Valued Projective Neural Network

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  • Jin-dong Li

    (Sichuan University
    Chengdu University of Technology)

  • Nan-jing Huang

    (Sichuan University)

Abstract

In this paper, a new class of complex-valued projective neural network is introduced and studied on a nonempty, closed, and convex subset of a finite-dimensional complex space. An existence and uniqueness result for the equilibrium point of complex-valued projective neural network is proved under some suitable conditions. Moreover, by utilizing the linear matrix inequality technique, some sufficient conditions are presented to ensure the asymptotical stability of the complex-valued projective neural network. Finally, two examples are given to illustrate the validity and feasibility of main results.

Suggested Citation

  • Jin-dong Li & Nan-jing Huang, 2018. "Asymptotical Stability for a Class of Complex-Valued Projective Neural Network," Journal of Optimization Theory and Applications, Springer, vol. 177(1), pages 261-270, April.
    • Handle: RePEc:spr:joptap:v:177:y:2018:i:1:d:10.1007_s10957-018-1252-2
    DOI: 10.1007/s10957-018-1252-2
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    References listed on IDEAS

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    4. Chen, Xiaofeng & Zhao, Zhenjiang & Song, Qiankun & Hu, Jin, 2017. "Multistability of complex-valued neural networks with time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 294(C), pages 18-35.
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    Cited by:

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    2. Jinlong Shu & Lianglin Xiong & Tao Wu & Zixin Liu, 2019. "Stability Analysis of Quaternion-Valued Neutral-Type Neural Networks with Time-Varying Delay," Mathematics, MDPI, vol. 7(1), pages 1-23, January.

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