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Stability Analysis of the Impulsive Projection Neural Network

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Abstract

Since the neural network model may be affected by the impulse, a projection neural network(PNN) model with impulsive effect, named impulsive projection neural network(IPNN), is proposed in this paper. The IPNN can solve the variational inequalities and related optimization problems much faster than the PNN. We obtain the stability of the IPNN in two steps. Firstly, we construct a Lyapunov function to prove the stability of the PNN. Secondly, we prove that the Lyapunov function is non-increasing under the influence of impulsive effect. Finally, we give three simulation examples to show the performance of the IPNN.

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Acknowledgements

This work is supported by Foundation of Chongqing Municipal Key Laboratory of Institutions of Higher Education ([2017]3), Joint Training Base Construction Project for Graduate Students in Chongqing(JDLHPYJD2021016), Foundation of Chongqing Development and Reform Commission (2017[1007]), National Natural Science Foundation of China under Grants 61773004, Team Building Project for Graduate Tutors in Chongqing under Grants JDDSTD201802, Group Building Scientific Innovation Project for universities in Chongqing CXQT21021 and the Venture & Innovation Support Program for Chongqing Overseas Returnees under Grant cx2019127.

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Authors and Affiliations

  1. College of Mathematics and Statistics, Sichuan University of Science and Engineering, Zigong, 643002, Sichuan, China

    Jia Chen

  2. Department of Mathematics, Chongqing Jiaotong University, Chongqing, 400074, China

    Jin Hu

  3. Key Laboratory of Intelligent Information Processing and Control,Chongqing Three Gorges University, Chongqing, 404100, Wanzhou, People’s Republic of China

    B. O. Onasanya

  4. Department of Mathematics, University of Ibadan, Ibadan, 200284, Oyo State, Nigeria

    B. O. Onasanya

  5. School of Three Gorges Artificial Intelligence, Chongqing Three Gorges University, Chongqing, 404100, Wanzhou, People’s Republic of China

    Yuming Feng

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  1. Jia Chen
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  2. Jin Hu
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  3. B. O. Onasanya
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  4. Yuming Feng
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Correspondence to Jin Hu.

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Chen, J., Hu, J., Onasanya, B.O. et al. Stability Analysis of the Impulsive Projection Neural Network. Neural Process Lett 55, 645–656 (2023). https://doi.org/10.1007/s11063-022-10901-x

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