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Neural Processing Letters
Erschienen in: Neural Processing Letters 1/2023

10.06.2022

Stability Analysis of the Impulsive Projection Neural Network

verfasst von: Jia Chen, Jin Hu, B. O. Onasanya, Yuming Feng

Erschienen in: Neural Processing Letters | Ausgabe 1/2023

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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.
Vorheriger Artikel Heavy-Head Sampling for Fast Imitation Learning of Machine Learning Based Combinatorial Auction Solver
Nächster Artikel Adaptive Generation of Weakly Supervised Semantic Segmentation for Object Detection

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Metadaten
Titel
Stability Analysis of the Impulsive Projection Neural Network
verfasst von
Jia Chen
Jin Hu
B. O. Onasanya
Yuming Feng
Publikationsdatum
10.06.2022
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 1/2023
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-022-10901-x

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