Neural network approaches based on new NCP-functions for solving tensor complementarity problem
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computational Mathematics
Link
https://link.springer.com/content/pdf/10.1007/s12190-021-01509-w.pdf
Reference39 articles.
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3. Alcantara, J.H., Chen, J.-S.: Neural networks based on three classes of NCP-functions for solving nonlinear complementarity problems. Neurocomputing 359, 102–113 (2019)
4. Chen, J.-S., Ko, C.H., Pan, S.-H.: A neural network based on generalized Fischer–Burmeister function for nonlinear complementarity problems. Inf. Sci. 180, 697–711 (2010)
5. Chen, C., Mangasarian, O.L.: A class of smoothing functions for nonlinear and mixed complementarity problems. Comput. Optim. Appl. 5, 97–138 (1996)
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1. Improved Fixed Point Iterative Methods for Tensor Complementarity Problem;Journal of Optimization Theory and Applications;2023-09-27
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