Design and analysis of recurrent neural network models with non‐linear activation functions for solving time‐varying quadratic programming problems
Abstract A special recurrent neural network (RNN), that is the zeroing neural network (ZNN), is adopted to find solutions to time‐varying quadratic programming (TVQP) problems with equality and inequality constraints. However, there are some weaknesses in activation functions of traditional ZNN mode...
Guardado en:
Autores principales: | Xiaoyan Zhang, Liangming Chen, Shuai Li, Predrag Stanimirović, Jiliang Zhang, Long Jin |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Wiley
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/a9918134877d4dea9872592f5f9a307a |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Low‐rank constrained weighted discriminative regression for multi‐view feature learning
por: Chao Zhang, et al.
Publicado: (2021) -
Constrained tolerance rough set in incomplete information systems
por: Renxia Wan, et al.
Publicado: (2021) -
An efficient hybrid recommendation model based on collaborative filtering recommender systems
por: Mohammed Fadhel Aljunid, et al.
Publicado: (2021) -
Deep imitation reinforcement learning for self‐driving by vision
por: Qijie Zou, et al.
Publicado: (2021) -
Steganography based on quotient value differencing and pixel value correlation
por: Reshma Sonar, et al.
Publicado: (2021)