Finite time dual neural networks with a tunable activation function for solving quadratic programming problems and its application

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Bibliographic Details
Published inNeurocomputing (Amsterdam) Vol. 143; pp. 80 - 89
Main Authors Miao, Peng, Shen, Yanjun, Xia, Xiaohua
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier 02.11.2014
Subjects
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Connectionism. Neural networks
Continuous conveyors: mechanical, hydraulic, pneumatic, etc
Exact sciences and technology
Flows in networks. Combinatorial problems
Material handling, hoisting. Storage. Packaging
Mathematical programming
Operational research and scientific management
Operational research. Management science
Additive noise
Recurrent neural nets
Recurrent neural networks
Stability
Finite-time stability
Computer simulation
Quadratic programming problem
Lyapunov method
Tunable activation function
Conveyor belt
Neural network
Quadratic programming
Flexibility
Modeling
Delay
Activation function
Optimal solution
Problem solving
Time interval
Belt conveyor
Lyapunov function
Quadratic function
Online AccessGet full text
ISSN0925-2312
DOI10.1016/j.neucom.2014.06.018

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ISSN:0925-2312
DOI:10.1016/j.neucom.2014.06.018