Skip to Main Content

Advertisement

MIT Press Direct, home
header search
Search
Advanced Search
Skip Nav Destination

A One-Layer Recurrent Neural Network with a Discontinuous Activation Function for Linear Programming

Neural Computation (2008) 20 (5): 1366–1383.
This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.
Analysis and prediction of hydrogen-blended natural gas diffusion from various pipeline leakage sources based on CFD and ANN approach
  • Yongjun Li
  • Zhirong Wang
  • Zheng Shang
International Journal of Hydrogen Energy (2024) 53: 535.
A projection recurrent neural network based sliding mode control to stabilize unknown fractional-order chaotic systems
  • Abbas Kariminia
  • Hassan Zarabadipour
International Journal of Dynamics and Control (2023) 11 (4): 1736.
Neurodynamics-driven portfolio optimization with targeted performance criteria
  • Jun Wang
  • Xin Gan
Neural Networks (2023) 157: 404.
Artificial neural network approaches for disaster management: A literature review
  • Sreeparna Guha
  • Rabin K. Jana
  • Manas K. Sanyal
International Journal of Disaster Risk Reduction (2022) 81: 103276.
Cardinality-constrained portfolio selection based on collaborative neurodynamic optimization
  • Man-Fai Leung
  • Jun Wang
Neural Networks (2022) 145: 68.
Fixed-Time Stable Neurodynamic Flow to Sparse Signal Recovery via Nonconvex L1-β2-Norm
  • You Zhao
  • Xiaofeng Liao
  • Xing He
Neural Computation (2022) 34 (8): 1727.
Hash Bit Selection Based on Collaborative Neurodynamic Optimization
  • Xinqi Li
  • Jun Wang
  • Sam Kwong
IEEE Transactions on Cybernetics (2022) 52 (10): 11144.
Sparse signal reconstruction via collaborative neurodynamic optimization
  • Hangjun Che
  • Jun Wang
  • Andrzej Cichocki
Neural Networks (2022) 154: 255.
A Modulation Recognition Algorithm via Hybrid Feature Analysis in Aeronautical Wireless Channel
  • Kun Liu
  • Xin Xiang
  • Zhiying Peng
  • Haoqi Bi
  • Yuan Liang
IEEE Access (2021) 9: 89507.
Application of Neural Network Models for Mathematical Programming Problems: A State of Art Review
  • Kailash Lachhwani
Archives of Computational Methods in Engineering (2020) 27 (1): 171.
Control of magnetic levitation system using recurrent neural network-based adaptive optimal backstepping strategy
  • Armita Fatemimoghadam
  • Hamid Toshani
  • Mohammad Manthouri
Transactions of the Institute of Measurement and Control (2020) 42 (13): 2382.
Activation functions selection for BP neural network model of ground surface roughness
  • Yuhang Pan
  • Yonghao Wang
  • Ping Zhou
  • Ying Yan
  • Dongming Guo
Journal of Intelligent Manufacturing (2020) 31 (8): 1825.
Finite-Time and Fixed-Time Stabilization of Discontinuous Neural Networks With Nonlinear Coupling via Switching Approach
  • Chao Yang
  • Yicheng Liu
  • Lihong Huang
IEEE Access (2020) 8: 184231.
A Discrete-Time Neurodynamic Approach to Sparsity-Constrained Nonnegative Matrix Factorization
  • Xinqi Li
  • Jun Wang
  • Sam Kwong
Neural Computation (2020) 32 (8): 1531.
A neurodynamic approach to nonsmooth constrained pseudoconvex optimization problem
  • Chen Xu
  • Yiyuan Chai
  • Sitian Qin
  • Zhenkun Wang
  • Jiqiang Feng
Neural Networks (2020) 124: 180.
Simultaneous identification, tracking control and disturbance rejection of uncertain nonlinear dynamics systems: A unified neural approach
  • Dechao Chen
  • Shuai Li
  • Qing Wu
  • Liefa Liao
Neurocomputing (2020) 381: 282.
A One-Layer Recurrent Neural Network for Constrained Complex-Variable Convex Optimization
  • Sitian Qin
  • Jiqiang Feng
  • Jiahui Song
  • Xingnan Wen
  • Chen Xu
IEEE Transactions on Neural Networks and Learning Systems (2018) 29 (3): 534.
A nonnegative matrix factorization algorithm based on a discrete-time projection neural network
  • Hangjun Che
  • Jun Wang
Neural Networks (2018) 103: 63.
A Collective Neurodynamic Optimization Approach to Nonnegative Matrix Factorization
  • Jianchao Fan
  • Jun Wang
IEEE Transactions on Neural Networks and Learning Systems (2017) 28 (10): 2344.
A One-Layer Recurrent Neural Network for Pseudoconvex Optimization Problems With Equality and Inequality Constraints
  • Sitian Qin
  • Xiudong Yang
  • Xiaoping Xue
  • Jiahui Song
IEEE Transactions on Cybernetics (2017) 47 (10): 3063.
A Discrete-Time Projection Neural Network for Solving Degenerate Convex Quadratic Optimization
  • Zican Zhang
  • Chuandong Li
  • Xing He
  • Tingwen Huang
Circuits, Systems, and Signal Processing (2017) 36 (1): 389.
A neurodynamic approach to convex optimization problems with general constraint
  • Sitian Qin
  • Yadong Liu
  • Xiaoping Xue
  • Fuqiang Wang
Neural Networks (2016) 84: 113.
A one-layer recurrent neural network for non-smooth convex optimization subject to linear inequality constraints
  • Xiaolan Liu
  • Mi Zhou
Chaos, Solitons & Fractals (2016) 87: 39.
Nonlinear Model Predictive Control Based on Collective Neurodynamic Optimization
  • Zheng Yan
  • Jun Wang
IEEE Transactions on Neural Networks and Learning Systems (2015) 26 (4): 840.
Neural network for constrained nonsmooth optimization using Tikhonov regularization
  • Sitian Qin
  • Dejun Fan
  • Guangxi Wu
  • Lijun Zhao
Neural Networks (2015) 63: 272.
Global Exponential Synchronization of Multiple Memristive Neural Networks With Time Delay via Nonlinear Coupling
  • Zhenyuan Guo
  • Shaofu Yang
  • Jun Wang
IEEE Transactions on Neural Networks and Learning Systems (2015) 26 (6): 1300.
A Two-Layer Recurrent Neural Network for Nonsmooth Convex Optimization Problems
  • Sitian Qin
  • Xiaoping Xue
IEEE Transactions on Neural Networks and Learning Systems (2015) 26 (6): 1149.
An intelligent method of swarm neural networks for equalities-constrained nonconvex optimization
  • Hangjun Che
  • Chuandong Li
  • Xing He
  • Tingwen Huang
Neurocomputing (2015) 167: 569.
A collective neurodynamic optimization approach to bound-constrained nonconvex optimization
  • Zheng Yan
  • Jun Wang
  • Guocheng Li
Neural Networks (2014) 55: 20.
A new neural network for solving quadratic programming problems with equality and inequality constraints
  • Yongqing Yang
  • Jinde Cao
  • Xianyun Xu
  • Manfeng Hu
  • Yun Gao
Mathematics and Computers in Simulation (2014) 101: 103.
Passivity and Passification of Memristor-Based Recurrent Neural Networks With Time-Varying Delays
  • Zhenyuan Guo
  • Jun Wang
  • Zheng Yan
IEEE Transactions on Neural Networks and Learning Systems (2014) 25 (11): 2099.
Selective Positive–Negative Feedback Produces the Winner-Take-All Competition in Recurrent Neural Networks
IEEE Transactions on Neural Networks and Learning Systems (2013) 24 (2): 301.
A new one-layer recurrent neural network for nonsmooth pseudoconvex optimization
  • Sitian Qin
  • Wei Bian
  • Xiaoping Xue
Neurocomputing (2013) 120: 655.
A One-Layer Recurrent Neural Network for Real-Time Portfolio Optimization With Probability Criterion
IEEE Transactions on Cybernetics (2013) 43 (1): 14.
Reinforced recurrent neural networks for multi-step-ahead flood forecasts
  • Pin-An Chen
  • Li-Chiu Chang
  • Fi-John Chang
Journal of Hydrology (2013) 497: 71.
A One-Layer Projection Neural Network for Nonsmooth Optimization Subject to Linear Equalities and Bound Constraints
  • Qingshan Liu
  • Jun Wang
IEEE Transactions on Neural Networks and Learning Systems (2013) 24 (5): 812.
Model Predictive Control of Unknown Nonlinear Dynamical Systems Based on Recurrent Neural Networks
  • Yunpeng Pan
  • Jun Wang
IEEE Transactions on Industrial Electronics (2012) 59 (8): 3089.
A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization
  • Qingshan Liu
  • Zhishan Guo
  • Jun Wang
Neural Networks (2012) 26: 99.
Dynamical behaviors of recurrently connected neural networks and linearly coupled networks with discontinuous right-hand sides
  • Wenlian Lu
  • Tianping Chen
  • Bo Liu
  • Xiangnan He
Frontiers of Electrical and Electronic Engineering (2012) 7 (1): 32.
A new neural network for solving nonlinear convex programs with linear constraints
  • Yongqing Yang
  • Yun Gao
Neurocomputing (2011) 74 (17): 3079.
Global exponential stability of discrete-time recurrent neural network for solving quadratic programming problems subject to linear constraints
  • Qingshan Liu
  • Jinde Cao
Neurocomputing (2011) 74 (17): 3494.
A One-Layer Recurrent Neural Network for Constrained Nonsmooth Optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (2011) 41 (5): 1323.
A One-Layer Recurrent Neural Network for Pseudoconvex Optimization Subject to Linear Equality Constraints
IEEE Transactions on Neural Networks (2011) 22 (12): 1892.
Finite-Time Convergent Recurrent Neural Network With a Hard-Limiting Activation Function for Constrained Optimization With Piecewise-Linear Objective Functions
IEEE Transactions on Neural Networks (2011) 22 (4): 601.
A Recurrent Neural Network Based on Projection Operator for Extended General Variational Inequalities
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (2010) 40 (3): 928.
A Novel Recurrent Neural Network with Finite-Time Convergence for Linear Programming
  • Qingshan Liu
  • Jinde Cao
  • Guanrong Chen
Neural Computation (2010) 22 (11): 2962.
A New One-Layer Neural Network for Linear and Quadratic Programming
IEEE Transactions on Neural Networks (2010) 21 (6): 918.
Global exponential system of projection neural networks for system of generalized variational inequalities and related nonlinear minimax problems
  • Qingshan Liu
  • Yongqing Yang
Neurocomputing (2010) 73 (10-12): 2069.
Global Output Convergence of a Class of Recurrent Delayed Neural Networks with Discontinuous Neuron Activations
  • Zhenyuan Guo
  • Lihong Huang
Neural Processing Letters (2009) 30 (3): 213.
Two k-winners-take-all networks with discontinuous activation functions
  • Qingshan Liu
  • Jun Wang
Neural Networks (2008) 21 (2-3): 406.

Advertisement

  • Online ISSN 1530-888X
  • Print ISSN 0899-7667
A product of The MIT Press
Newsletter sign up

MIT Press Direct

Information

MIT Press

Contact Us

© 2023 The MIT Press
Close Modal
This Feature Is Available To Subscribers Only

or Create an Account

Close Modal
Close Modal
This site uses cookies. By continuing to use our website, you are agreeing to our privacy policy. No content on this site may be used to train artificial intelligence systems without permission in writing from the MIT Press.
Accept