Two \(k\)-winners-take-all networks with discontinuous activation functions

DOI10.1016/j.neunet.2007.12.044zbMath1254.90148OpenAlexW2088295634WikidataQ47942315 ScholiaQ47942315MaRDI QIDQ1932004

Qingshan Liu, Jun Wang

Publication date: 17 January 2013

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2007.12.044

zbMATH Keywords

global convergencelinear programmingquadratic programmingdifferential inclusionrecurrent neural networkLyapunov stabilitydiscontinuous activation function

Mathematics Subject Classification ID

Quadratic programming (90C20) Linear programming (90C05) Neural networks for/in biological studies, artificial life and related topics (92B20)

Related Items

A non-penalty recurrent neural network for solving a class of constrained optimization problems, Single-state distributed \(k\)-winners-take-all neural network model, A Novel Recurrent Neural Network with Finite-Time Convergence for Linear Programming, A model of analogue \(K\)-winners-take-all neural circuit, Analysis and design of a distributed \(k\)-winners-take-all model

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Matrix Analysis
• Optimization and nonsmooth analysis
• A Neural Network With<tex>$O(N)$</tex>Neurons for Ranking<tex>$N$</tex>Numbers in<tex>$O(1/N)$</tex>Time
• Stable computational dynamics for a class of circuits with O(N) interconnections capable of KWTA and rank extractions
• Global convergence of neural networks with discontinuous neuron activations
• Dynamical Behaviors of Delayed Neural Network Systems with Discontinuous Activation Functions