Analysis and Design of a $k$-Winners-Take-All Model With a Single State Variable and the Heaviside Step Activation Function

Jun Wang
2010 IEEE Transactions on Neural Networks  
This paper presents a k-winners-take-all (kWTA) neural network with a single state variable and a hard-limiting activation function. First, following several kWTA problem formulations, related existing kWTA networks are reviewed. Then, the kWTA model model with a single state variable and a Heaviside step activation function is described and its global stability and finite-time convergence are proven with derived upper and lower bounds. In addition, the initial state estimation and a
more » ... on and a discrete-time version of the kWTA model are discussed. Furthermore, two selected applications to parallel sorting and rank-order filtering based on the kWTA model are discussed. Finally, simulation results show the effectiveness and performance of the kWTA model.
doi:10.1109/tnn.2010.2052631 pmid:20709640 fatcat:63joiqudnbbvnprnut6lu7hc7m