On the K-winners-take-all-network
Advances in neural information processing systems 1
Winner-take-all networks of O(N) complexity
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NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Novel sorting network-based architectures for rank order filters
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special issue on low-power design
KWTA networks and their applications
Multidimensional Systems and Signal Processing
Dynamics of a winner-take-all neural network
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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Introduction to the Theory of Neural Computation
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Analog Integrated Circuits and Signal Processing
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Machine Learning
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A Discrete-Time Recurrent Neural Network with One Neuron for k-Winners-Take-All Operation
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A discrete-time dynamic K-winners-take-all neural circuit
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IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Two-dimensional rank-order filter by using max-min sorting network
IEEE Transactions on Circuits and Systems for Video Technology
A new k-winners-take-all neural network and its array architecture
IEEE Transactions on Neural Networks
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IEEE Transactions on Neural Networks
Another K-winners-take-all analog neural network
IEEE Transactions on Neural Networks
Performance analysis for a K-winners-take-all analog neural network: basic theory
IEEE Transactions on Neural Networks
A Simplified Dual Neural Network for Quadratic Programming With Its KWTA Application
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
K-winners-take-all circuit with O(N) complexity
IEEE Transactions on Neural Networks
Analysis and design of an analog sorting network
IEEE Transactions on Neural Networks
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ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
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Neural Networks
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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 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 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.