scholarly journals An adjustable 0.3 V current winner‐take‐all circuit for analogue neural networks

2021 ◽  
Author(s):  
Meysam Akbari ◽  
Ting‐I Chou ◽  
Kea‐Tiong Tang
Keyword(s):  
Neural Networks ◽  
Winner Take All ◽  
Take All

Neural networks for selection and the Luce choice rule

2000 ◽  
Vol 23 (4) ◽  
pp. 471-472
Author(s):  
Claus Bundesen
Keyword(s):  
Neural Networks ◽  
Selection Process ◽  
Race Model ◽  
Neural Mechanism ◽  
Nerve Fibers ◽  
Choice Rule ◽  
Inhibitory Network ◽  
Winner Take All ◽  
Take All

Page proposes a simple, localist, lateral inhibitory network for implementing a selection process that approximately conforms to the Luce choice rule. I describe another localist neural mechanism for selection in accordance with the Luce choice rule. The mechanism implements an independent race model. It consists of parallel, independent nerve fibers connected to a winner-take-all cluster, which records the winner of the race.

Combining distributed and localist computations in real-time neural networks

2000 ◽  
Vol 23 (4) ◽  
pp. 473-474 ◽  
Author(s):  
Gail A. Carpenter
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Neural Models ◽  
Distributed Representations ◽  
Network Hierarchy ◽  
Winner Take All ◽  
Take All

In order to benefit from the advantages of localist coding, neural models that feature winner-take-all representations at the top level of a network hierarchy must still solve the computational problems inherent in distributed representations at the lower levels.

Training Winner-Take-All Simultaneous Recurrent Neural Networks

2007 ◽  
Vol 18 (3) ◽  
pp. 674-684 ◽  
Author(s):  
Xindi Cai ◽  
D.V. Prokhorov ◽  
D.C. Wunsch
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Winner Take All ◽  
Take All

Optoelectronic thresholding module for winner-take-all operations in optical neural networks

1994 ◽  
Vol 33 (8) ◽  
pp. 1463 ◽  
Author(s):  
Alain Bergeron ◽  
Henri H. Arsenault ◽  
Erik Eustache ◽  
Denis Gingras
Keyword(s):  
Neural Networks ◽  
Optical Neural Networks ◽  
Winner Take All ◽  
Take All

scholarly journals Emergent Inference of Hidden Markov Models in Spiking Neural Networks Through Winner-Take-All

2020 ◽  
Vol 50 (3) ◽  
pp. 1347-1354 ◽  
Author(s):  
Zhaofei Yu ◽  
Shangqi Guo ◽  
Fei Deng ◽  
Qi Yan ◽  
Keke Huang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov ◽  
Spiking Neural Networks ◽  
Winner Take All ◽  
Take All
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