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Continuous time recurrent neural network designed for KWTA operation

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2 Author(s)
Costea, R.L. ; Dept. of Electr. Eng., Polytech. Univ. of Bucharest, Bucharest, Romania ; Marinov, C.A.

The paper shows rigorously how to build a KWTA selector from a classical neural Hopfield network in continuous time. The analytical relations between parameters result in a step-by-step accurate and flexible procedure to calculate the amplifiers gain, the processing and the resetting thresholds and the bias current.

Published in:

Neural Networks (IJCNN), The 2011 International Joint Conference on

Date of Conference:

July 31 2011-Aug. 5 2011