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- W2105567701 abstract "A spiking neural network model is used to identify characters in a character set. The network is a two layered structure consisting of integrate-and-fire and active dendrite neurons. There are both excitatory and inhibitory connections in the network. Spike time dependent plasticity (STDP) is used for training. The winner take all mechanism is enforced by the lateral inhibitory connections. It is found that most of the characters are recognized in a character set consisting of 48 characters. The network is trained successfully with increased resolution of the characters. Also, addition of uniform random noise does not decrease its recognition capability." @default.
- W2105567701 created "2016-06-24" @default.
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- W2105567701 date "2007-08-01" @default.
- W2105567701 modified "2023-09-26" @default.
- W2105567701 title "Character Recognition using Spiking Neural Networks" @default.
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- W2105567701 doi "https://doi.org/10.1109/ijcnn.2007.4370930" @default.
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