Title :
Character Recognition using Spiking Neural Networks
Author :
Gupta, Ankur ; Long, Lyle N.
Author_Institution :
Pennsylvania State Univ., University Park
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.
Keywords :
character recognition; neural nets; active dendrite neurons; character recognition; inhibitory connections; spike time dependent plasticity; spiking neural networks; two layered structure; Artificial neural networks; Biological information theory; Biology computing; Character recognition; Delay; Mobile robots; Navigation; Neural networks; Neurons; Temporal lobe;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4370930