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Based on the theories of lateral inhibition and artificial neural network (ANN), the different lateral inhibitory connections among the hidden neurons of SANN are studied. With the connect mode of activation-inhibition-activation, the SANN will obtain a higher learning accuracy and generalization ability. Furthermore, this inhibitory connection considers both the activation before and after been inhibited by surrounding neurons. The effectiveness of this inhibitory mode is demonstrated by simulation results. © 2013 Springer-Verlag Berlin Heidelberg.
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