Abstract
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.
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Yang, G., Qiao, Jf., Li, W., Chai, W. (2013). The Effect of Lateral Inhibitory Connections in Spatial Architecture Neural Network. In: Guo, C., Hou, ZG., Zeng, Z. (eds) Advances in Neural Networks – ISNN 2013. ISNN 2013. Lecture Notes in Computer Science, vol 7951. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39065-4_38
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DOI: https://doi.org/10.1007/978-3-642-39065-4_38
Publisher Name: Springer, Berlin, Heidelberg
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