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IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 21, NO. 12, DECEMBER 2010 1939 Periodic Activation Function and a Modified
 

Summary: IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 21, NO. 12, DECEMBER 2010 1939
Periodic Activation Function and a Modified
Learning Algorithm for the Multivalued Neuron
Igor Aizenberg, Senior Member, IEEE
Abstract--In this paper, we consider a new periodic activation
function for the multivalued neuron (MVN). The MVN is a
neuron with complex-valued weights and inputs/output, which
are located on the unit circle. Although the MVN outper-
forms many other neurons and MVN-based neural networks
have shown their high potential, the MVN still has a limited
capability of learning highly nonlinear functions. A periodic
activation function, which is introduced in this paper, makes
it possible to learn nonlinearly separable problems and non-
threshold multiple-valued functions using a single multivalued
neuron. We call this neuron a multivalued neuron with a periodic
activation function (MVN-P). The MVN-Ps functionality is much
higher than that of the regular MVN. The MVN-P is more
efficient in solving various classification problems. A learning
algorithm based on the error-correction rule for the MVN-P is
also presented. It is shown that a single MVN-P can easily learn

  

Source: Aizenberg, Igor - College of Science, Technology, Engineering, and Mathematics, Texas A&M University at Texarkana

 

Collections: Computer Technologies and Information Sciences