%0 Journal Article
%T Quaternionic Multilayer Perceptron with Local Analyticity
%A Teijiro Isokawa
%A Haruhiko Nishimura
%A Nobuyuki Matsui
%J Information
%D 2012
%I MDPI AG
%R 10.3390/info3040756
%X A multi-layered perceptron type neural network is presented and analyzed in this paper. All neuronal parameters such as input, output, action potential and connection weight are encoded by quaternions, which are a class of hypercomplex number system. Local analytic condition is imposed on the activation function in updating neurons¡¯ states in order to construct learning algorithm for this network. An error back-propagation algorithm is introduced for modifying the connection weights of the network.
%K quaternion
%K local analyticity
%K Wirtinger calculus
%K multilayer perceptron
%K error back-propagation
%U http://www.mdpi.com/2078-2489/3/4/756