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Homogeneous artificial neural network with a variable activation
Vestnik rossijskih universitetov. Matematika, Tome 22 (2017) no. 1, pp. 39-44
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The model of homogeneous artificial neural network (ANN) with a variable activation function of the neuron isstudied. The program is developed on Python 3. Numerical experiments for artificial neural network training using classical nonlinear programming methods (gradient, Monte Carlo, coordinate descent) on the basis of empirical data of blood tests showed that such approach can be used for the ANN-models implementation in various fields.
Keywords: artificial neural network; activation function of artificial neuron; program for artificial neural network simulation; blood test results of patients. 
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A. A. Arzamastsev; M. A. Kislyakov; N. A. Zenkova. Homogeneous artificial neural network with a variable activation. Vestnik rossijskih universitetov. Matematika, Tome 22 (2017) no. 1, pp. 39-44. http://geodesic.mathdoc.fr/item/VTAMU_2017_22_1_a5/

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