ANN Activation Function Comparative Study for Sinusoidal Data

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Dwi Sudarno Putra, Meri Azmi, Muslikhin, Wawan Purwanto

2022 Journal of Physics: Conference Series Vol. 2406 Issue 1 Conference paper Cited by 11 Quartile

Abstract

An artificial neural network (ANN) has neurons that are interconnected. Inside the neuron, there is an activation function that determines the value issued by the neuron. There are several types of activation functions. The choice of activation function will determine the result of an ANN. This paper describes the performance comparison of several activation functions used in an ANN in processing sinusoidal signals. There are three types of activation functions being compared, those are Sigmoid, Tansig, and ReLU. The sinusoidal dataset has come from simulation data of the PMSM FOC control process. The results indicated that the Tansig activation function is the best choice for sinusoid data. © Published under licence by IOP Publishing Ltd.

Affiliations

Departemen Teknik Otomotif, Universitas Negeri Padang, Indonesia; Centre for Energy and Power Electronics Research (CEPER), Universitas Negeri Padang, Indonesia; Jurusan Teknologi Informasi, Politeknik Negeri Padang, Indonesia; Department of Electronics Engineering Education, Universitas Negeri Yogyakarta, Indonesia