Samsung Electronics Co., Ltd.

Universitaet Zuerich

Bodo Ruckauer

Shih-Chii Liu

Michael Pfeiffer

Yuhuang Hu

Iulia-Alexandra Lungu

A processor-implemented neural network method includes acquiring connection weight of an analog neural network (ANN) node of a pre-trained ANN; and determining, a firing rate of a spiking neural network (SNN) node of an SNN, corresponding to the ANN node, based on an activation of the ANN node which is determined based on the connection weight. and the firing rate is also determined based on information indicating a timing at which the SNN node initially fires.

Neural network apparatus and method

A neural network conversion method and a recognition apparatus that implements the method are provided. A method of converting an analog neural network (ANN) to a spiking neural network (SNN) normalizes first parameters of a trained ANN based on a reference activation that is set to be proximate to a maximum activation of artificial neurons included in the ANN, and determines second parameters of an SNN based on the normalized first parameters.

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Zurich, Switzerland

Bodo Ruckauer