Sampling Neural Network: A Novel Neural Network Based on Sampling Theorem

In this paper, a new neural network algorithm is proposed, which is based on the signal sampling theorem. A new activation function of neural network in Sa(t) form and a new neuron weight error correction method are proposed. The sampling neural network algorithm (SNN) has the following advantages: clarity in theory, simple in design, reliable in operation, convenient in hardware implementation, low in operations, low in input sample data requirements, and does not fall into local minimum. The specific implementation of the method fully considers the hardware implementation, so the neural network algorithm has certain application prospects and value.