Strategy of Incremental Learning on a Compartmental Spiking Neuron Model

Abstract

The article presents a method for implementing incremental learning on a compartmental spiking neuron model. The training of one neuron with the possibility of forming new classes was chosen as an incremental learning scenario. During the training, only a new sample was used, without knowledge of the entire previous training samples. The results of experiments on the Iris dataset are presented, demonstrating the applicability of the chosen strategy for incremental learning on a compartmental spiking neuron model.