Biologically-inspired artificial neurons: modeling and applications

Currently used neural networks employ mostly simple neuron models that greatly differ from the "real" biological neurons. To ensure progress in biology-based neural processing, more advanced neuron models must be developed that better reflect the biological functionality. In this paper, we investigate a neuron model which satisfies such requirements to a much higher degree. We also examine some of its learning properties and look at its applications.