Scholles, M.M.SchollesHosticka, B.J.B.J.HostickaRichert, P.P.RichertSchwarz, M.M.Schwarz2022-03-082022-03-081993https://publica.fraunhofer.de/handle/publica/32077110.1109/IJCNN.1993.714185Currently 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 communication, 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.enadaptionadaptive systemBiokybernetikbiological cyberneticsImpulsfolgelearningLernenmathematisches Modellneural networkneuronales Netzwerkpulse trainrangeSchallortungsignal delaySignalverzögerungsonarsound locationsound navigation621conference paper