Technische Universit├Ąt Ilmenau

Neuromorphic Engineering 1 - Modultafeln of TU Ilmenau

The Modultafeln have a pure informational character. The legally binding information can be found in the corresponding Studienplan and Modulhandbuch, which are served on the pages of the course offers. Please also pay attention to this legal advice (german only). Information on place and time of the actual lectures is served in the Vorlesungsverzeichnis.

subject properties subject number 101941 - common information
subject number101941
departmentDepartment of Electrical Engineering and Information Technology
ID of group2143 (Micro- and nanoelectronic Systems Group)
subject leaderProf. Dr. Martin Ziegler
term Sommersemester
previous knowledge and experience
learning outcome

Students will be able to understand and analyze the principles of neural computation methods so that they can compare various advantages and disadvantages of neuro-inspired networks.

  • Biophysical background: neurons, synapses, Data processing invertebrates and vertebrates, Implicit and explicit learning, Short and long-term potentiation, Plasticity
  • Spiking neurons models
  • Hebbian learning theory
  • Neural Networks: an overview (McCulloch-Pitts Neuron, Perceptron, Adalein/Madaline, ART, Boltzmann-Machine)
  • Neuronal analog circuits: Axon Hillock Circuit, LIF-Neuron, STDP, AER
media of instruction

PowerPoint presentation, blackboard

literature / references
  • Gerstner and Kistler, Spiking Neuron Models. Single Neurons, Populations, Plasticity, Cambridge University Press, 2002
  • Analog VLSI and Neural Systems, C. Mead, Addison-Wesley Pub. Comp. 1989
evaluation of teaching
Details in major Master Elektrotechnik und Informationstechnik 2014 (MNE), Master Micro- and Nanotechnologies 2016
subject nameNeuromorphic Engineering 1
examination number2100594
credit points5
on-campus program (h)45
self-study (h)105
Obligationobligatory elective
examoral examination performance, 30 minutes
details of the certificate
maximum number of participants