Neuromorphic Engineering 2 - Interactive curriculae of TU Ilmenau

The interactive curriculae provide information on the degree programmes offered by the TU Ilmenau.

Please refer to the respective study and examination rules and regulations for the legally binding curricula (Annex Curriculum).

You can find all details on planned lectures and classes in the course catalogue.

Please note that this page is no longer updated. All modules and study plans from PO version 2021 onwards (Bachelor and Master study programs) are now available on the Campus Portal.

module properties Neuromorphic Engineering 2 in degree program Master Micro- and Nanotechnologies 2016
ATTENTION: not offered anymore

module number

200669

examination number

2101049

department

Department of Electrical Engineering and Information Technology

ID of group

2143 (Micro- and Nanoelectronic Systems)

module leader

Prof. Dr. Martin Ziegler

term

winter term only

language

Englisch

credit points

on-campus program (h)

self-study (h)

105

obligation

elective module

exam

written examination performance, 90 minutes

details of the certificate

Im Rahmen der Übung können die Teilnehmer Bonuspunkte für die erfolgreiche Bearbeitung bestimmter (vom Prüfer festgelegter) Teilaufgaben sammeln, welche zur Verbesserung der schriftlichen Prüfungsleistung mitangerechnet werden können.

In the frame of the seminars you can gain bonus points for some of the excercises (pre-defined by the teacher). These points can be used to improve your written exam.

link to Moodle course

teacher

Dr. Claudia Lenk

signup details for alternative examinations

maximum number of participants

previous knowledge and experience

Neuromorphic Engineering 1

learning outcome

After the lectures and exercises, the students are able to understand and analyze the principles of biological sensing and information processing and the adaptation of these principles in technological system. They can compare different neuromorphic sensors, regarding their underlying principles and performance, and know about advantages and disadvantages of these technologies compared to conventional sensors.

content

Biophysical background: biological sensors (vision, auditory, olfactory, tactile), pre-processing at sensor level, sensory adaptation, and processing methods and pathways for sensory information
Asynchronous ouput representation/ Adress-event representation
Event-driven computation
Nonlinear dynamics: an overview (bifurcations and their properties, fix-point analysis)
Neuromorphic vision sensors
Neuromorphic auditory sensors
Sensor fusion for neuromorphic sensors
Application in the robotic and medical field (retinal/cochlea implants)

media of instruction and technical requirements for education and examination in case of online participation

PowerPoint presentation, blackboard

literature / references

Analog VLSI and Neural Systems, C. Mead, Addison-Wesley Pub. Comp. 1989

evaluation of teaching