Today's most powerful computers are still outperformed by biological brains in
routine functions such as vision, audition, and motor control. The reasons for
this gap between biological and artificial systems are not fully understood.
Understanding the principles of biological computation and how to implement them
in hardware, is crucial for developing novel techniques for information
processing.
Neuromorphic engineering attempts to use the principles and style of
computation observed in biology. Neuromorphic systems emphasize distributed,
collective, self-organized, eventdriven mechanisms. The building blocks of these
systems are analog circuits in which transistors are mostly operated weak
inversion (below threshold), where their exponential I-V characteristics and low
currents can be exploited. These features allow the implementation of massively
parallel, low-power spiking recurrent neural networks as well as e�cient sensors.
Students will acquire basic analog design skills necessary to understand the
building blocks of neuromorphic engineering. They will become familiar with the
most widely used neuronal and synaptic circuits.
Frequency | Weekday | Time | Format / Place | Period | |
---|---|---|---|---|---|
weekly | Mo | 14-16 | T2-233 | 06.10.2014-06.02.2015
not on: 12/22/14 / 12/29/14 |
Module | Course | Requirements | |
---|---|---|---|
39-Inf-NE1 Neuromorphic Engineering 1 | Neuromorphic Engineering I | Student information | |
- | Graded examination | Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
Degree programme/academic programme | Validity | Variant | Subdivision | Status | Semester | LP | |
---|---|---|---|---|---|---|---|
Sportwissenschaft / Master | (Enrollment until SoSe 2014) | IuB; WP B1; WP B2 | Wahlpflicht | 2 | benotet + 2 LP für veranstaltungsübergreifende mündl. Prüfung |
Die Veranstaltung Neuromorphic Engineering I ist eine
Modulveranstaltung, die in englischer Sprache gehalten wird. Sie besteht
aus einer Vorlesung, einer wöchentlichen Übung, einem wöchentlichen
Praktikum und einer mündlichen Prüfung. Da es sich um eine
Modulveranstaltung handelt, ist es für den Erhalt der LP notwendig, an
allen Teilveranstaltungen teilzunehmen. Es werden insgesamt 10 LP
vergeben, sofern alle erforderlichen Teilleistungen erbracht wurden.
Bitte bei Besuch dieser Veranstaltung, alle Teilveranstaltungen
(Vorlesung, Übung, Praktikum) im eKVV in den Stundenplan aufnehmen. Die
Zeiten für die Übung und das Praktikum wurden im eKVV festgelegt, können
aber bei Bedarf in der ersten Vorlesungsstunde in Absprache mit den
Teilnehmern neu vereinbart werden.