Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
| additional remarks |
Note: "Neural Engineering: Implants, Interfaces and Algorithms Neuromorphic" is the revised and expanded former "Engineering for Cognitive Systems".
Neural engineering is an interdisciplinary research area that combines foundations of biology, physics, mathematics, computer science, psychology and engineering to design artificial “neural systems”, such as active body prostheses, or autonomous robots, whose design and functional principles are based on those of biological nervous systems. In this lecture students get introduced to basics of neural engineering, such as recordings from neuronal cells, brain-computer interfaces, interpretations of neuronal signals, setup and operational principles of biological and artificial neural networks, distributed system development and computation, event-based sensors or control, or analog low-power VLSI chip design for neural inspired sensors and computing units.
Applications: design of (a) algorithms for sensory data processing and motor control in applications such as neuro-prosthesis, and (b) autonomous cognitive systems to interact in real-time in real-world scenarios. |
| Links |
E-Learning course (e. g. Moodle)
TUMonline entry
|