Course EIT-ISE-110-K-7
Neurocomputing (2V+1U, 4.0 LP)
Course Type
| SWS | Type | Course Form | CP (Effort) | Presence-Time / Self-Study | |
|---|---|---|---|---|---|
| - | K | Lecture with exercise classes (V/U) | 4.0 CP | ||
| 2 | V | Lecture | 28 h | 48 h | |
| 1 | U | Lecture hall exercise class | 14 h | 30 h | |
| (2V+1U) | 4.0 CP | 42 h | 78 h | ||
Basedata
| SWS | 2V+1U |
|---|---|
| CP, Effort | 4.0 CP = 120 h |
| Position of the semester | 1 Sem. in WiSe |
| Level | [7] Master (Advanced) |
| Language | [EN] English |
| Lecturers | |
| Area of study | [EIT-ISE] Integrated Sensor Systems |
| Livecycle-State | [NORM] Active |
Contents
- Introduction to the field of innovative computer architectures and systems for the technical implementation of biological information processing principles
- Presentation of diverse aims and solution concepts: Hardware for technical cognition systems, biological-technical interfaces, simulation and verification of models of biological evidence
- Rehearsal of relevant and commonly applied neural algorithms, including deep networks/deep-learning and analysis of computational requirements and operators
- Extension from amplitude-coded to spike-coded representation and processing
- Presentation and effect of potential simplification options for the regarded algorithms
- Basics of circuit technology (digital, analog, opto-elektronic/optisch) and related implementation technologies (CMOS, WSI, M(O)EMS, etc.) for neural hardware
- Overview of fundamental architectural principles of neurochips, -processors and -computers
- Assessment criteria and taxonomy for neural HW
- Presentation and detailed discussion of selected, representative implementations
- Outlook on new lines in the field, e.g., evolvable hardware, organic computing, and self-monitoring and repairing sensor systems
Literature
- S. Haykin: Neural Networks – A Comprehensive Foundation. Prentice Hall, 1998, ISBN 0132733501
- G. Cauwenberghs, M. Bayoumi: Learning on Silicon –Adaptive VLSI Neural Systems. Kluwer, 1999, ISBN 0-7923-8555-1
- W. Maas, C. Bishop: Pulsed Neural Networks. MIT Press, 1999, ISBN 0-262-13350-4
- D. Mange, M. Tomassini: Bio-Inspired Computing Machines. PPUR, 1998, ISBN 2-88074-371-0
- R. Hecht-Nielsen: Neurocomputing. Addison Wesley, 1991
Materials
- Lecture slides (PDF)
- Virtual machine for the lab with data, simulators, and hardware interfaces preinstalled
Registration
Registration in the first lecture
Requirements for attendance (informal)
Modules:
- [EIT-DSV-531-M-4] Digital Signal Processing (M, 4.0 LP)
- [EIT-ISE-112-M-7] Sensor Signal Processing (M, 5.0 LP)
- [EIT-ISE-651-M-4] Technology and Design of Integrated Mixed-Signal Circuits and Systems (TESYS) (M, 5.0 LP)
- [EIT-ISE-701-M-2] Electronics I (M, 6.0 LP)
- [EIT-ISE-702-M-3] Electronics II (M, 4.0 LP)
Requirements for attendance (formal)
None
References to Course [EIT-ISE-110-K-7]
| Module | Name | Context | |
|---|---|---|---|
| [EIT-ISE-110-M-7] | Neurocomputing | P: Obligatory | 2V+1U, 4.0 LP |
| [SO-08-2611-M-6] | Computation -. Specialized Seminars | WP: Obligation to choose | 2V+1U, 4.0 LP |
| [SO-08-2612-M-6] | Advanced Module 5: Computation - Research and Methods | WP: Obligation to choose | 2V+1U, 4.0 LP |