- 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
Neurocomputing (M, 4.0 LP)
|Module Number||Module Name||CP (Effort)|
|EIT-ISE-110-M-7||Neurocomputing||4.0 CP (120 h)|
|CP, Effort||4.0 CP = 120 h|
|Position of the semester||1 Sem. in WiSe|
|Level|| Master (Advanced)|
|Area of study||[EIT-ISE] Integrated Sensor Systems|
|Reference course of study||[EIT-88.781-SG#2010] M.Sc. Electrical and Computer Engineering |
|Type/SWS||Course Number||Title||Choice in |
|SL||SL is |
required for exa.
|P||42 h||78 h||
Examination achievement PL1
- Form of examination: oral examination (30 Min.)
- Examination Frequency: each semester
Evaluation of grades
The grade of the module examination is also the module grade.
Competencies / intended learning achievements
After completing this module you can...
- ... explain the concepts of dedicated neural and bio-inspired hardware and its application potential and limitations.
- ... explain the design principles of circuits with alternative signal representation and adaptive structures.
- ... explain the issues of supervised and unsupervised learning, host-based learning or on-line continuous learning systems.
- ... explain and master the effects of simplified implementations.
- ... explain fault-tolerance and robustness issues in conventional and neural computing systems.
- ... abstract contents/result to M(O)EMS/microsystems application.
- ... code and/or simulate a neural algorithm in Python, BRIAN, etc.
- ... compile (labeled) examples from application scenario, create data sets for training/validation/test, select and train a neural network, and apply it for newly measured data (live classification).
- ... use a neural computing device, e.g., analog or digital neural hardware, customizing it to application and data source, e.g., sensor, and execute real-time classification/processing.
- ... physically design and validate custom neurons, neural circuits, and neural systems in an established CMOS-process (with given background in microelectronics).
Requirements for attendance of the module (informal)
- [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 of the module (formal)None
References to Module / Module Number [EIT-ISE-110-M-7]
|Course of Study||Section||Choice/Obligation|
|[EIT-88.781-SG#2010] M.Sc. Electrical and Computer Engineering ||[Free Elective Area] Elective Subjects||[W] Elective Module|
|[EIT-88.A20-SG#2021] M.Sc. European Master in Embedded Computing Systems (EMECS) ||[Free Elective Area] Elective Subjects||[W] Elective Module|
|[EIT-88.A44-SG#2018] M.Sc. Media and Communication Technology ||[Free Elective Area] Technical Elective Subjects||[W] Elective Module|
|[EIT-88.D55-SG#2021] M.Sc. Embedded Computing Systems (ESY) ||[Free Elective Area] Elective Subjects||[W] Elective Module|
|[EIT-AC-MSC-TW-MPOOL-7]||General Elective Modules Master A&C|
|[EIT-EIT-MSC-TW-MPOOL-7]||Technical Elective Modules Master EIT|
|[EIT-MKT-MSC-TW-MPOOL-7]||Technical Elective Modules Master MKT|
|[EIT-SIAK-DT-ENG-MPOOL]||SIAK Certificate "Digital Transformation" - Modules EIT "Engineering"|