Module Handbook

  • Dynamischer Default-Fachbereich geändert auf EIT

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


CP, Effort 4.0 CP = 120 h
Position of the semester 1 Sem. in WiSe
Level [7] Master (Advanced)
Language [EN] English
Area of study [EIT-ISE] Integrated Sensor Systems
Livecycle-State [NORM] Active


  • 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


  • 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


  • Lecture slides (PDF)
  • Virtual machine for the lab with data, simulators, and hardware interfaces preinstalled


Registration in the first lecture

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