Module Handbook

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Notes on the module handbook of the department Social Sciences

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Module SO-08-2612-M-6

Advanced Module 5: Computation - Research and Methods (M, 6.0 LP)

Module Identification

Module Number Module Name CP (Effort)
SO-08-2612-M-6 Advanced Module 5: Computation - Research and Methods 6.0 CP (180 h)

Basedata

CP, Effort 6.0 CP = 180 h
Position of the semester 1 Sem. in WiSe/SuSe
Level [6] Master (General)
Language [EN] English
Module Manager
Lecturers
Area of study [INF-VIS] Visualisation and Scientific Computing
Reference course of study [SO-88.A95-SG] M.Sc. Cognitive Science
Livecycle-State [NORM] Active

Courses

Type/SWS Course Number Title Choice in
Module-Part
Presence-Time /
Self-Study
SL SL is
required for exa.
PL CP Sem.
2V+1U EIT-ISE-110-K-7
Neurocomputing
WP 42 h 78 h
PRAK
- no 4.0 WiSe
4L INF-16-81-K-7
Visualisation and HCI (Project)
WP 56 h 184 h
PRAK
- no 8.0 WiSe/SuSe
4L INF-61-81-K-7
Service Robots and Assistance Systems (Project)
WP 56 h 184 h
PRAK
- no 8.0 SuSe
  • About [EIT-ISE-110-K-7]: Title: "Neurocomputing"; Presence-Time: 42 h; Self-Study: 78 h
  • About [EIT-ISE-110-K-7]: The study achievement [PRAK] practical exercises (successful participation) must be obtained.
  • About [INF-16-81-K-7]: Title: "Visualisation and HCI (Project)"; Presence-Time: 56 h; Self-Study: 184 h
  • About [INF-16-81-K-7]: The study achievement [PRAK] practical exercises (successful participation) must be obtained.
  • About [INF-61-81-K-7]: Title: "Service Robots and Assistance Systems (Project)"; Presence-Time: 56 h; Self-Study: 184 h
  • About [INF-61-81-K-7]: The study achievement [PRAK] practical exercises (successful participation) must be obtained.

Examination achievement PL1

  • Form of examination: written or oral examination
  • Examination Frequency: each semester
  • Examination number: 60200 ("Advanced Module 5: Computation - Research and Methods")

Evaluation of grades

The grade of the module examination is also the module grade.


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
Different tasks from visualiuzation, e.g.:
  • Visualization of scalar fields: Implemention of algortithms like marching cubes, volume rendering, etc.
  • Visualization of vector fields: Implemention of algortithms like stream lines and surfaces, turbulence detection, detection of topology, etc.
  • Construction of visualization framework for the implemented algorithms with interactive graphical output based on
  • Learning the development tool MCA
  • Programming of DSPs
  • Basic sensor processing
  • Specification of a service robot or an assisting system
  • Implementation of a complex control task

Competencies / intended learning achievements

On successfully completing the module students will be able to,
  • design human-centered man-machine interfaces and prototypically implement them
  • design and perform evaluations for hard- and software systems
  • design and develop some basic functions a robot system
  • design, validate, and optimize complete application-specific systems from sensory acquisition to perception & cognition
  • adapt and extend the achieved implementation to changing needs
  • prepare special topics and present them to the audience comprehensibly using electronic media
  • prepare and manage a scientific discussion on specific topics related to the module

Requirements for attendance (informal)

None

Requirements for attendance (formal)

None

References to Module / Module Number [SO-08-2612-M-6]

Course of Study Section Choice/Obligation
[SO-88.A95-SG] M.Sc. Cognitive Science Basis Modules [WP] Compulsory Elective