227-1039-00L  Basics of Instrumentation, Measurement, and Analysis (University of Zurich)

SemesterAutumn Semester 2017
LecturersS.‑C. Liu, T. Delbrück, R. Hahnloser, G. Indiveri, V. Mante, P. Pyk, W. von der Behrens
Periodicityyearly recurring course
Language of instructionEnglish
CommentNo enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: INI502

Mind the enrolment deadlines at UZH:
Link

Registration in this class requires the permission of the instructors. Class size will be limited to available lab spots.
Preference is given to students that require this class as part of their major.



Courses

NumberTitleHoursLecturers
227-1039-00 SBasics of Instrumentation, Measurement, and Analysis (University of Zurich)
Permission from lecturers required for all students.
**Course at University of Zurich**
120s hrsby appt.S.‑C. Liu, T. Delbrück, R. Hahnloser, G. Indiveri, V. Mante, P. Pyk, W. von der Behrens

Catalogue data

AbstractExperimental data are always as good as the instrumentation and measurement, but never any better. This course provides the very basics of instrumentation relevant to neurophysiology and neuromorphic engineering, it consists of two parts: a common introductory part involving analog signals and their acquisition (Part I), and a more specialized second part (Part II).
ObjectiveThe goal of Part I is to provide a general introduction to the signal acquisition process. Students are familiarized with basic lab equipment such as oscilloscopes, function generators, and data acquisition devices. Different electrical signals are generated, visualized, filtered, digitized, and analyzed using Matlab (Mathworks Inc.) or Labview (National Instruments).

In Part II, the students are divided into small groups to work on individual measurement projects according to availability and interest. Students single-handedly solve a measurement task, making use of their basic knowledge acquired in the first part. Various signal sources will be provided.
Prerequisites / NoticeFor each part, students must hand in a written report and present a live demonstration of their measurement setup to the respective supervisor. The supervisor of Part I is the teaching assistant, and the supervisor of Part II is task specific. Admission to Part II is conditional on completion of Part I (report + live demonstration).

Reports must contain detailed descriptions of the measurement goal, the measurement procedure, and the measurement outcome. Either confidence or significance of measurements must be provided. Acquisition and analysis software must be documented.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits4 credits
ExaminersS.-C. Liu
Typeungraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.
Additional information on mode of examinationRegistration modalities, date and venue of this performance assessment are specified solely by the UZH.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

GeneralPermission from lecturers required for all students

Offered in

ProgrammeSectionType
Neural Systems and Computation MasterCompulsory Core CoursesOInformation