Richard Hahnloser: Katalogdaten im Herbstsemester 2016 |
Name | Herr Prof. Dr. Richard Hahnloser |
Lehrgebiet | Neuroinformatik |
Adresse | Institut für Neuroinformatik ETH Zürich, Y55 G 27 Winterthurerstrasse 190 8057 Zürich SWITZERLAND |
Telefon | +41 44 635 30 51 |
hrichard@ethz.ch | |
Departement | Informationstechnologie und Elektrotechnik |
Beziehung | Ordentlicher Professor |
Nummer | Titel | ECTS | Umfang | Dozierende | |
---|---|---|---|---|---|
227-1036-01L | NSC Master Short Project I (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: INI505 Mind the enrolment deadlines at UZH: http://www.uzh.ch/studies/application/mobilitaet_en.html | 8 KP | 17A | R. Hahnloser | |
Kurzbeschreibung | Usually a student selects the topic of a Master Short Project in consultation with his or her mentor. | ||||
Lernziel | see above | ||||
227-1036-02L | NSC Master Short Project II (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: INI506 Mind the enrolment deadlines at UZH: http://www.uzh.ch/studies/application/mobilitaet_en.html | 8 KP | 17A | R. Hahnloser | |
Kurzbeschreibung | Usually a student selects the topic of a Master Short Project in consultation with his or her mentor. | ||||
Lernziel | see above | ||||
227-1039-00L | Basics of Instrumentation, Measurement, and Analysis (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: INI502 Mind the enrolment deadlines at UZH: http://www.uzh.ch/studies/application/mobilitaet_en.html 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. | 4 KP | 9V | S.‑C. Liu, T. Delbrück, A. Ghosh, R. Hahnloser, G. Indiveri, V. Mante, P. Pyk, W. von der Behrens | |
Kurzbeschreibung | Experimental 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). | ||||
Lernziel | The 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. | ||||
Voraussetzungen / Besonderes | For 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. | ||||
227-1041-01L | NSC Master's Theses (long) and Exam (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: INI503 Mind the enrolment deadlines at UZH: http://www.uzh.ch/studies/application/mobilitaet_en.html Only students who fulfil the following criteria are allowed to begin with their master thesis: a. successful completion of the bachelor programme; b. fulfilling of any additional requirements necessary to gain admission to the master programme. | 45 KP | 96D | R. Hahnloser | |
Kurzbeschreibung | The Master thesis concludes the study programme. Thesis work should prove the students' ability to independent, structured and scientific working. | ||||
Lernziel | see above | ||||
227-1041-02L | NSC Master's Thesis and Exam (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: INI504 Mind the enrolment deadlines at UZH: http://www.uzh.ch/studies/application/mobilitaet_en.html Only students who fulfil the following criteria are allowed to begin with their master thesis: a. successful completion of the bachelor programme; b. fulfilling of any additional requirements necessary to gain admission to the master programme. | 29 KP | 62D | R. Hahnloser | |
Kurzbeschreibung | The Master thesis concludes the study programme. Thesis work should prove the students' ability to independent, structured and scientific working. | ||||
Lernziel | see above | ||||
227-1043-00L | Neuroinformatics - Colloquia (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: INI701 Mind the enrolment deadlines at UZH: http://www.uzh.ch/studies/application/mobilitaet_en.html | 0 KP | 1K | S.‑C. Liu, R. Hahnloser, V. Mante, K. A. Martin | |
Kurzbeschreibung | Das Kolloquium der Neuroinformatik ist eine Vortragsserie eingeladener Experten. Die Vorträge spiegeln Schwerpunkte aus der Neurobiologie und des Neuromorphic Engineering wider, die speziell für unser Institut von Relevanz sind. | ||||
Lernziel | Die Vorträge informieren Studenten und Forscher über neueste Forschungsergebnisse. Dementsprechend sind die Vorträge primaer nicht fuer wissenschaftliche Laien, sondern für Forschungsspezialisten konzipiert. | ||||
Inhalt | Die Themen haengen stark von den eingeladenen Spezialisten ab und wechseln von Woche zu Woche. Alle Themen beschreiben aber 'Neural computation' und deren Implementierung in biologischen und kuenstlichen Systemen. |