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HU Credits:
2
Degree/Cycle:
2nd degree (Master)
Responsible Department:
Brain Science: Computation & Information Proc.
Semester:
2nd Semester
Teaching Languages:
English
Campus:
E. Safra
Course/Module Coordinator:
Israel Nelken
Coordinator Office Hours:
Appointments by email
Teaching Staff:
Prof Israel Nelken
Mr. Nizar Abed
Mr. David Beniaguev
Course/Module description:
The course will provide knowledge and expertise in data analysis for neuroscience. It will include lectures and practical work in class.
Course/Module aims:
The course will provide basic expertise in understanding the structure of data, time and frequency representations, filtering, parameter estimations and basics of statistical evaluation approaches.
Learning outcomes - On successful completion of this module, students should be able to:
Describe random time series by their correlation structure and frequency content
Design and apply filters in the time and frequency domains
characterize repeated shapes using orthogonal decompositions
Identify parametric models and evaluate the significance of the estimated parameters
Attendance requirements(%):
100
Teaching arrangement and method of instruction:
Lectures and practical class sessions
Course/Module Content:
Representation of time sequences in the time and frequency domains
Filtering in the time and frequency domains
Design of filters
Characterization of shapes by orthogonal decompositions (principal components and similar)
Formulation and identification of parametric models
Required Reading:
No
Additional Reading Material:
No
Course/Module evaluation:
End of year written/oral examination 0 %
Presentation 0 %
Participation in Tutorials 0 %
Project work 70 %
Assignments 30 %
Reports 0 %
Research project 0 %
Quizzes 0 %
Other 0 %
Additional information:
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