Course Syllabus

The syllabuses on both this page and the NTU online course information are synchronized.

Course Information

Item Content
Course title Functional Analysis and Approximation Theory
Semester 112-2
Designated for GRADUATE INSTITUTE OF COMMUNICATION ENGINEERING
GRADUATE INSTITUTE OF ELECTRICAL ENGINEERING
Instructor THIERRY BLU
Curriculum No. CommE 7006
Curriculum Id No. 942 M0330
Class
Credit 3
Full/Half Yr. Half
Required/Elective Elective
Time Wednesday 6,7,8(13:20~16:20)
Place 博理212
Remarks The course is conducted in English。

 

Course Syllabus

Item Content
Course Description This course provides graduate students with a panorama of functional analysis and approximation theory in multiple dimensions, adopting a systematic dual point of view (functions defined through a collection of measurements, weak formulations). The emphasis will be laid on the simplest, albeit modern mathematical concepts and mechanisms, with a view to avoid extraneous formalism and more abstract (e.g., topological) considerations. This knowledge will be used to model engineering problems (e.g., data acquisition, sampling), to devise methods for solving exactly or approximately the inverse problems that are related (e.g., resulting from partial differential equations), and to analyze the error resulting from the approximations.
Course Objective Equip postgraduate students with advanced knowledge on functional analysis (in particular, on measure theory, integration and generalized functions), and on the approximation of functions using bases (in particular, polynomial, spline and wavelet approximations). At the end of this course, students are expected to be know how to deal with the measurements (generalized samples) of functions to construct accurate approximating functions.
Course Requirement Grading: 5 Homeworks on • Lebesgue integration (15%) • Hilbertian Analysis (15%) • Distribution Theory (15%) • Calculus of Variations (15%) • Approximation Theory (15%) 1 Matlab assignment on approximation theory and wavelets (20%) Class participation (5%)
Student Workload (expected study time outside of class per week)
References D.M.A. Bressoud, A radical approach to Lebesgue’s theory of integration, Cambridge University Press, (2008) C.F. Gerald and P.O. Wheatley, Applied Numerical analysis, Addison-Wesley (1999) Gel'fand, Izrail Moiseevich, et al. Generalized functions. Vol. 1. New York: Academic press, 1968. D.C. Champeney, A handbook of Fourier theorems, Cambridge University Press (1987) R. Dautray and J.L. Lions, Mathematical Analysis and Numerical Methods for Science and Technology: Functional and Variational Methods Springer (2000) Mallat, Stéphane. A wavelet tour of signal processing. Access Online via Elsevier, 1999.
Designated Reading

 

Progress

Week Date Topic

 

Grading

NO Item Pc Explanations for the conditions

 

Adjustment methods for students

Adjustment method
Teaching methods
Assignment submission methods
Exam methods
Others

 

Office Hour

Remarks None