Basic theories for information processing

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Lecturer
Yamashita Yukihiko 
Place
Fri5-6(S632)  
Credits
Lecture0  Exercise0  Experiment0
Code
70011
Syllabus updated
2009/11/12
Lecture notes updated
2009/9/28
Semester
Fall Semester

Purpose of lecture

To learn basic techniques of information processing for international development.
Linear algebra, optimization technique, and statistical estimation are lectured.

Plan of lecture

1. Introduction, eigenvalue problem
2. Singular value decomposition
3. Generalized inverses
4. Octave for linear algebra processing
5. Maximum gradient method
6. Conjugate gradient method
7. Quasi-Newton's method
8. Conditional optimization
9. Support vector machine
10. Probability
11. Normal distribution
12 Geometrical estimation and testing
13 Cramer-Rao lower bound
14. Statistical learning theory

Textbook and reference

Prints are prepared.

Related and/or prerequisite courses

Linear algebra

Evaluation

Reports 70%, Home work 30%

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