- 担当教員
- 原 精一郎
- 使用教室
- 火3-4(W831)
- 単位数
- 講義：2 演習：0 実験：0
- 講義コード
- 77037
- シラバス更新日
- 2014年10月1日
- 講義資料更新日
- 2015年1月21日
- アクセス指標
-
- 学期
- 後期
講義概要
Recently, because of the improvements of measuring instruments and computers, enormous measurement data can be acquired very easily. However it is not easy to interpret the information contained in such data correctly.
講義の目的
In this lecture, mathematical processing method of extracting and recognizing the information contained in 1D and 2D measured data are explained comprehensively and practically.
講義計画
. Acquirement of measurement data
Variations of data, Strategy of measurement
2. Separation of components
Analogue filtering, Digital filtering, Filter bank, Noise reduction, Waveform error removal
3. Recognition of characteristics
Fourier transform, Wavelet transform
Spectrum estimation (FFT, Information entropy)
Auto-correlation, Cross-correlation,
Statistical parameter, Statistical analysis of parameters, Fractal analysis
Sensory test
教科書・参考書等
Textbook: Supplied by the faculty
Reference:
Random Data: Analysis and Measurement Procedures, Julius S. Bendat & Allan G. Piersol, 4th edition, 1998
An Introduction to Stochastic Process with special reference to Methods and Applications, M. S. Bartlett 1966
Chaotic and Fractal Dynamics: An Introduction for Applied Scientists and Engineers, Francis C. Moon, 1992
関連科目・履修の条件等
None
成績評価
Understanding of the knowledge of the lectures, in addition to the ability to apply them to the real measured data
Policy
Assignments and final report.
May be written in Japanese excluding International Graduate Program students.
Attendance to the class
連絡先（メール、電話番号）
Seiichiro Hara harasei＠mei.titech.ac.jp
