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.
In this lecture, mathematical processing method of extracting and recognizing the information contained in 1D and 2D measured data are explained comprehensively and practically.
. 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)
Statistical parameter, Statistical analysis of parameters, Fractal analysis
Textbook: Supplied by the faculty
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
Understanding of the knowledge of the lectures, in addition to the ability to apply them to the real measured data
Assignments and final report.
May be written in Japanese excluding International Graduate Program students.
Attendance to the class
Seiichiro Hara harasei＠mei.titech.ac.jp