This course focuses on signal processing, and covers the fundamentals of Fourier series and Fourier transform.
This approach/method is not only useful for solving partial differential equations found in fields of mechanical engineering, electrical engineering, information and communication engineering, but is applicable to many other areas.
Fourier series, Fourier transform, a sampling theorem, a discrete Fourier transform, a fast Fourier transform and a frequency filter can be understood and ready to apply.
Fourier series, Fourier transform, Sampling theorem, Discrete Fourier transform, Fast Fourier Transform, Frequency filter
|✔ Specialist skills||Intercultural skills||Communication skills||Critical thinking skills||✔ Practical and/or problem-solving skills|
Students will be given exercise problems at every lecture.
|Course schedule||Required learning|
|Class 1||Fourier series and orthogonal relationships||Exercise related to Fourier series|
|Class 2||Complex Fourier series, Parseval’s theorem||Exercise related to Complex Fourier series|
|Class 3||Fourier transform of a limited section||Exercise related to Fourier transform|
|Class 4||Characteristics of Fourier transform||Exercise related to Fourier transform|
|Class 5||Discrete Fourier transform and delta function||Exercise related to Discrete Fourier transform|
|Class 6||Sampling theorem and spectrum||Exercise related to Sampling theorem|
|Class 7||Filtering of discrete data, Frequency filter and convolution, Fast Fourier Transform||Exercise related to Fast Fourier Transform|
|Class 8||Summary and development||Exercise|
Handouts will be provided as needed.
Exercises(40%) and tests(60%)