Course Objective

  • Students completing this course will be able to understand the representation of various types of signals including data representation and data processing. The course covers the basic concept of signals and systems and the mathematical representation of signals and systems for continuous-time and discrete-time systems, the analysis of signals in frequency and complex frequency domains using the Fourier, Laplace, and Z-transforms. Students will also learn how to analyze the linear feedback systems and convert signal from continuous-time signals to discrete-time signals.

Course Syllabus

  • Introduction to signal and system. Continuous-time signals and systems: mathematical representation of signals, frequency-domain representation of signals, time-domain representation of systems, transform-domain representation of systems and continuous-time system architecture. Discrete-time signals and systems: mathematical representation of signals, frequency-domain representation of signals, time-domain representation of systems, transform-domain representation of systems and discrete-time system architecture. First order and higher order differential equations. Frequency response, Fourier analysis and Laplace transforms.

Course Outcomes

Students graduating this course will be able to:

  • Demonstrate an understanding of the fundamental properties of linear systems.

  • Use linear systems tools, especially transform analysis and convolution, to analyze and predict the behavior of linear systems.

  • Synthesize systems especially frequency selective filter when the specification of input and output is given by using the suitable transforms.

Core text

  • Lathi, B. P., “Signal Processing and Linear Systems”, Berkeley-Cambridge Press, 1998

  • Watcharapong Khovidhungij, “Signals, Systems, and Control”, Chulalongkorn University Press, 2016

Grading Policy:

  • In-class activities evalution 30%

  • Midterm 30%

  • Final 30%

  • Assignment 10%

Homework Scores

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