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2017　Signal and System Analysis

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Academic unit or major
Undergraduate major in Information and Communications Engineering
Instructor(s)
Yamada Isao  Yoshimura Natsue 
Class Format
Lecture / Exercise     
Media-enhanced courses
Day/Period(Room No.)
Tue3-4(I311)  Fri1-4(I311)  
Group
-
Course number
ICT.S206
Credits
3
Academic year
2017
Offered quarter
2Q
Syllabus updated
2017/3/21
Lecture notes updated
-
Language used
Japanese
Access Index

Course description and aims

In the broad range of the information and communications engineering, signal analysis has been a powerful mathematical tool box for understanding the behaviors of signals and systems through alternative expressions, , as the sum / integral of well-understood elementary functions, e.g, monomial functions and trigonometric functions. Starting from the elementary complex analysis as a prerequisite of the signal analysis, this lecture surveys its central ideas found, e.g., in Taylor series expansion, Laurent series expansion, Fourier series expansion, Fourier transform, Sampling theorems, Discrete time Fourier transform and Laplace transform.

Student learning outcomes

Through the lectures and seminars, the students will be able to:
1) understand mathematical treatments of complex functions.
2) understand the mathematical ideas and calculation methods of the major signal analyses, e.g., Fourier series, Fourier transform, Laplace transform.
3) understand the technical value of the frequency analysis and apply to the broad range of Information and Communications engineering.

Keywords

Linear systems, Eigen functions, Complex Analysis, Euler's formula, Complex derivative, Cauchy-Riemann equation, Holomorphic function, Complex integral, Cauchy's integral theorem, Cauchy's integral formula, Cauchy's residue theorem, Laurent series expansion, Taylor series expansion, Fourier series expansion, Complex Fourier series expansion, Fourier Integral, Fourier transform, Sampling theorem, Discrete time Fourier transform, Laplace transform, Differential equation, Linear time invariant systems and frequency responses.

Competencies that will be developed

✔ Specialist skills Intercultural skills Communication skills ✔ Critical thinking skills ✔ Practical and/or problem-solving skills

Class flow

Two lectures and one seminar are given in every week.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Invitation to Signal and System Analysis: Eigen functions of Linear Systems Explain about eigen functions of linear systems.
Class 2 Complex number system: four arithmetic operations, Euler's formula Explain how real field can be extended to complex field. Explain about Euler's formula
Class 3 Complex functions: Continuity, Differentiability, Cauchy-Riemann's equation, Holomorphic function Explain about the relation between differentiability of two variable real function and complex function.
Class 4 Holomorphic function and Complex Integral: Cauchy's integral theorem, Cauchy's integral formula Explain Cauchy's integral theorem and Cauchy's integral formula.
Class 5 Taylor series expansion and Laurent series expansion Explain about the relation between Taylor series expansion and Laurent series expansion.
Class 6 Cauchy's residue theorem and its application to definite integral Explain about Cauchy's residue theorem and how this theorem can be applied to application to definite integral.
Class 7 Supplementary Lecture on Complex Analysis Explain about the elements of the complex analysis.
Class 8 Fourier Analysis and Signal Processing 1 Explain about Fourier Series and Fourier Transform from Signal Processing view point
Class 9 Fourier Analysis and Signal Processing 2 Explain about the relation between Sampling theorem and Discrete time Fourier transform
Class 10 Fourier series 1: Trigonometric polynomial approximation, Fourier series expansion, Convergence theorems Explain about (i) the relation between the trigonometric polynomial approximation and Fourier series, and (ii) convergence theorem of Fourier series expansion.
Class 11 Fourier series 2: Gibbs phenomenon, Parseval's equation，Orthogonal function expansion Explain about Gibbs' phenomenon and Parseval's equation.
Class 12 Fourier integral: Derivation of Fourier and Inverse Fourier transforms, Parseval's equation, Convolution theorem Explain about the relation between Fourier transform and Fourier series expansion.
Class 13 Laplace transform 1: Laplace transform and its inversion, Basic properties and calculation formulae Explain about the relation between Laplace transform and Fourier transform.
Class 14 Laplace transform 2: Applications to differential and integral equations Explain how to apply Laplace transform to differential equation and integral iequation.
Class 15 Laplace transform 3: Applications to transient analysis of linear systems Apply Laplace transform to transient analysis of linear systems.

Textbook(s)

M. Sakawa, Ouyou kaisekigaku no kiso, Morikita Publishing, 2014 (in Japanese).

Reference books, course materials, etc.

Lecture materials will be given if necessary.

Assessment criteria and methods

Learning achievement is evaluated based on a terminal exam(8) and quizzes(2). The numbers indicate approximate weights for the evaluation.

Related courses

  • LAS.M102 ： Linear Algebra I / Recitation
  • LAS.M101 ： Calculus I / Recitation
  • ICT.C201 ： Introduction to Information and Communications Engineering
  • ICT.S210 ： Digital Signal Processing
  • ICT.I207 ： Linear Circuits
  • ICT.S302 ： Functional Analysis and Inverse Problems
  • ICT.S307 ： Statistical Signal Processing
  • ICT.C214 ： Communication Systems

Prerequisites (i.e., required knowledge, skills, courses, etc.)

As a general rule, we accept only applications from students in the department of Information and communications Engineering

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