2019 Experiments of Information and Communications Engineering I

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Academic unit or major
Undergraduate major in Information and Communications Engineering
Yamaguchi Masahiro  Shinozaki Takahiro  Nakamura Tomoya 
Course component(s)
Lecture /     
Day/Period(Room No.)
Tue3-4(VLSI設計室)  Fri1-4(VLSI設計室)  
Course number
Academic year
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Syllabus updated
Lecture notes updated
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Course description and aims

This experiment deals with the analysis of analog filter, the design of digital filter, and the frequency analysis.
Students implement the programs of convolution, spectrum analysis, and sampling, and apply them to practical digital signals for enhancing the understanding of these subjects. Next, the Gibbs phenomenon and the effect of window function are observed. FIR and IIR filters are designed and applied to some signals such as acoustic signals to confirm the effect of those digital filters. The transfer function of an analog filter is analyzed and a digital filter is designed according to the analyzed transfer function. Finally, through programming of the multirate signal processing, students will learn the examples of its applications.

Student learning outcomes

The aim of this experiment is to achieve deeper understanding of digital signal processing through programming the algorithm and implementing some application examples by using MATLAB.


Discrete signal, linear system, convolution, Fourier transform, DFT, FFT, window function, FIR filter, IIR filter, bilinear transform method, impulse invariant method, downsampling and upsampling

Competencies that will be developed

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

Class flow

Through MATLAB programming on the subjects from Part 1 to 5, and applying the programs to artificial and acoustic data, students acquire deeper understanding by considering the meaning of the results. While it is assumed that students concurrently attend ICT.S210 Digital Signal Processing, the experiment will be carried out independently upon the lecture. If there are any questions, consult either the instructor or TA to solve them. It is recommended to read the reference book for better comprehension of the experiment.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Part 1 Introduction of signal processing (1) Representation of signal and system Generate various digital signals and plot their graphs as discrete time signals.
Class 2 Part 1 Introduction of signal processing (2) Convolution and Fourier transform Observe the results of convolution, Fourier transform of convolution, Fourier transform of two signals.
Class 3 Part 1 Introduction of signal processing (3) Spectrum analysis of discrete time signal Derive the Fourier transforms of various signals and observe the plots of their amplitudes and phases.
Class 4 Part 1 Introduction of signal processing (4) Sampling of signal and reconstruction Generate the simulated continuous time signal and apply sampling. Then reconstruct the original signal from the sampled signal. Observe the aliasing effect in time domain and frequency domain.
Class 5 Part 2 Mastering FFT (1) Spectrum analysis using DFT With correct understanding of the meaning of frequency, show the graphs of the DFT results.
Class 6 Part 2 Mastering FFT (2) Implementation of convolution using FFT Implement convolution using FFT. Discuss the method to obtain the same results as linear convolution.
Class 7 Part 3 FIR filter (1) Examining the linear phase characteristics Construct FIR filter from given parameters, and show the filtering results. Observe the graph of frequency response of the filter.
Class 8 Part 3 FIR filter (2) Ideal low-pass filter Apply ideal LPF using FFT. Design and apply an FIR LPF. Observe Gibbs phenomenon.
Class 9 Part 3 FIR filter (3) FIR filter design by window function method Design LPF, BPF, and HPF using hamming window function and apply them to real digital signal.
Class 10 Part 4 IIR filter (1) Analysis of analog filter Derive frequency response of an analog filter using Laplace transform. Derive the parameters the Butterworth filter.
Class 11 Part 4 IIR filter (2) Bilinear transform method and impulse invariant method Design 2nd-order Butterworth digital filter and Chebyshev digital filter using bilinear transform and window function methods.
Class 12 Part 4 IIR filter (3) Frequency conversion Design various LPF, BPF, and HPF using frequency conversion method and apply them to various signals.
Class 13 Part 4 IIR filter (4) Examining BIBO stability Verify the stability of IIR filters. Apply various digital filters to acoustic signals and compare the results.
Class 14 Part 5 Multirate signal processing (1) Downsampling and upsampling Confirm the difference of output signals with different interpolation functions in upsampling.
Class 15 Part 5 Multirate signal processing (2) Conversion of sampling rate Investigate the relationship between the file size, sound quality and sampling rate in various acoustic signals.


Download the course materials through OCW-i.

Reference books, course materials, etc.

樋口龍雄,川又政征著,MATLAB対応 ディジタル信号処理(森北出版株式会社)

Assessment criteria and methods

Grading will be decided based on the understanding level of the contents from part 1 to 5 by submitted reports.

Related courses

  • ICT.S210 Digital Signal Processing

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

It is desirable that students concurrently attend ICT.S210 Digital Signal Processing.

Contact information (e-mail and phone)    Notice : Please replace from "[at]" to "@"(half-width character).

Masahiro Yamaguchi, E-mail: yamaguchi.m.aa[at]m.titech.ac.jp
Takahiro Shinozaki, E-mail: shinot[at]ip.titech.ac.jp
Tomoya Nakamura, E-mail: nakamura.t.bj[at]m.titech.ac.jp

Office hours

Contact by e-mail in advance.

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