Study programme 2019-2020Français
Signal processing
Programme component of Bachelor's in Computer Science à la Faculty of Science

Students are asked to consult the ECTS course descriptions for each learning activity (AA) to know what assessment methods are planned for the end of Q3

CodeTypeHead of UE Department’s
contact details
Teacher(s)
US-B3-SCINFO-016-MOptional UEDUTOIT ThierryF105 - Information, Signal et Intelligence artificielle
  • DUTOIT Thierry

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Anglais
Anglais163200055.001st term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
I-TCTS-030Signal Processing 11632000Q1100.00%
Programme component

Objectives of Programme's Learning Outcomes

  • Understand the fundamentals of computer science
    • Show an understanding and deep knowledge of the concepts of computer science and mathematical formalisms used in the field of computer science
    • Solve exercises and computer problems by applying basic knowledge in the various disciplines of computer science
  • Demonstrate basic knowledge and know-how in related fields
    • Have a good knowledge of English in order to read and understand scientific texts, especially in the field of computer science.
    • Demonstrate knowledge and basic skills in science and technology.
  • Understand the fundamentals related to scientific methods
    • Develop skills of abstraction and modelling through a conceptual and scientific approach
    • Conduct rigorous reasoning based on scientific arguments
  • Understand the fundamentals of communication
    • Have a good command of language and communication techniques.

Learning Outcomes of UE

understand the theory required for developing a library of basic digital signal processing components (sampling, convolution, filtering, poles and zeros in the z plane, FFT, sub-band analysis)

Content of UE

linear time-invariant digital systems; frequency analysis of digital signals and systems; Shannon theorem and sampling theory; discrete (and Fast) Fourier Transform; digital filters (including elements of digital filter synthesis); simple digital system in PYTHON.

Prior Experience

Not applicable

Type of Assessment for UE in Q1

  • Presentation and/or works
  • Written examination

Q1 UE Assessment Comments

Project report = 35%; writen exam = 65%

Type of Assessment for UE in Q3

  • Written examination

Q3 UE Assessment Comments

writen exam = 100%

Type of Resit Assessment for UE in Q1 (BAB1)

  • N/A

Q1 UE Resit Assessment Comments (BAB1)

Not applicable

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
I-TCTS-030
  • Cours magistraux
  • Exercices dirigés
  • Travaux pratiques
  • Projet sur ordinateur

Mode of delivery

AAMode of delivery
I-TCTS-030
  • Face to face

Required Reading

AA
I-TCTS-030

Required Learning Resources/Tools

AARequired Learning Resources/Tools
I-TCTS-030Not applicable

Recommended Reading

AA
I-TCTS-030

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
I-TCTS-030Not applicable

Other Recommended Reading

AAOther Recommended Reading
I-TCTS-030AUGER, F. (1999) Introduction à la théorie du signal et de l'information, 461 pp. Paris : TechnipDENBIGH, P. (1998) System Analysis and Signal Processing, 513 pp. Harlow : Addison-WesleyBAHER, H. (2001) Analog and Digital Signal Processing, 497 pp. Chichester : Wiley & SonsLYONS, R.G. (1998) Understanding Digital Signal Processing, 517pp. Harlow : Addison-Wesley

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
I-TCTS-030Authorized
(*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term
Date de génération : 13/07/2020
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