Course Analog Signals and Systems

---

Responsible: Prof. Dr. Rainer Bartz

Course

Meets requirements of following modules(MID)

• in active programs
  • Ba ET2012 ASS
  • Ba ET2010 ASS
  • Ba TIN2010 ASS

Course Organization

Version created 2013-06-20 VID 4 valid from WS 2012/13 valid to

Course identifiers Long name Analog Signals and Systems CID F07_ASS CEID (exam identifier)

Contact hours per week (SWS) Lecture 2 Exercise (unsplit) Exercise (split) 2 Lab Project Seminar Tutorial(voluntary) 1

Total contact hours Lecture 30 Exercise (unsplit) Exercise (split) 30 Lab Project Seminar Tutorial (voluntary) 15

Max. capacity Exercise (unsplit) Exercise (split) 40 Lab Project Seminar

Total effort (hours): 150

Instruction language

• German, 80%
• English, 20%

Study Level

• Undergraduate

Prerequisites

• all mathematical foundation courses of the program
• trigonometric, exponential and logarithmic functions
• limits, infinite series, partial fraction expansion
• differential and integral calculus
• fundamentals of electrical engineering
• RLC-circuits; complex numbers and functions

Textbooks, Recommended Reading

• Carlson, G. E.: Signal and Linear System Analysis, John Wiley & Sons, Inc.
• Girod, B.: Einführung in die Systemtheorie, Teubner Verlag
• von Grünigen, D. Ch.: Digitale Signalverarbeitung, Fachbuchverlag Leipzig
• Hsu, H.P.: Signals and Systems, Schaums Outlines
• Meyer, M.: Signalverarbeitung, Verlag Vieweg
• Ohm, J.-R.; Lüke, H. D.: Signalübertragung, Springer-Verlag
• Oppenheim, A.V.; Wilsky, A.S.:Signals & Systems, Prentice Hall
• Werner, M.: Signale und Systeme, Verlag Vieweg

Instructors

• Prof. Dr. Rainer Bartz
• Prof. Dr. Harald Elders-Boll
• Prof. Dr. Andreas Lohner

Supporting Scientific Staff

• Dipl.-Ing. Martin Seckler
• Dipl.-Ing. Norbert Kellersohn

Transcipt Entry

Analog Signals and Systems

Assessment

Type
wE	written exam

Total effort [hours]
wE	10

Frequency: 2-3/year

---

Course components

Lecture/Exercise

Objectives

Contents

• basic concepts
  • signal and system; examples
  • classification of signals
  • common signals: cos, exp, step, ramp, impulse (Dirac)
  • characteristics of signals: symmetry, energy, power, RMS
  • odd-even decomposition of signals
  • basic operations with signals: time-scaling, time-reversal, time-shift, and their combinations
  • characteristics of systems: memory, causality, stability
  • block diagrams and their components
• signals
  • Fourier series
  • Fourier transform (1D) of CT signals
    • definition of the Fourier transform
    • Fourier transform pairs and theorems; examples
    • Parseval's theorem
    • auto-correlation function and energy density spectrum
    • cross-correlation function
  • Laplace transform
    • double-sided Laplace transform
    • the complex s-plane
    • single-sided Laplace transform
    • Laplace transform pairs and theorems; examples
    • initial and final value theorem
    • inverse transform using partial fraction expansion
    • relationship to Fourier transform
  • sampling
    • Fourier transform of impulse train
    • ideal sampling
    • spectrum of sampled signals
    • sampling theorem
    • aliasing, examples
• systems; signal transmission
  • continuous time (CT) LTI systems
    • linear, and time-invariant (LTI) systems
    • working with block diagrams
    • impulse input and impulse response
    • step input and step response
    • convolution integral and its evaluation
    • determining characteristics of LTI systems: causality, stability
    • Bode-plot of the frequency response
      • 7 building blocks to construct a Bode-plot
    • the transfer function
    • pole-zero plot and stability
  • design of CT filter systems
    • distortionless transmission
    • basic filter types: low pass, high pass, band pass, band stop filter

Acquired Skills

• students acquire fundamental knowledge on theory and applications of continuous-time signals and systems
• they understand the behavior of typical systems
• they can apply important algorithms for convolution, Fourier-, and Laplace-transform
• they are able to model a system and to analyze it in time and frequency domain
• they can apply system theory to real-world systems (like electrical circuits)

Additional Component Assessment

Type
fAP	(optional) assessed problem solving
fSP	supervised/assisted problem solving

Contribution to course grade
fAP	(if offered) rated: 20%
fSP	not rated

Frequency: 1/year