Difference between revisions of "BSc: Signals And Systems"

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  +
 
= Signals and Systems =
  
= Signals and Systems =
  +
* '''Course name''': Signals and Systems
  +
* '''Code discipline''': XYZ
  +
* '''Subject area''': Electric Engineering
   
  +
== Short Description ==
−
* <span>'''Course name:'''</span> Signals and Systems
  
  +
This course covers the following concepts: discrete(-time) signals, their impulse and frequency domains; classification of (discrete) systems (bound-input-bound-output, linear and shift-invariant); filters and filtering, finite and infinite impulse response filters; discrete(-time) Fourier transform and fast Fourier transform.
−
* <span>'''Course number:'''</span> XYZ
  
−
* <span>'''Subject area:'''</span> Electric Engineering
  
   
−
== Course characteristics ==
 +
== Prerequisites ==
   
−
=== Key concepts of the class ===
 +
=== Prerequisite subjects ===
  +
* CSE202 — Analytical Geometry and Linear Algebra: complex numbers, vecrors and matrix operations, basis and basis decomposition, concept of eigen values and vectors.
  +
* CSE201 — Mathematical Analysis I: limits and absolutly summabale series, exponent function, besic integration.
  +
* CSE113 — Philosophy I - (Discrete Math and Logic): Algorithm time and space complexity.
   
  +
=== Prerequisite topics ===
−
* discrete(-time) signals, their impulse and frequency domains
  
−
* classification of (discrete) systems (bound-input-bound-output, linear and shift-invariant)
 
−
* filters and filtering, finite and infinite impulse response filters
 
−
* discrete(-time) Fourier transform and fast Fourier transform
  
   
−
=== What is the purpose of this course? ===
  
   
  +
== Course Topics ==
  +
{| class="wikitable"
  +
|+ Course Sections and Topics
  +
|-
  +
! Section !! Topics within the section
  +
|-
  +
| Complex numbers and functions, vector and Hilbert Spaces, computational aspects ||
  +
# Complex numbers and their matrix representation
  +
# Vector spaces with dot-product
  +
# Metrics and convergence, Hilbert spaces
  +
# Algorithms and their computational (space and time) complexity
  +
|-
  +
| Discrete Fourier Transform and Fast Fourier Transforms (DFT and FFT) ||
  +
# Circular convolution, eigen vectors and values of the circular convolution
  +
# Discrete Fourier Transform (DFT) and its inverse
  +
# Circutate filters and filtering
  +
# Fast Fourier Transform (FFT),its inverse, and computational aspects of DFT and fast FFT
  +
|-
  +
| Discrete-time signals and systems: properties and classification ||
  +
# Kotelnikov-Whittaker–Nyquist–Shannon sampling Theorem.
  +
# Discrete signals as sequences, spaces of absolutely summable and bounded sequences.
  +
# Auto- and cross-correlation; memoryless, causal and shift-invariant systems
  +
# Linear systems, their matrix representation and properties
  +
# Convolution and its relations to linear shift-invariant systems
  +
|-
  +
| Convolution, Discrete-time Fourier Transformation, filtering ||
  +
# Math preliminaries on complex exponent and Euler formulas.
  +
# Introduction of the discrete-time Fourier transform via convolution eigen values and vectors.
  +
# Discrete-time Fourier transform as the frequency response of a linear shift-invariant system.
  +
# Inverse discrete-time Fourier transform.
  +
# DTFT properties (including convolution theorem).
  +
# Elements of ideal Filter Design.
  +
|}
  +
== Intended Learning Outcomes (ILOs) ==
  +
  +
=== What is the main purpose of this course? ===
 
The goal of the course is to present mathematical foundations of digital signal processing altogether with practical experience to design finite and infinite impulse response filters. The course is aimed to provide basic mathematical knowledge and practical skills needed for further studies of applied signal processing and digital signal processing from engineering as well as from mathematical perspective.
  
The goal of the course is to present mathematical foundations of digital signal processing altogether with practical experience to design finite and infinite impulse response filters. The course is aimed to provide basic mathematical knowledge and practical skills needed for further studies of applied signal processing and digital signal processing from engineering as well as from mathematical perspective.
   
  +
=== ILOs defined at three levels ===
−
== Prerequisites ==
  
−  
−
* [https://eduwiki.innopolis.university/index.php/BSc:AnalyticGeometryAndLinearAlgebraI CSE202 — Analytical Geometry and Linear Algebra]: complex numbers, vecrors and matrix operations, basis and basis decomposition, concept of eigen values and vectors.
 
−
* [https://eduwiki.innopolis.university/index.php/BSc:MathematicalAnalysisI CSE201 — Mathematical Analysis I]: limits and absolutly summabale series, exponent function, besic integration.
 
−
* [https://eduwiki.innopolis.university/index.php/BSc:Logic_and_Discrete_Mathematics CSE113 — Philosophy I - (Discrete Math and Logic)]: Algorithm time and space complexity.
  
−  
−
== Course Objectives Based on Bloom’s Taxonomy ==
  
−  
−
=== What should a student remember at the end of the course? ===
  
   
  +
==== Level 1: What concepts should a student know/remember/explain? ====
  +
By the end of the course, the students should be able to ...
 
* discrete (time) signals and systems, their classification
  
* discrete (time) signals and systems, their classification
 
* linear shift-invariant systems, filters and filtering
  
* linear shift-invariant systems, filters and filtering
Line 34: Line 66:
 
* Discrete-Time Fourier Transformation (DTFT),
  
* Discrete-Time Fourier Transformation (DTFT),
   
−
=== What should a student be able to understand at the end of the course? ===
 +
==== Level 2: What basic practical skills should a student be able to perform? ====
  +
By the end of the course, the students should be able to ...
−  
 
* relations between analog and digital signals (sampling)
  
* relations between analog and digital signals (sampling)
−
* relations between convolution, correlation, and filtering of discrete signals
+
* relations between convolution, correlation, and filtering of discrete signals
 
* role of impulse and frequency domains of discrete signals
  
* role of impulse and frequency domains of discrete signals
 
* differences between infinite and finite discrete signals
  
* differences between infinite and finite discrete signals
Line 43: Line 75:
 
* role of discrete Fourier transform (DFT) and fast DFT (FFT)
  
* role of discrete Fourier transform (DFT) and fast DFT (FFT)
   
−
=== What should a student be able to apply at the end of the course? ===
 +
==== Level 3: What complex comprehensive skills should a student be able to apply in real-life scenarios? ====
  +
By the end of the course, the students should be able to ...
−  
 
* basic numerical tools from mathematical package SciLab/Octave
  
* basic numerical tools from mathematical package SciLab/Octave
 
* classify discrete signals and systems
  
* classify discrete signals and systems
 
* design and implement infinite and finite impulse response filters
  
* design and implement infinite and finite impulse response filters
 
* implement and use discrete time Fourier transform,
  
* implement and use discrete time Fourier transform,
−
* implement and use discrete Fourier transform and fast DFT.
 +
* implement and use discrete Fourier transform and fast DFT.
  +
== Grading ==
   
−
=== Course evaluation ===
 +
=== Course grading range ===
  +
{| class="wikitable"
−  
−
{|
 +
|+
  +
|-
−
|+ Course grade breakdown
  
  +
! Grade !! Range !! Description of performance
−
!
  
  +
|-
−
!
  
  +
| A. Excellent || 104-130 || -
−
!align="center"| '''Proposed points'''
  
 
|-
  
|-
  +
| B. Good || 84-103 || -
−
| Labs/seminar classes
  
−
| 20
  
−
|align="center"| 20
  
 
|-
  
|-
  +
| C. Satisfactory || 65-83 || -
−
| Interim performance assessment
  
−
| 30
  
−
|align="center"| 90
  
 
|-
  
|-
  +
| D. Poor || 0-64 || -
−
| Exams
  
−
| 50
  
−
|align="center"| 20
  
 
|}
  
|}
   
  +
=== Course activities and grading breakdown ===
−
If necessary, please indicate freely your course’s features in terms of students’ performance assessment:
  
  +
{| class="wikitable"
−  
  +
|+
−
==== Labs/seminar classes: ====
  
−  
−
* In-class participation 1 point for each individual contribution in a class but not more than 1 point a week (i.e. 14 points in total for 14 study weeks),
  
−
* overall course contribution (to accumulate extra-class activities valuable to the course progress, e.g. a short presentation, book review, very active in-class participation, etc.) up to 6 points.
  
−  
−
==== Interim performance assessment: ====
  
−  
−
* Each of 4 home-made individual lab (computational) assignments costs 15 points (i.e. 60 points for all 4 assignments).
  
−
* Each of 3 home-made individual written theory tests cost 10 points (i.e. 30 points for all 3 tests).
  
−  
−
==== Exam: ====
  
−  
−
* final examination costs 20 points.
  
−  
−
==== Overall score: ====
  
−  
−
130 points (100%).
  
−  
−
=== Grades range ===
  
−  
−
{|
  
−
|+ Course grading range
  
−
!
  
−
!
  
−
!align="center"| '''Proposed range'''
  
 
|-
  
|-
  +
! Activity Type !! Percentage of the overall course grade
−
| A. Excellent
  
−
| 80-100
  
−
|align="center"| 104-130
  
 
|-
  
|-
  +
| Labs/seminar classes || 20
−
| B. Good
  
−
| 65-79
  
−
|align="center"| 84-103
  
 
|-
  
|-
  +
| Interim performance assessment || 90
−
| C. Satisfactory
  
−
| 50-64
  
−
|align="center"| 65-83
  
 
|-
  
|-
−
| D. Poor
 +
| Exams || 20
−
| 0-49
  
−
|align="center"| 0-64
  
 
|}
  
|}
   
  +
=== Recommendations for students on how to succeed in the course ===
−
If necessary, please indicate freely your course’s grading features:
  
   
−
* A: at least 80% of the overall score;
  
−
* B: at least 65% of the overall score;
  
−
* C: at least 50% of the overall score;
  
−
* D: less than 50% of the overall score.
  
   
−
=== Resources and reference material ===
 +
== Resources, literature and reference materials ==
−  
−
==== Textbook: ====
  
   
  +
=== Open access resources ===
 
* Martin Vetterli, Jelena Kovacevic, and Vivek K Goyal.Foundations of Signal Processing.Cambridge University Press, 2014. ISBN 10703860X
  
* Martin Vetterli, Jelena Kovacevic, and Vivek K Goyal.Foundations of Signal Processing.Cambridge University Press, 2014. ISBN 10703860X
−  
−
==== Reference material: ====
  
−  
 
* Oppenheim, Alan V., and A. S. Willsky. Signals and Systems (2nd ed.) Prentice Hall, 1996. ISBN 0-13-814757-4.
  
* Oppenheim, Alan V., and A. S. Willsky. Signals and Systems (2nd ed.) Prentice Hall, 1996. ISBN 0-13-814757-4.
 
* Richard G. Lyons.UnderstandingDigitalSignalProcessing. Prentice Hall, 2010. ISBN 978-0137027415
  
* Richard G. Lyons.UnderstandingDigitalSignalProcessing. Prentice Hall, 2010. ISBN 978-0137027415
−
*
  
   
−
== Course Sections ==
 +
=== Closed access resources ===
   
−
The main sections of the course and approximate hour distribution between them is as follows:
  
   
  +
=== Software and tools used within the course ===
−
{|
  
  +
−
|+ Course Sections
  
  +
= Teaching Methodology: Methods, techniques, & activities =
−
|align="center"| '''Section'''
  
  +
−
| '''Section Title'''
  
  +
== Activities and Teaching Methods ==
−
|align="center"| '''Lectures'''
  
  +
{| class="wikitable"
−
|align="center"| '''Seminars'''
  
  +
|+ Activities within each section
−
|align="center"| '''Self-study'''
  
−
|align="center"| '''Knowledge'''
  
 
|-
  
|-
  +
! Learning Activities !! Section 1 !! Section 2 !! Section 3 !! Section 4
−
|align="center"| '''Number'''
  
−
|
  
−
|align="center"| '''(hours)'''
  
−
|align="center"| '''(labs)'''
  
−
|align="center"|
  
−
|align="center"| '''evaluation'''
  
 
|-
  
|-
  +
| Homework and group projects || 1 || 1 || 1 || 1
−
|align="center"| 1
  
−
| Complex numbers and functions, vector and Hilbert Spaces, computational aspects
 
−
|align="center"| 4
  
−
|align="center"| 4
  
−
|align="center"| 4
  
−
|align="center"| 1
  
 
|-
  
|-
  +
| Testing (written or computer based) || 1 || 0 || 0 || 0
−
|align="center"| 2
  
−
| Discrete Fourier Transform and Fast Fourier Transforms (DFT and FFT)
  
−
|align="center"| 6
  
−
|align="center"| 6
  
−
|align="center"| 6
  
−
|align="center"| 2
  
 
|-
  
|-
  +
| Reports || 1 || 1 || 1 || 1
−
|align="center"| 3
  
−
| Discrete-time signals and systems: properties and classification
  
−
|align="center"| 6
  
−
|align="center"| 6
  
−
|align="center"| 6
  
−
|align="center"| 2
  
 
|-
  
|-
  +
| Discussions || 1 || 1 || 1 || 1
−
|align="center"| 4
  
−
| Convolution, Discrete-time Fourier Transformation, filtering
 
−
|align="center"| 6
  
−
|align="center"| 6
  
−
|align="center"| 6
  
−
|align="center"| 2
  
 
|-
  
|-
  +
| Development of individual parts of software product code || 0 || 1 || 1 || 1
−
|align="center"| Final examination
  
−
|
 +
|-
  +
| Midterm evaluation || 0 || 1 || 1 || 1
−
|align="center"|
  
  +
|}
−
|align="center"|
  
  +
== Formative Assessment and Course Activities ==
−
|align="center"|
  
−
|align="center"| 2
  
−
|}
  
−  
−
=== Section 1 ===
  
−  
−
==== Section title: ====
  
−  
−
Complex numbers and functions, vector and Hilbert Spaces, computational aspects
  
−  
−
=== Topics covered in this section: ===
  
−  
−
* Complex numbers and their matrix representation
  
−
* Vector spaces with dot-product
  
−
* Metrics and convergence, Hilbert spaces
  
−
* Algorithms and their computational (space and time) complexity
  
   
−
=== What forms of evaluation were used to test students’ performance in this section? ===
 +
=== Ongoing performance assessment ===
   
  +
==== Section 1 ====
−
{|
  
  +
{| class="wikitable"
−
!
  
  +
|+
−
!align="center"| '''Yes/No'''
  
 
|-
  
|-
  +
! Activity Type !! Content !! Is Graded?
−
| Development of individual parts of software product code
  
−
|align="center"| 0
  
 
|-
  
|-
  +
| Question || Prove that each complex number has a square root. || 1
−
| Homework and group projects
  
−
|align="center"| 1
  
 
|-
  
|-
  +
| Question || Prove that the neutral element is unique in a vector space. || 1
−
| Midterm evaluation
  
−
|align="center"| 0
  
 
|-
  
|-
  +
| Question || Prove that pixel (Manhattan) and Euclidean norms are equivalent in finite-dimensional real (complex) spaces. || 1
−
| Testing (written or computer based)
  
−
|align="center"| 1
  
 
|-
  
|-
  +
| Question || Is the set of integers complete in the discrete metrics? || 1
−
| Reports
  
−
|align="center"| 1
  
 
|-
  
|-
  +
| Question || What is space and time complexity of dot product in a complex n-dimensional vector space? || 1
−
| Essays
  
−
|align="center"| 0
  
 
|-
  
|-
  +
| Question || Prove that each complex number but zero has the inverse. || 0
−
| Oral polls
  
−
|align="center"| 0
  
 
|-
  
|-
  +
| Question || Prove that each vector of a vector space has unique opposite element. || 0
−
| Discussions
  
−
|align="center"| 1
  
−
|}
  
−  
−  
−
</div>
  
−  
−
=== Typical questions for ongoing performance evaluation within this section ===
  
−  
−
# Prove that each complex number has a square root.
  
−
# Prove that the neutral element is unique in a vector space.
  
−
# Prove that pixel (Manhattan) and Euclidean norms are equivalent in finite-dimensional real (complex) spaces.
  
−
# Is the set of integers complete in the discrete metrics?
  
−
# What is space and time complexity of dot product in a complex n-dimensional vector space?
  
−  
−
=== Typical questions for seminar classes (labs) within this section ===
  
−  
−
# Prove that each complex number but zero has the inverse.
  
−
# Prove that each vector of a vector space has unique opposite element.
  
−
# Prove that pixel and the universal norms are equivalent in finite-dimensional real(complex) spaces.
  
−
# Is the set of rational numbers complete in the discrete metrics?
  
−
# What is space and time complexity of finite matrices multiplication (according to the definition)?
  
−  
−
=== Test questions for final assessment in this section ===
  
−  
−
(TBD)
  
−
# Build if possible (or prove that it isn’t) ...
  
−  
−
=== Section 2 ===
  
−  
−
==== Section title: ====
  
−  
−
Discrete Fourier Transform and Fast Fourier Transforms (DFT and FFT)
  
−  
−
=== Topics covered in this section: ===
  
−  
−
* Circular convolution, eigen vectors and values of the circular convolution
  
−
* Discrete Fourier Transform (DFT) and its inverse
  
−
* Circutate filters and filtering
  
−
* Fast Fourier Transform (FFT),its inverse, and computational aspects of DFT and fast FFT
  
−  
−
=== What forms of evaluation were used to test students’ performance in this section? ===
  
−  
−
{|
  
−
!
  
−
!align="center"| '''Yes/No'''
  
 
|-
  
|-
  +
| Question || Prove that pixel and the universal norms are equivalent in finite-dimensional real(complex) spaces. || 0
−
| Development of individual parts of software product code
  
−
|align="center"| 1
  
 
|-
  
|-
  +
| Question || Is the set of rational numbers complete in the discrete metrics? || 0
−
| Homework and group projects
  
−
|align="center"| 1
  
 
|-
  
|-
  +
| Question || What is space and time complexity of finite matrices multiplication (according to the definition)? || 0
−
| Midterm evaluation
  
  +
|}
−
|align="center"| 1
  
  +
==== Section 2 ====
  +
{| class="wikitable"
  +
|+
 
|-
  
|-
  +
! Activity Type !! Content !! Is Graded?
−
| Testing (written or computer based)
  
−
|align="center"| 0
  
 
|-
  
|-
  +
| Question || Compute circular convolution of given two short integer signals. || 1
−
| Reports
  
−
|align="center"| 1
  
 
|-
  
|-
  +
| Question || Explain Discrete Fourier Transform as orthogonal vector decomposition. || 1
−
| Essays
  
−
|align="center"| 0
  
 
|-
  
|-
  +
| Question || Compute DFT and FFT for given short integer signal. || 1
−
| Oral polls
  
−
|align="center"| 0
  
 
|-
  
|-
  +
| Question || Prove circular impulse shift property. || 0
−
| Discussions
  
−
|align="center"| 1
  
−
|}
  
−  
−
=== Typical questions for ongoing performance evaluation within this section ===
  
−  
−
# Compute circular convolution of given two short integer signals.
  
−
# Explain Discrete Fourier Transform as orthogonal vector decomposition.
 
−
# Compute DFT and FFT for given short integer signal.
  
−  
−
=== Typical questions for seminar classes (labs) within this section ===
  
−  
−
# Prove circular impulse shift property.
  
−
# Study commutativity, linearity and associativity of the circular convolution.
  
−
# Give matrix representation for the circular convolution for several small dimensions.
  
−
# Recall 2-redex fast Fourier transform and draw its matrices for several small dimensions.
  
−  
−
=== Test questions for final assessment in this section ===
  
−  
−
TBD
  
−  
−
# Assume that a finite signal ...
  
−  
−
=== Section 3 ===
  
−  
−
==== Section title: ====
  
−  
−
Discrete-time signals and systems: properties and classification
  
−  
−
=== Topics covered in this section: ===
  
−  
−
* Kotelnikov-Whittaker–Nyquist–Shannon sampling Theorem.
 
−
* Discrete signals as sequences, spaces of absolutely summable and bounded sequences.
  
−
* Auto- and cross-correlation; memoryless, causal and shift-invariant systems
  
−
* Linear systems, their matrix representation and properties
  
−
* Convolution and its relations to linear shift-invariant systems
  
−  
−
=== What forms of evaluation were used to test students’ performance in this section? ===
  
−  
−
{|
  
−
!
  
−
!align="center"| '''Yes/No'''
  
 
|-
  
|-
  +
| Question || Study commutativity, linearity and associativity of the circular convolution. || 0
−
| Development of individual parts of software product code
  
−
|align="center"| 1
  
 
|-
  
|-
  +
| Question || Give matrix representation for the circular convolution for several small dimensions. || 0
−
| Homework and group projects
  
−
|align="center"| 1
  
 
|-
  
|-
  +
| Question || Recall 2-redex fast Fourier transform and draw its matrices for several small dimensions. || 0
−
| Midterm evaluation
  
  +
|}
−
|align="center"| 1
  
  +
==== Section 3 ====
  +
{| class="wikitable"
  +
|+
 
|-
  
|-
  +
! Activity Type !! Content !! Is Graded?
−
| Testing (written or computer based)
  
−
|align="center"| 0
  
 
|-
  
|-
  +
| Question || Give examples of (infinite) absolutely summable/non-summable, bounded/unbounded,etc., signals. || 1
−
| Reports
  
−
|align="center"| 1
  
 
|-
  
|-
  +
| Question || Is autocorrelation linear system? Is it shift-invariant? || 1
−
| Essays
  
−
|align="center"| 0
  
 
|-
  
|-
  +
| Question || Prove that a linear system is memoryless iff its matrix is diagonal. || 1
−
| Oral polls
  
−
|align="center"| 0
  
 
|-
  
|-
  +
| Question || Prove that a linear system is causal iff its matrix is low-triangle. || 0
−
| Discussions
  
−
|align="center"| 1
  
−
|}
  
−  
−
=== Typical questions for ongoing performance evaluation within this section ===
  
−  
−
# Give examples of (infinite) absolutely summable/non-summable, bounded/unbounded,etc., signals.
 
−
# Is autocorrelation linear system? Is it shift-invariant?
  
−
# Prove that a linear system is memoryless iff its matrix is diagonal.
  
−  
−
=== Typical questions for seminar classes (labs) within this section ===
  
−  
−
# Prove that a linear system is causal iff its matrix is low-triangle.
  
−
# A linear system is shift-invariant iff its matrix consists (exclusively) of diagonals of some constant (individual for each diagonal).
  
−
# Prove that product of finite power series is convolution of the finite signals consisting of the coefficients of these series.
  
−  
−
=== Test questions for final assessment in this section ===
  
−  
−
TBD
  
−  
−
# Compute cross-correlation of two box signals.
  
−
# Study properties (linearity, causality, stability, etc.) of a weighted accumulator
  
−  
−
=== Section 4 ===
  
−  
−
==== Section title: ====
  
−  
−
Convolution, Discrete-time Fourier Transformation, filtering
  
−  
−
=== Topics covered in this section: ===
  
−  
−
* Math preliminaries on complex exponent and Euler formulas.
  
−
* Introduction of the discrete-time Fourier transform via convolution eigen values and vectors.
  
−
* Discrete-time Fourier transform as the frequency response of a linear shift-invariant system.
  
−
* Inverse discrete-time Fourier transform.
  
−
* DTFT properties (including convolution theorem).
  
−
* Elements of ideal Filter Design.
  
−  
−
=== What forms of evaluation were used to test students’ performance in this section? ===
  
−  
−
{|
  
−
!
  
−
!align="center"| '''Yes/No'''
  
 
|-
  
|-
  +
| Question || A linear system is shift-invariant iff its matrix consists (exclusively) of diagonals of some constant (individual for each diagonal). || 0
−
| Development of individual parts of software product code
  
−
|align="center"| 1
  
 
|-
  
|-
  +
| Question || Prove that product of finite power series is convolution of the finite signals consisting of the coefficients of these series. || 0
−
| Homework and group projects
  
  +
|}
−
|align="center"| 1
  
  +
==== Section 4 ====
  +
{| class="wikitable"
  +
|+
 
|-
  
|-
  +
! Activity Type !! Content !! Is Graded?
−
| Midterm evaluation
  
−
|align="center"| 1
  
 
|-
  
|-
  +
| Question || Do there exists a periodic function with non-commensurable periods? || 1
−
| Testing (written or computer based)
  
−
|align="center"| 0
  
 
|-
  
|-
  +
| Question || Prove that product of two exponents is equal to the exponent with sum of powers. || 1
−
| Reports
  
−
|align="center"| 1
  
 
|-
  
|-
  +
| Question || Prove conjugate property for DTFT. || 1
−
| Essays
  
−
|align="center"| 0
  
 
|-
  
|-
  +
| Question || Prove DTFT-correspondence for impulse shift. || 0
−
| Oral polls
  
−
|align="center"| 0
  
 
|-
  
|-
  +
| Question || Prove DTFT-correspondence for frequency shift. || 0
−
| Discussions
  
  +
|-
−
|align="center"| 1
  
  +
| Question || Design a low-band filter with a given spectrum consisting of a single box. || 0
−
|}
  
  +
|}
  +
=== Final assessment ===
  +
'''Section 1'''
  +
# Build if possible (or prove that it isn’t) ...
  +
'''Section 2'''
  +
# Assume that a finite signal ...
  +
'''Section 3'''
  +
# Compute cross-correlation of two box signals.
  +
# Study properties (linearity, causality, stability, etc.) of a weighted accumulator
  +
'''Section 4'''
  +
# Show that exponent with imaginary power is a periodic function, find the smallest period.
  +
# Prove sampling and scaling properties for the Dirac Delta function.
   
  +
=== The retake exam ===
−
=== Typical questions for ongoing performance evaluation within this section ===
  
  +
'''Section 1'''
   
  +
'''Section 2'''
−
# Do there exists a periodic function with non-commensurable periods?
  
−
# Prove that product of two exponents is equal to the exponent with sum of powers.
  
−
# Prove conjugate property for DTFT.
  
   
  +
'''Section 3'''
−
=== Typical questions for seminar classes (labs) within this section ===
  
   
  +
'''Section 4'''
−
# Prove DTFT-correspondence for impulse shift.
  
−
# Prove DTFT-correspondence for frequency shift.
  
−
# Design a low-band filter with a given spectrum consisting of a single box.
  
−  
−
=== Test questions for final assessment in this section ===
  
−  
−
TBD
  
−  
−
# Show that exponent with imaginary power is a periodic function, find the smallest period.
  
−
# Prove sampling and scaling properties for the Dirac Delta function.
  

Revision as of 12:58, 12 July 2022

Signals and Systems

  • Course name: Signals and Systems
  • Code discipline: XYZ
  • Subject area: Electric Engineering

Short Description

This course covers the following concepts: discrete(-time) signals, their impulse and frequency domains; classification of (discrete) systems (bound-input-bound-output, linear and shift-invariant); filters and filtering, finite and infinite impulse response filters; discrete(-time) Fourier transform and fast Fourier transform.

Prerequisites

Prerequisite subjects

  • CSE202 — Analytical Geometry and Linear Algebra: complex numbers, vecrors and matrix operations, basis and basis decomposition, concept of eigen values and vectors.
  • CSE201 — Mathematical Analysis I: limits and absolutly summabale series, exponent function, besic integration.
  • CSE113 — Philosophy I - (Discrete Math and Logic): Algorithm time and space complexity.

Prerequisite topics

Course Topics

Course Sections and Topics
Section Topics within the section
Complex numbers and functions, vector and Hilbert Spaces, computational aspects
  1. Complex numbers and their matrix representation
  2. Vector spaces with dot-product
  3. Metrics and convergence, Hilbert spaces
  4. Algorithms and their computational (space and time) complexity
Discrete Fourier Transform and Fast Fourier Transforms (DFT and FFT)
  1. Circular convolution, eigen vectors and values of the circular convolution
  2. Discrete Fourier Transform (DFT) and its inverse
  3. Circutate filters and filtering
  4. Fast Fourier Transform (FFT),its inverse, and computational aspects of DFT and fast FFT
Discrete-time signals and systems: properties and classification
  1. Kotelnikov-Whittaker–Nyquist–Shannon sampling Theorem.
  2. Discrete signals as sequences, spaces of absolutely summable and bounded sequences.
  3. Auto- and cross-correlation; memoryless, causal and shift-invariant systems
  4. Linear systems, their matrix representation and properties
  5. Convolution and its relations to linear shift-invariant systems
Convolution, Discrete-time Fourier Transformation, filtering
  1. Math preliminaries on complex exponent and Euler formulas.
  2. Introduction of the discrete-time Fourier transform via convolution eigen values and vectors.
  3. Discrete-time Fourier transform as the frequency response of a linear shift-invariant system.
  4. Inverse discrete-time Fourier transform.
  5. DTFT properties (including convolution theorem).
  6. Elements of ideal Filter Design.

Intended Learning Outcomes (ILOs)

What is the main purpose of this course?

The goal of the course is to present mathematical foundations of digital signal processing altogether with practical experience to design finite and infinite impulse response filters. The course is aimed to provide basic mathematical knowledge and practical skills needed for further studies of applied signal processing and digital signal processing from engineering as well as from mathematical perspective.

ILOs defined at three levels

Level 1: What concepts should a student know/remember/explain?

By the end of the course, the students should be able to ...

  • discrete (time) signals and systems, their classification
  • linear shift-invariant systems, filters and filtering
  • Discrete Fourier Transformation (DFT)
  • Fast discrete Fourier Transformation (FFT)
  • Discrete-Time Fourier Transformation (DTFT),

Level 2: What basic practical skills should a student be able to perform?

By the end of the course, the students should be able to ...

  • relations between analog and digital signals (sampling)
  • relations between convolution, correlation, and filtering of discrete signals
  • role of impulse and frequency domains of discrete signals
  • differences between infinite and finite discrete signals
  • role of discrete time Fourier transform and its inverse
  • role of discrete Fourier transform (DFT) and fast DFT (FFT)

Level 3: What complex comprehensive skills should a student be able to apply in real-life scenarios?

By the end of the course, the students should be able to ...

  • basic numerical tools from mathematical package SciLab/Octave
  • classify discrete signals and systems
  • design and implement infinite and finite impulse response filters
  • implement and use discrete time Fourier transform,
  • implement and use discrete Fourier transform and fast DFT.

Grading

Course grading range

Grade Range Description of performance
A. Excellent 104-130 -
B. Good 84-103 -
C. Satisfactory 65-83 -
D. Poor 0-64 -

Course activities and grading breakdown

Activity Type Percentage of the overall course grade
Labs/seminar classes 20
Interim performance assessment 90
Exams 20

Recommendations for students on how to succeed in the course

Resources, literature and reference materials

Open access resources

  • Martin Vetterli, Jelena Kovacevic, and Vivek K Goyal.Foundations of Signal Processing.Cambridge University Press, 2014. ISBN 10703860X
  • Oppenheim, Alan V., and A. S. Willsky. Signals and Systems (2nd ed.) Prentice Hall, 1996. ISBN 0-13-814757-4.
  • Richard G. Lyons.UnderstandingDigitalSignalProcessing. Prentice Hall, 2010. ISBN 978-0137027415

Closed access resources

Software and tools used within the course

Teaching Methodology: Methods, techniques, & activities

Activities and Teaching Methods

Activities within each section
Learning Activities Section 1 Section 2 Section 3 Section 4
Homework and group projects 1 1 1 1
Testing (written or computer based) 1 0 0 0
Reports 1 1 1 1
Discussions 1 1 1 1
Development of individual parts of software product code 0 1 1 1
Midterm evaluation 0 1 1 1

Formative Assessment and Course Activities

Ongoing performance assessment

Section 1

Activity Type Content Is Graded?
Question Prove that each complex number has a square root. 1
Question Prove that the neutral element is unique in a vector space. 1
Question Prove that pixel (Manhattan) and Euclidean norms are equivalent in finite-dimensional real (complex) spaces. 1
Question Is the set of integers complete in the discrete metrics? 1
Question What is space and time complexity of dot product in a complex n-dimensional vector space? 1
Question Prove that each complex number but zero has the inverse. 0
Question Prove that each vector of a vector space has unique opposite element. 0
Question Prove that pixel and the universal norms are equivalent in finite-dimensional real(complex) spaces. 0
Question Is the set of rational numbers complete in the discrete metrics? 0
Question What is space and time complexity of finite matrices multiplication (according to the definition)? 0

Section 2

Activity Type Content Is Graded?
Question Compute circular convolution of given two short integer signals. 1
Question Explain Discrete Fourier Transform as orthogonal vector decomposition. 1
Question Compute DFT and FFT for given short integer signal. 1
Question Prove circular impulse shift property. 0
Question Study commutativity, linearity and associativity of the circular convolution. 0
Question Give matrix representation for the circular convolution for several small dimensions. 0
Question Recall 2-redex fast Fourier transform and draw its matrices for several small dimensions. 0

Section 3

Activity Type Content Is Graded?
Question Give examples of (infinite) absolutely summable/non-summable, bounded/unbounded,etc., signals. 1
Question Is autocorrelation linear system? Is it shift-invariant? 1
Question Prove that a linear system is memoryless iff its matrix is diagonal. 1
Question Prove that a linear system is causal iff its matrix is low-triangle. 0
Question A linear system is shift-invariant iff its matrix consists (exclusively) of diagonals of some constant (individual for each diagonal). 0
Question Prove that product of finite power series is convolution of the finite signals consisting of the coefficients of these series. 0

Section 4

Activity Type Content Is Graded?
Question Do there exists a periodic function with non-commensurable periods? 1
Question Prove that product of two exponents is equal to the exponent with sum of powers. 1
Question Prove conjugate property for DTFT. 1
Question Prove DTFT-correspondence for impulse shift. 0
Question Prove DTFT-correspondence for frequency shift. 0
Question Design a low-band filter with a given spectrum consisting of a single box. 0

Final assessment

Section 1

  1. Build if possible (or prove that it isn’t) ...

Section 2

  1. Assume that a finite signal ...

Section 3

  1. Compute cross-correlation of two box signals.
  2. Study properties (linearity, causality, stability, etc.) of a weighted accumulator

Section 4

  1. Show that exponent with imaginary power is a periodic function, find the smallest period.
  2. Prove sampling and scaling properties for the Dirac Delta function.

The retake exam

Section 1

Section 2

Section 3

Section 4

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