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ABET Course Objectives and Outcomes Form

Course number and title: EE113 Digital Signal Processing
Credits: 4
Instructor(s)-in-charge: A. Alwan (alwan@ee.ucla.edu)
  M. van der Schaar (mihaela@ee.ucla.edu)
Course type: Lecture
Required or Elective: Required.
Course Schedule:
Lecture: 4 hrs/week. Meets twice weekly.
Dicussion: 1 hr/discussion section. Multiple discussion sections offered per quarter.
Outside Study: 9 hrs/week.
Office Hours: 2 hrs/week by instructor. 2 hrs/week by each teaching assistant.
 
Course Assessment:
Homework: 7-8 assignments
Exams: 1 midterm and 1 final examination.
Design: Matlab-based design project/online experimentation.
 
Grading Policy: Typically 10% design, 20% homework, 30% midterm, 40% final
Course Prerequisites: EE102
Catalog Description: Relationship between continuous-time and discrete-time signals. Z-transform. Discrete Fourier transform. Fast Fourier transform. Structures for digital filtering. Introduction to digital filter design techniques.  
Textbook and any related course material:
A. H. Sayed, Lecture Notes on Discrete-Time Signal Processing, available online on course website.
Interactive Digital Signal Processing Laboratory, http://www.ee.ucla.edu/~dsplab.
 
Course Website
Additional Course Website
Topics covered in the course and level of coverage:
Discrete-time signals and systems. 4 hrs.
Impulse response sequence & convolution. 3 hrs.
Difference equations, zero-state and zero-input solutions. 3 hrs.
One and two-sided z-transforms, partial fractions, transfer functions, block diagrams. 6 hrs.
Discrete-time Fourier transform, properties, and applications. 6 hrs.
Discrete-time Fourier transform, properties, and applications. 4 hrs.
Fast Fourier transform. 2 hrs.
Sampling theorem. 2 hrs.
Examples of applications of DSP (lectures and computer project). outside study
Course objectives and their relation to the Program Educational Objectives:  
Contribution of the course to the Professional Component:
Engineering Topics: 0 %
General Education: 0 %
Mathematics & Basic Sciences: 0 %
Expected level of proficiency from students entering the course:
Mathematics: Strong
Physics: Some
Chemistry: Not Applicable
Technical writing: Average
Computer Programming: Average
Material available to students and department at end of course:
  Available to
students
Available to
department
Available to
instructor
Available to
TA(s)
Course Objectives and Outcomes Form: X X X X
Lecture notes, homework assignments, and solutions: X X X X
Samples of homework solutions from 2 students: X
Samples of lab reports from 2 students: X
Samples of exam solutions from 2 students: X
Course performance form from student surveys: X X
Will this course involve computer assignments? YES Will this course have TA(s) when it is offered? YES

  Level of contribution of course to Program Outcomes
(a) Strong  
(b) Strong  
(c) Strong  
(g) Average  
(i) Average  
(k) Some  
(m) Some  
Strong: (a) (b) (c)
Average: (g) (i)
Some: (k) (m)

:: Upon completion of this course, students will have had an opportunity to learn about the following ::
  Specific Course Outcomes Program Outcomes
1. Plot discrete-time signals, evaluate their energy and power, check for periodicity, and evaluate the period of a signal. a
2. Identity properties of discrete-time systems such as time-invariance, stability, causality, and linearity. a m
3. Draw block diagrams of discrete-time systems. c
4. Solve constant-coefficient difference equations and identify their modes. a m
5. Determine the zero-input and zero-state responses of systems described by constant-coefficient difference equations, and use the superposition principle to determine the complete response of such systems. a m
6. Compute the linear and circular convolutions of discrete-time sequences. a
7. Evaluate the discrete-time Fourier transform (DTFT) of a sequence. a
8. Evaluate and plot the frequency (magnitude and phase) response of linear time-invariant systems, and identify all-pass and minimum phase systems. a
9. Evaluate the discrete Fourier transform (DFT) of a sequence, relate it to the DTFT, and use the DFT to compute the linear convolution of two sequences. a
10. Compute the z-transform of a sequence, identify its region of convergence, and compute the inverse z-transform by partial fractions. a
11. Use the z-transform to evaluate the transfer function of linear time-invariant systems and to identify the corresponding zeros and poles. a m
12. Use the z-transform to determine difference equations from transfer function descriptions. a m
13. Use the z-transform to solve constant-coefficient difference equations with initial conditions. a
14. Use Nyquist sampling theorem to choose adequate sampling rates and to understand aliasing. a c
15. Opportunity to conduct matlab-based project(s) requiring some independent reading, programming, simulations, and technical writing. b c g
16. Explain how Digital Signal Processing concepts are used in some selected applications in lecture and through the computer project. a c k
17. Several homework assignments delving on core concepts and reinforcing analytical skills learned in class. a i m
18. Opportunities to interact weekly with the instructor and the teaching assistant(s) during regular office hours and discussion sections in order to further the students' learning experience and the students' interest in the material. i

  Program outcomes and how they are covered by the specific course outcomes
(a)   Plot discrete-time signals, evaluate their energy and power, check for periodicity, and evaluate the period of a signal.  
  Identity properties of discrete-time systems such as time-invariance, stability, causality, and linearity.  
  Solve constant-coefficient difference equations and identify their modes.  
  Determine the zero-input and zero-state responses of systems described by constant-coefficient difference equations, and use the superposition principle to determine the complete response of such systems.  
  Compute the linear and circular convolutions of discrete-time sequences.  
  Evaluate the discrete-time Fourier transform (DTFT) of a sequence.  
  Evaluate and plot the frequency (magnitude and phase) response of linear time-invariant systems, and identify all-pass and minimum phase systems.  
  Evaluate the discrete Fourier transform (DFT) of a sequence, relate it to the DTFT, and use the DFT to compute the linear convolution of two sequences.  
  Compute the z-transform of a sequence, identify its region of convergence, and compute the inverse z-transform by partial fractions.  
  Use the z-transform to evaluate the transfer function of linear time-invariant systems and to identify the corresponding zeros and poles.  
  Use the z-transform to determine difference equations from transfer function descriptions.  
  Use the z-transform to solve constant-coefficient difference equations with initial conditions.  
  Use Nyquist sampling theorem to choose adequate sampling rates and to understand aliasing.  
  Explain how Digital Signal Processing concepts are used in some selected applications in lecture and through the computer project.  
  Several homework assignments delving on core concepts and reinforcing analytical skills learned in class.  
(b)   Opportunity to conduct matlab-based project(s) requiring some independent reading, programming, simulations, and technical writing.  
(c)   Draw block diagrams of discrete-time systems.  
  Use Nyquist sampling theorem to choose adequate sampling rates and to understand aliasing.  
  Opportunity to conduct matlab-based project(s) requiring some independent reading, programming, simulations, and technical writing.  
  Explain how Digital Signal Processing concepts are used in some selected applications in lecture and through the computer project.  
(g)   Opportunity to conduct matlab-based project(s) requiring some independent reading, programming, simulations, and technical writing.  
(i)   Several homework assignments delving on core concepts and reinforcing analytical skills learned in class.  
  Opportunities to interact weekly with the instructor and the teaching assistant(s) during regular office hours and discussion sections in order to further the students' learning experience and the students' interest in the material.  
(k)   Explain how Digital Signal Processing concepts are used in some selected applications in lecture and through the computer project.  
(m)   Identity properties of discrete-time systems such as time-invariance, stability, causality, and linearity.  
  Solve constant-coefficient difference equations and identify their modes.  
  Determine the zero-input and zero-state responses of systems described by constant-coefficient difference equations, and use the superposition principle to determine the complete response of such systems.  
  Use the z-transform to evaluate the transfer function of linear time-invariant systems and to identify the corresponding zeros and poles.  
  Use the z-transform to determine difference equations from transfer function descriptions.  
  Several homework assignments delving on core concepts and reinforcing analytical skills learned in class.  

:: Last modified: February 2013 by J. Lin ::

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