Introduction to Signal Processing

(2-0-3-3)

CMPE Degree: This course is Elective for the CMPE degree.

EE Degree: This course is Required for the EE degree.

Lab Hours: 3 supervised lab hours and 0 unsupervised lab hours.

Technical Interest Groups / Course Categories: EE Common Core, Threads / ECE Electives

Course Coordinator: Ghassan AlRegib

Prerequisites: (MATH 1502 [min C] or (MATH 15X2 [min T] and (MATH 1522 [min C] or MATH 1553 [min C])) or MATH 1512 [min C] or (MATH 1552 [min C] and (MATH 1553 [min C] or MATH 1554 [min C] or MATH 1564 [min C]))) and (CS 1371 [min C] or CS 1171 [min D, with concurrency]

Catalog Description

Introduction to discrete-time signal processing and linear systems. Sampling theorem, filtering, frequency response, Discrete Fourier Transform, Z-Transform. Laboratory emphasizes computer-based signal processing.

Textbook(s)

Digital Signal Processing First

Course Outcomes

Express signal processing systems in mathematical form.

Write Matlab code describing a signal processing system.

Analyze signals in terms of their frequency content.

Describe system behavior in terms of impulse response and convolution.

Analyze linear system behavior in terms of Fourier transform and frequency response. 

Analyze mixed analog-digital systems with sampling operations and digital filters. 

Utilize the z-transform to analyze discrete-time systems in terms of poles and zeroes.

Use complex exponential notation to describe signals and systems. 

Describe how signal processing is used in applications (e.g., audio and image processing).

Strategic Performance Indicators (SPIs)

N/A

Topic List

  1. Discrete-Time Signals and Systems
    1. Sinusoids and Complex Amplitudes
    2. The Spectrum
  2. The Sampling Process
    1. Sampling Theorem
    2. Aliasing
  3. Digital Filters
    1. Finite-Impulse-Response (FIR) Filters
    2. Linearity and Time-Invariance: Convolution
    3. Frequency Response
    4. Infinite-Impulse-Response (IIR) Filters
    5. Relationship between Continuous-Time and Discrete-Time Frequency Domains
  4. Discrete Fourier Analysis
    1. DTFT: Discrete-Time Fourier Transform
    2. DFT: Discrete Fourier Transform
    3. DFS: Discrete Fourier Series
    4. Application: Spectrograms for Time-Frequency Analysis
  5. The Z-transform
    1. Zeros and Poles
    2. Three Domains: Relationship among Time, Frequency, and Z domains
  6. Lab Topics may include:
    1. Introduction to MATLAB
    2. Complex Exponentials and the Spectrum
    3. Music or Speech Synthesis with Sinusoids
    4. Image Processing: e.g. Edge Detection, De-blurring
    5. Bandpass Filtering: Touch-Tone Decoding
    6. Biomedical Applications: e.g. Hearing, Cochlear Implants, EKG.