Prof. Brian L. Evans

1
Introduction
EE 313 Linear Systems and Signals
Fall 2010

• Prof. Brian L. Evans
• Dept. of Electrical and Computer Engineering
• The University of Texas at Austin

Initial conversion of content to PowerPointby
Dr. Wade C. Schwartzkopf
2
Coverage of Course

• Analysis of linear subsystems within control,
  communication, and signal processing systems
• Examples of electronic control systems?
• Antilock brakes
• Engine control
• Chemical processing plant
• Emerging trend brake by wire
• Examples of signal processing and communication
  systems?

3
Signal Processing Systems

• Speech and audio
• Speech compression (cell phones)
• Speech synthesis and recognition
• Audio CD players
• Audio compression AC3, MPEG 1 layer 3 audio
  (MP3)
• Image and video compression
• Image compression JPEG, JPEG 2000
• Video CDs MPEG 1
• DVD, digital cable, HDTV MPEG 2
• Wireless video MPEG 4/H.263,MPEG 4 Advanced
  Video Coding/H.264

Moving Picture Experts Group (MPEG)
Joint Picture Experts Group (JPEG)
4
Communication Systems

• Digital subscriber lines (DSL)
• Cable modems
• Cellular phones
• First generation (1G) Advanced Mobile Phone
  Service
• Second generation (2G) Global System for Mobile
  (GSM) and Interim Standard-95 (Code Division
  Multiple Access)
• Third generation (3G) cdma2000, Wideband CDMA
• Fourth generation (4G) Long Term Evolution,
  Wi-Max
• Local area wireless Internet access
• IEEE 802.11a, b, g, n, etc. (WiFi)

Analog
Digital
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Related BS ECE Technical Areas
Introduction

• Communication/networking
• EE345S Real-Time DSP Lab
• EE360K Digital Comm.
• EE371C Wireless Comm Lab
• EE372N Telecom. Networks
• EE379K-15 Info. Theory

• Signal/image processing
• EE345S Real-Time DSP Lab
• EE351M DSP (theory)
• EE371R Digital Image and Video Processing
• Embedded Systems
• EE345M Embedded and Real-Time Systems
• EE345S Real-Time DSP Lab
• EE360M Dig. Sys. Design
• EE360N Computer Arch.
• EE360R VLSI CAD

Spring
Fall
Fall
Spring
Spring
Spring
Undergraduates may request permission to take
grad courses
EE345S may be used for advanced laboratory
pre-requisite for senior design project.
6
Signals as Functions

• Function of an independent variable
• Temperature vs. time
• Closing value of a stock market vs. day
• Continuous-time signals
• x(t) where t can take any real value
• x(t) may be 0 for a given range of values of t
• Discrete-time signals
• xn where n ? ...-3,-2,-1,0,1,2,3...
• Sometimes use sample index instead of time
  for n
• Values for x may be real or complex

7
Analog vs. Digital Amplitude

• At each time value, analog signal amplitude takes
  real or complex value (a.k.a. continuous-valued)
• Digital signal amplitude takes values from a
  discrete set (a.k.a. discrete-valued)

Analog continuous-time signal
Digital continuous-time signal
1
-1
8
Deterministic vs. Random Signals

• Deterministic signal amplitudes
• Can be mathematically described, e.g. x(t)
  cos(2 p f0 t)
• Random signal amplitudes
• Cannot be predicted exactly
• Cannot be described by a mathematical function
• Distribution of amplitude values can be defined
• Consider flipping fair coin (uniform
  distribution)
• Let 1 be heads and -1 be tails

Matlab/Mathscript Code flipnumber 110 y
sign(randn(10,1)) stem(flipnumber, y)