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1 1) Signals 2) Systems 3) For example ... “Figures and images used in these lecture notes by permission, copyright 1997 by Alan V. Oppenheim and Alan S. Willsky” Introduction to Signal Processing Summer 2007 Basics: Signals and Systems Keyur Desai (Slides: Courtesy of Prof. Alan S. Willsky) 16 May 2007
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Signal Processing

Dec 24, 2015

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Tayab Memon

This is an introductory lecture on signal processing
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Page 1: Signal Processing

1

1) Signals

2) Systems

3) For example ...

“Figures and images used in these lecture notes by permission,copyright 1997 by Alan V. Oppenheim and Alan S. Willsky”

Introduction to Signal Processing Summer 2007

Basics: Signals and Systems

Keyur Desai (Slides: Courtesy of Prof. Alan S. Willsky)

16 May 2007

Page 2: Signal Processing

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SIGNALS

Signals are functions of independent variables that carry information. For example:

• Electrical signals --- voltages and currents in a circuit• Acoustic signals --- audio or speech signals (analog or

digital)

Spectrogram

Time-domainSpeech signal

Page 3: Signal Processing

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SIGNALS

• Video signals --- intensity variations in an image (e.g. a CAT scan)

• Biological signals --- sequence of bases in a gene

DNA

Its signal representation

Page 4: Signal Processing

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THE INDEPENDENT VARIABLES

• For electrical signal the value of voltage or current changes with time, hence time is called independent variable and voltage or current is called dependent variable

• Independent variable can be continuous— Trajectory of a space shuttle— Mass density in a cross-section of a brain

• Independent variable can be discrete— DNA base sequence— Digital image pixels

• Independent variable can be 1-D, 2-D, ••• N-D

Page 5: Signal Processing

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THE INDEPENDENT VARIABLES

What are the independent variables in these signals?

(i) Speech (ii) CAT scan image (iii) DNA sequence

(i) Time (ii) Spatial Location (iii) Location on DNA molecule

For this course: Focus on a single (1-D) independent variable which we call “time”.

Continuous-Time (CT) signals: x(t), t — continuous valuesDiscrete-Time (DT) signals: x[n], n — integer values only

Page 6: Signal Processing

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CT Signals

• Most of the signals in the physical world are CT signals—E.g. voltage & current, pressure, temperature, velocity, etc.

Page 7: Signal Processing

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DT Signals

• Examples of DT signals in nature:— DNA base sequence— Population of the nth generation of certain species

• x[n], n — integer, time varies discretely

Page 8: Signal Processing

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Many human-made DT Signals

Ex.#1 Weekly Dow-Jones

industrial average

Why DT? —Can be processed by modern digital computers

and digital signal processors (DSPs).

Ex.#2 digital image

Page 9: Signal Processing

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SYSTEMS

For the most part, our view of systems will be from an input-output perspective:

A system responds to applied input signals, and its response is described in terms of one or more output signals

x(t) y(t)CT System

DT Systemx[n] y[n]

Page 10: Signal Processing

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•An RLC circuit

•What is the input signal? • x(t) (the D.C. source)

•What is the output signal? • y(t) (the signal across capacitor)

•What is the system? • The whole RLC network

EXAMPLES OF SYSTEMS

Page 11: Signal Processing

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•Dynamics of an aircraft or space vehicle•An algorithm for analyzing financial and economic

factors to predict bond prices•An algorithm for post-flight analysis of a space launch•An edge detection algorithm for medical images

What are the inputs and what are the outputs in above examples?

EXAMPLES OF SYSTEMS

Page 12: Signal Processing

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SYSTEM INTERCONNECTIONS

•An important concept is that of interconnecting systems— To build more complex systems by interconnecting

simpler subsystems— To modify response of a system

•Signal flow (Block) diagram

Cascade

Feedback

Parallel +

+