DIGITAL SIGNAL PROCESSING
Lecture 1
(Article 1.1, 1.2, 1.p3)
BOOKS
Text Book : Digital Signal Processing: Principles, Algorithms and
Applications (Fourth Edition), John G. Proakis, Dimitris G. Manolakis
Reference Book: Discrete Time Signal Processing (Second Edition), Alan
V. Oppenheim, Ronald W. Schafer
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WHY DSP
Rapid development, significant advances of digital computer technology and
IC fabrication
Advantage over analog processing?
̶ Less expensive
̶ Reliable
̶ Programmable/Flexible
̶ Accuracy/Higher precision available
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APPLICATIONS OF DSP
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SIGNALS, SYSTEMS & SIGNAL PROCESSING
-Signal
-System
-Signal Processing
-Digital Processing of analog signals
­ Finite Precision effects
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1.2 CLASSIFICATION OF SIGNALS
Continuous Time vs Discrete Time
Continuous Valued vs Discrete Valued
Deterministic vs Random
Multichannel vs Multidimensional
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MULTICHANNEL VS MULTIDIMENSIONAL
Example multichannel
signals:
¨
ECG
¨
EEG
¨
stereo audio
¨
stereo cameras
(vision)
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1.3.1 CONCEPT OF FREQUENCY IN CT SIGNALS
¨
The CT sinusoid can be defined as
"! !# " = A #$%!"# + ! "&&&&&&&&&&&&&&&&& # $ < # < $
¨
¨
Three parameters: A is the amplitude, Ω is the frequency in rad/s and θ is the
phase in radians.
The frequency in rad/s is related to F (Hz) as: " = !! !
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PROPERTIES OF ANALOG SINUSOIDS
For every fixed value of F, xa(t) is periodic
Continuous-time sinusoidal signals with distinct (different) frequencies are
themselves distinct.
Increasing the frequency F results in an increase in the rate if oscillation of the
signal , in the sense that more cycles are included in the given time interval
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