Outline
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Digital Signal Processing
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Overview of DSP
Classification of Signals
Representation of Signals
Typical Signal Processing Operations
Examples of Typical Signals
Typical Signal Processing Applications
Why Digital Signal Processing
Chapter 1: Signals and Signal Processing
Digital Signal Processing
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Overview of DSP
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Overview of DSP
Signals play an important role in our daily life.
A signal is a function of independent variables such as
time, distance, position, temperature, and pressure
A signal carries information
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Examples: speech, music, picture, and video signals
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The objective of signal processing is to extract the
useful information carried by the signal
Digital Signal Processing
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Method information extraction: Depends on the type of signal and
the nature of the information being carried by the signal
DSP is concerned with the mathematical representation of the
signal and the algorithmic operation carried out on it
Signals can be represented in the domain of the original
independent variables or in a transformed domain
Likewise, the information extraction process may be carried out in
the original domain of the signal or in a transformed domain
This course is concerned with the discrete-time representation of
signals and their discrete-time processing
Digital Signal Processing
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Classification of Signals
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Continuous / Discrete
Real / Complex
Scalar / Vector
One dimensional / Multi-Dimensional
Deterministic / Random
Classification of Signals
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Digital Signal Processing
Digital Signal Processing
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Classification of Signals
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Classification of Signals
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Digital Signal Processing
One-dimensional (1-D) signal:
• Function of a single independent variable,
e.g., speech signal, 𝑠(𝑡)
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Two-dimensional (2-D) signal:
• Function of two independent variables,
e.g., image, 𝑠(𝑥, 𝑦)
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Multidimensional signal:
• Black and white video signal is a 3-D signal, two spatial variables
and time,
i.e., 𝑣(𝑥, 𝑦, 𝑡)
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• Color video signal has three channels of 3-D signals (RGB),
 i.e., 𝑢(𝑥, 𝑦, 𝑡) = [𝑟(𝑥, 𝑦, 𝑡) 𝑔(𝑥, 𝑦, 𝑡) 𝑏(𝑥, 𝑦, 𝑡)]𝑇
Analog signal:
 Continuous in both time and amplitude
Digital signal:
 Discrete in both time and amplitude
Sampled-data signal:
 Discrete-time and continuous amplitude signal
Quantized boxcar signal:
 Continuous-time and discrete amplitude signal
Digital Signal Processing
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