Signals and System for unit 1

1. JENITON S
Assistant Professor
Department of ECE
KARPAGAM INSTITUTE OF
TECHNOLOGY

2.  Understand the operations and classifications
of signals & systems

3. Standard signals
 Step, Ramp, Pulse, Impulse, Real and complex
exponentials and Sinusoids
Classification of Signals
 Continuous time (CT) and Discrete Time (DT)
signals, Periodic & Aperiodic signals,
Deterministic & Random signals, Energy &
Power signals

4. Classification of systems:
 CT systems and DT systems – Linear &
Nonlinear, Time – variant & Time-invariant,
Causal & Non-causal, Stable & Unstable.

5.  Introduction of Signals
 Types of Signals
 Basic Standard signals
 Applications

6. Signals are mathematical function
 Dependent variable = voltage, temperature,
flow rate, pressure etc..
 Independent variable = time

7.  Based on dimension of signal
 1 Dimensional –Speech, ECG, EEG
 2 Dimensional –Image
 3 Dimensional –Colour Image, Video

8. Based on nature of signal
 Analog Signal
 Digital Signal
 Continuous Time Signal (CT)
 Discrete Time Signal (DT)
Based on amplitude
 Based on time

9.  The amplitude of an analog signal can have
any value (including fractions) at any point in
time.
 Analog signal have infinite values.

10.  The amplitude of signal can have only finite
and discrete values
 The special case of Digital signal having two
discrete values is known as Binary signal

11.  All continuous (Analog) signals that are
functions of time are continuous - time but not
all continuous-time signals are
continuous(Analog)

12.  Signal that has a value for only specific points in
time (Finite ,real valued)
 Typically formed by “sampling” a continuous-
time signal
 Represented as x(n). Also called as sequence
 Commonly found in all Computational systems
(digital world)
 ex. Audio signal mp3, Image JPEG
 Displayed graphically as individual values
 Called a “stem” plot

13.  Discrete-time signals are often obtained by
sampling continuous-time signals

16.  Heaviside function
 Represented by U(t) and U(n)
 t is a Power signal
 Neither Even signal nor Odd signal
Application:
 DC Generator(Switching on and off of a
device)
 Communication application

18.  Represented by r(t) and r(n)
 Neither Even nor odd signal
 Neither Energy nor power signal
Application:
 Current andVoltage relation circuits

20.  Deltafunction
 CT -Dirac delta function
 DT-Kronecker delta function
 Unit Area signal
 Even Signal
 Neither Energy nor Power signal
Application
 Thunderbolt
 ECG function

24.  Acceleration function Represented as p(t) and
p(n)
Application:
 The Bike responds to acceleration

25.  Smooth
 •Finite power signal.
 •Violates none of our criteria for real-world
signals.
Application:
 Any sound signal
 The light signal
 A tornedo – Complex sinusoidal signal

27.  Sine Cardinal function
 Normalized Sinc function
 Represented by sinc(t)
 Energy Signal
APPLICATION
 Digital Signal Processing
 Information Theory