The signal encapsulates information about the behaviour of a physical phenomenon, for example, electrical current flowing through a resistor, sonar sound waves propagating under water, or earthquakes.

1. SIGNALS
A signal is a function or a data set representing a physical
quantity or variable.
The signal encapsulates information about the behaviour of
a physical phenomenon, for example, electrical current
flowing through a resistor, sonar sound waves propagating
under water, or earthquakes.
EXAMPLE:
Music, video, voice, pictures, data and so forth are all
examples of signals to be transmitted and stored.

2. CLASSIFICATION OF SIGNALS

3. ANALOG AND DIGITAL SIGNAL
 ANALOG:
 Analog signal is a continuous signal which represents physical
measurements.
 Denoted by sine waves
 Uses continuous range of values to represent information
 Human voice in air, analog electronic devices.
 More likely to get affected reducing accuracy.
 Analog hardware is not flexible.
 Can be used in analog devices only. Best suited for audio and video
transmission.
 APPLICATION:Thermometer
 Analog signal processing can be done in real time and consumes
less bandwidth.
 Stored in the form of wave signal

4. ANALOG AND DIGITAL SIGNAL
DIGITAL :
 Digital signals are discrete time signals generated by digital
modulation
 Denoted by square waves
 Uses discrete or discontinuous values to represent information.
 Computers, CDs, DVDs, and other digital electronic devices.
 Samples analog waveforms into a limited set of numbers and
records them.
 Digital hardware is flexible in implementation.
 Application:PCs, PDAs
 There is no guarantee that digital signal processing can be
done in real time and consumes more bandwidth to carry out
the same information.
 Stored in the form of binary bit

5. Discrete signal
A discrete signal or discrete-time signal is a time
series consisting of a sequence of quantities.
Unlike a continuous-time signal, a discrete-time
signal is not a function of a continuous argument;
however, it may have been obtained by sampling
from a continuous-time signal.
This 7.5-second triangle wave segment has a
sample period of 0.5 seconds, and sample times
of 0.0, 0.5, 1.0, 1.5, ...,7.5. The sample rate of the
sequence is therefore 1/0.5, or 2 Hz.

6. DIGITAL SIGNAL PROCESSING
Digital signal processing:
Digital signal processing (DSP) is the process of analyzing
and modifying a signal to optimize or improve its efficiency
or performance.
It involves applying various mathematical and
computational algorithms to analog and digital signals to
produce a signal that's of higher quality than the original
signal.

8. TYPES OF SIGNALS
Signals are classified into the following
categories:
Continuous Time and Discrete Time Signals.
Deterministic and Non-deterministic Signals.
Even and Odd Signals.
Periodic and Aperiodic Signals.
Energy and Power Signals.
Real and Imaginary Signals.

9. TYPES OF SIGNALS
Continuous Time (CT) Signals
A continuous time signal is a function that is
continuous, meaning there are no breaks in
the signal. For all real values of t you will get a
value. f(t),t⊂R CT signals are ususally
represented by using x(t), having a
parentheses and the variable t.

10. CONT
Discrete Time Signals:
A discrete time signal is a signal whose value is
taken at discrete measurements. With a
discrete time signal there will be time periods
of n where you do not have a value. DT signals
are represented using the form x[n]. Discrete
signals are approximations of CT signals.

11. CONT
Deterministic and Non-deterministic Signals
 A signal is said to be deterministic if there is
no uncertainty with respect to its value at any
instant of time. Or, signals which can be
defined exactly by a mathematical formula are
known as deterministic signals.

12. CONT
• Non-deterministic signals are random in
nature hence they are called random signals.
Random signals cannot be described by a
mathematical equation. They are modelled in
probabilistic terms.

13. • Even and Odd Signals
• A signal is said to be even when it satisfies the
condition x(t) = x(-t)
• Example 1: t2, t4… cost etc.
• Let x(t) = t2
• x(-t) = (-t)2 = t2 = x(t)
• t2 is even function

14. CONT
• A signal is said to be odd when it satisfies the condition
x(t) = -x(-t)
• Example: t, t3 ... And sin t
• Let x(t) = sin t
• x(-t) = sin(-t) = -sin t = -x(t)
• sin t is odd function.
• Periodic and Aperiodic Signals
• A signal is said to be periodic if it satisfies the condition
x(t) = x(t + T) or x(n) = x(n + N).
• Where
• T = fundamental time period,
• 1/T = f = fundamental frequency.

15. • Energy and Power Signals
• A signal is said to be energy signal when it has finite energy.
• EnergyE=∫∞−∞x2(t)dtEnergyE=∫−∞∞x2(t)dt
• A signal is said to be power signal when it has finite power.
• PowerP=limT→∞12T∫T−Tx2(t)dtPowerP=limT→∞12T∫−TTx
2(t)dt
• NOTE:A signal cannot be both, energy and power
simultaneously. Also, a signal may be neither energy nor
power signal.
• Power of energy signal = 0
• Energy of power signal = ∞

16. Real and Imaginary Signals
• A signal is said to be real when it satisfies the
condition x(t) = x*(t)
• A signal is said to be odd when it satisfies the
condition x(t) = -x*(t)
• Example:
• If x(t)= 3 then x*(t)=3*=3 here x(t) is a real
signal.
• If x(t)= 3j then x*(t)=3j* = -3j = -x(t) hence x(t)
is a odd signal.