Signals and classification
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SIGNALS AND SYSTEM
SURAJ MISHRA
SUMIT SINGH
AMIT GUPTA
PRATYUSH SINGH
(E.C 2ND YEAR ,MCSCET) 1
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Topics
Introduction Classification of Signals Some Useful Signal Operations Some useful signal models
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Introduction
The concepts of signals and systems arise in a wide variety of areas:communications, circuit design, biomedical engineering, power systems, speech processing, etc.
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What is a Signal?
SIGNAL A set of information or data. Function of one or more
independent variables. Contains information about the
behavior or nature of some phenomenon.
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Examples of Signals
BRAIN WAVE
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Examples of Signals
Stock Market data as signal (time series)
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What is a System?
SYSTEMSignals may be processed further
by systems, which may modify them or extract additional from them.
A system is an entity that processes a set of signals (inputs) to yield another set of signals (outputs).
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What is a System? (2)
A system may be made up of physical components, as in electrical or mechanical systems (hardware realization).
A system may be an algorithm that computes an outputs from an inputs signal (software realization).
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Examples of signals and systems
Voltage (x1) and current (x2) as functions of time in an electrical circuit are examples of signals.
A circuit is itself an example of a system (T), which responds to applied voltages and currents.
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Some Useful Signal Some Useful Signal ModelsModels
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Signal Models: Unit Step Function
Continuous-Time unit step function, u(t):
u(t) is used to start a signal, f(t) at t=0 f(t) has a value of ZERO for t <0
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Signal Models: Unit Impulse Function
A possible approximation to a unit impulse:An overall area that has been maintained at unity.
Multiplication of a function by an Impulse?
b(t) = 0; for all t0is an impulse function which the area is b.
Graphically, it is represented by an arrow "pointing to infinity" at t=0 with its length equal to its area.
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Signal Models: Unit Impulse Function (3)
May use functions other than a rectangular pulse. Here are three example functions:
Note that the area under the pulse function must be unity.
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Signal Models: Unit Ramp Function
Unit ramp function is defined by: r(t) = tu(t)
Where can it be used?
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Signal Models: Exponential Function est
Most important function in SNS where s is complex in general, s = +j
Therefore,est = e(+j)t = etejt = et(cost + jsint)(Euler’s formula: ejt = cost + jsint)
If s = -j, est = e(-j)t = ete-jt = et(cost - jsint)
From the above, etcost = ½(est +e-st )
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Signal Models: Exponential Function est (2)
Variable s is complex frequency. est = e(+j)t = etejt = et(cost + jsint)
est = e(-j)t = ete-jt = et(cost - jsint)etcost = ½(est +e-st )
There are special cases of est :1. A constant k = ke0t (s=0 =0,=0)
2. A monotonic exponential et (=0, s=)
3. A sinusoid cost (=0, s=j)
4. An exponentially varying sinusoid etcost (s= j)
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Signals Classification
Signals may be classified into: 1. Continuous-time and Discrete-time signals 2. Deterministic and Stochastic Signal 3. Periodic and Aperiodic signals 4. Even and Odd signals 5. Energy and Power signals
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Continuous v/S Discrete Signals
Continuous-timeA signal that is specified for everyvalue of time t.
Discrete-timeA signal that is specified only at discrete valuesof time t.
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Deterministic v/s Stochastic Signal
Signals that can be written in any mathematical expression are called deterministic signal.
(sine,cosine..etc) Signals that cann’t be written in mathematical
expression are called stochastic signals. (impulse,noise..etc)
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Periodic v/s Aperiodic Signals
Signals that repeat itself at a proper interval of time are called periodic signals.
Continuous-time signals are said to be periodic.
Signals that will never repeat themselves,and get over in limited time are called aperiodic or non-periodic signals.
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Even v/s Odd Signals
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Even v/s Odd Signals
A signal x(t) or x[n] is referred to as an even signal if CT: DT:
A signal x(t) or x[n] is referred to as an odd signal if CT: DT:
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Even and Odd Functions: Properties
Property:
Area: Even signal:
Odd signal:
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Even and Odd Components of a Signal (1)
Every signal f(t) can be expressed as a sum of even and odd components because
Example, f(t) = e-atu(t)
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Signal with finite energy (zero power)
Signal with finite power (infinite energy)
Signals that satisfy neither property are referred as neither energy nor power signals
Energy v/s Power Signals
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Size of a Signal, Energy (Joules)
Measured by signal energy Ex:
Generalize for a complex valued signal to: CT: DT:
Energy must be finite, which means
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Size of a Signal, Power (Watts)
If amplitude of x(t) does not → 0 when t → ∞, need to measure power Px instead:
Again, generalize for a complex valued signal to: CT:
DT:
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OPERATIONS ON SIGNALS
It includes the transformation of independent variables.
It is performed in both continuous and discrete time signals.
Operations that are performed are-
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1.ADDITION &SUBSTRACTION
Let two signals x(t) and y(t) are given, Their addition will be,
z(t) = x(t) + y(t)
Their substraction will be,
z(t) = x(t) – y(t)
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2.MULTIPLICATION OF SIGNAL BY A CONSTANT
If a constant ‘A’ is given with a signal x(t)
z(t) = A.x(t)
If A>1,it is an amplified signal. If A<1,it is an attenuated signal.
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3.MULTIPLICATION OF TWO SIGNALS
If two signals x(t) and y(t) are given,than their multiplication will be
z(t) = x(t).y(t)
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4.SHIFTING IN TIME
Let a signal x(t),than the signal x(t-T) represented a delayed version of x(t),which is delayed by T sec.
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Signal Operations: Time Shifting
Shifting of a signal in time adding or subtracting the amount of the
shift to the time variable in the function. x(t) x(t–to)
to > 0 (to is positive value),signal is shifted to the right (delay).
to < 0 (to is negative value),signal is shifted to the left (advance).
x(t–2)? x(t) is delayed by 2 seconds. x(t+2)? x(t) is advanced by 2 seconds.
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Signal Operations: Time Shifting (2)
Subtracting a fixed amount from the time variable will shift the signal to the right that amount.
Adding to the time variable will shift the signal to the left.
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Signal Operations: Time Shifting
Shifting of a signal in time
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5.COMPRESSION/EXPANSION OF SIGNALS
This is also known as ‘Time Scaling’ process. Let a signal x(t) is given,we will examine as
x(at)
where a =real number and how it is related to x(t) ?
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Time Scaling
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Signal Operations: Time Inversion
Reversal of the time axis, or folding/flipping the signal (mirror image) over the y-axis.
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THANKS....................... FOR YOUR
ATTENTION !
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