1.basics of signals
TRANSCRIPT
Signals and Systems
Prof. Satheesh Monikandan.BHOD-ECE
INDIAN NAVAL ACADEMY, EZHIMALA
92 INAC-L-AT15
• Course Code : ECL427 • Course title : SIGNALAS AND SYSTEMS• Credit Hours : 3
• Semester : AT2015
• Refernece Book : A.V.Oppenheim, A.V.Willsky and
S.Hamid Nawab, “Signals and Systems,” PHI, 2nd Edition, 2013.
Syllabus - I• Introduction to Signals• Spectral Analysis
– Fourier Series– Fourier Transform– Frequency Domain Representation of Finite Energy
Signals and Periodic Signals– Signal Energy and Energy Spectral Density – Signal Power and Power Spectral Density
• Signal Transmission through a Linear System– Convolution Integral and Transfer Function
Outline• Signals and Systems
– Signals and Systems– What is a signal?– Signal Basics– Analog / Digital Signals– Real vs Complex– Periodic vs. Aperiodic– Bounded vs. Unbounded– Causal vs. Noncausal– Even vs. Odd– Power vs. Energy
The Bands
VLF LF MF HF VHF UHF SHF EHF
Su
bm
illime
ter
Ra
ng
eELF
3MHz 30MHz300MHz 3GHz 30GHz 300GHz
FarInfra-Red
300KHz30KHz 3THz
300m
Radio Optical
3KHz
NearInfra-Red
700nm
1PetaHz
Red
Orange
Yellow
Green
Blue
Indigo
Violet
600nm 400nm500nm
Ultraviolet
1ExaHz
X-Ray
1500nm
Introduction to Signals
• A Signal is the function of one or more independent variables that carries some information to represent a physical phenomenon.
• A continuous-time signal, also called an analog signal, is defined along a continuum of time.
Elementary Signals
Sinusoidal & Exponential Signals• Sinusoids and exponentials are important in signal
and system analysis because they arise naturally in the solutions of the differential equations.
• Sinusoidal Signals can expressed in either of two ways :
cyclic frequency form- A sin 2Пfot = A sin(2П/To)t
radian frequency form- A sin ωot
ωo = 2Пfo = 2П/To
To = Time Period of the Sinusoidal Wave
Sinusoidal & Exponential Signals Contd.
x(t) = A sin (2Пfot+ θ)= A sin (ωot+ θ)
x(t) = Aeat Real Exponential
= Aejω̥t = A[cos (ωot) +j sin (ωot)] Complex Exponential
θ = Phase of sinusoidal wave A = amplitude of a sinusoidal or exponential signal fo = fundamental cyclic frequency of sinusoidal signal ωo = radian frequency
Sinusoidal signal
Signal Examples• Electrical signals --- voltages and currents in a
circuit• Acoustic signals --- audio or speech signals
(analog or digital)• Video signals --- intensity variations in an image
(e.g. a CT scan)• Biological signals --- sequence of bases in a
gene• Noise: unwanted signal
:
Measuring Signals
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5.55111512312578E-017
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Period
Am
plitude
Definitions
• Voltage – the force which moves an electrical current against resistance
• Waveform – the shape of the signal (previous slide is a sine wave) derived from its amplitude and frequency over a fixed time (other waveform is the square wave)
• Amplitude – the maximum value of a signal, measured from its average state
• Frequency (pitch) – the number of cycles produced in a second – Hertz (Hz). Relate this to the speed of a processor eg 1.4GigaHertz or 1.4 billion cycles per second
Signal Basics Continuous time (CT) and discrete time (DT) signals
CT signals take on real or complex values as a function of an independent variable that ranges over the real numbers and are denoted as x(t).
DT signals take on real or complex values as a function of an independent variable that ranges over the integers and are denoted as x[n].
Note the subtle use of parentheses and square brackets to distinguish between CT and DT signals.
Analog Signals
• Human Voice – best example
• Ear recognises sounds 20KHz or less
• AM Radio – 535KHz to 1605KHz
• FM Radio – 88MHz to 108MHz
Digital signals
• Represented by Square Wave• All data represented by binary values
• Single Binary Digit – Bit• Transmission of contiguous group of bits is a bit
stream• Not all decimal values can be represented by
binary1 0 1 0 1 0 1 0
Analogue vs. Digital
Analogue Advantages• Best suited for audio and video• Consume less bandwidth• Available world wide
Digital Advantages• Best for computer data• Can be easily compressed• Can be encrypted• Equipment is more common and less expensive• Can provide better clarity
Analog or Digital
• Analog Message: continuous in amplitude and over time– AM, FM for voice sound– Traditional TV for analog video– First generation cellular phone (analog mode)– Record player
• Digital message: 0 or 1, or discrete value– VCD, DVD– 2G/3G cellular phone– Data on your disk
A/D and D/A
• Analog to Digital conversion; Digital to Analog conversion– Gateway from the communication device to the
channel
• Nyquist Sampling theorem– From time domain: If the highest frequency in the
signal is B Hz, the signal can be reconstructed from its samples, taken at a rate not less than 2B samples per second
Real vs. ComplexQ. Why do we deal with complex signals? A. They are often analytically simpler to deal with than real
signals, especially in digital communications.
Periodic vs. Aperiodic Signals Periodic signals have the property that x(t + T) = x(t) for all t.
The smallest value of T that satisfies the definition is called the period.
Shown below are an aperiodic signal (left) and a periodic signal (right).
A causal signal is zero for t < 0 and an non-causal signal is zero for t > 0
Right- and left-sided signals
A right-sided signal is zero for t < T and a left-sided signal is zero for t > T where T can be positive or negative.
Causal vs. Non-causal
Even vs. Odd Even signals xe(t) and odd signals xo(t) are defined as
xe(t) = xe(−t) and xo(t) = −xo(−t). Any signal is a sum of unique odd and even signals. Using
x(t) = xe(t)+xo(t) and x(−t) = xe(t) − xo(t)
Another Classification of Signals (Waveforms)
• Deterministic Signals: Can be modeled as a completely specified function of time
• Random or Stochastic Signals: Cannot be completely specified as a function of time; must be modeled probabilistically
Signum Function
( ) ( ) 1 , 0
sgn 0 , 0 2u 1
1 , 0
t
t t t
t
> = = = − − <
Precise Graph Commonly-Used Graph
The signum function, is closely related to the unit-step function.
Unit Ramp Function
( ) ( ) ( ), 0ramp u u
0 , 0
tt tt d t t
tλ λ
−∞
> = = = ≤ ∫
•The unit ramp function is the integral of the unit step function.•It is called the unit ramp function because for positive t, its slope is one amplitude unit per time.
Representation of Impulse Function
The area under an impulse is called its strength or weight. It is represented graphically by a vertical arrow. An impulse with a strength of one is called a unit impulse.
Properties of the Impulse Function
( ) ( ) ( )0 0g gt t t dt tδ∞
−∞
− =∫
The Sampling Property
( )( ) ( )0 0
1a t t t t
aδ δ− = −
The Scaling Property
The Replication Property
g(t) ⊗ δ(t) = g (t)
Unit Impulse TrainThe unit impulse train is a sum of infinitely uniformly-spaced impulses and is given by
( ) ( ) , an integerTn
t t nT nδ δ∞
=−∞
= −∑
The Unit Rectangle Function
The unit rectangle or gate signal can be represented as combination of two shifted unit step signals as shown
The Unit Triangle Function
A triangular pulse whose height and area are both one but its base width is not, is called unit triangle function. The unit triangle is related to the unit rectangle through an operation called convolution.
Signal Properties: Terminology
• Waveform• Time-average operator• Periodicity• DC value
• Power
• RMS Value
• Normalized Power• Normalized Energy
Power and Energy Signals
• Power Signal– Infinite duration– Normalized power
is finite and non-zero
– Normalized energy averaged over infinite time is infinite
– Mathematically tractable
• Energy Signal– Finite duration– Normalized energy
is finite and non-zero
– Normalized power averaged over infinite time is zero
– Physically realizable
The Decibel (dB)
• Measure of power transfer
• 1 dB = 10 log10 (Pout / Pin)
• 1 dBm = 10 log10 (P / 10-3) where P is in Watts
• 1 dBmV = 20 log10 (V / 10-3) where V is in Volts
What is a communications system?
• Communications Systems: Systems designed to transmit and receive information
Info Source
Info Source
Info Sink
Info Sink
CommSystem
Block Diagram
ReceiverRx
receivedmessage
tosink
m̃( t )
TransmitterTx s(t)
transmittedsignal
Channelr(t)
receivedsignal
m(t)message
from source
Info Source
Info Source
Info Sink
Info Sink
n(t)noise
Telecommunication
• Telegraph
• Fixed line telephone
• Cable
• Wired networks
• Internet
• Fiber communications
• Communication bus inside computers to communicate between CPU and memory
Wireless Communications
• Satellite
• TV
• Cordless phone
• Cellular phone
• Wireless LAN, WIFI
• Wireless MAN, WIMAX
• Bluetooth
• Ultra Wide Band
• Wireless Laser
• Microwave
• GPS
• Ad hoc/Sensor Networks
Comm. Sys. Bock Diagram
m̃( t )Txs(t)
Channelr(t)
m(t)
Noise
RxBaseband
SignalBaseband
SignalBandpassSignal• “Low” Frequencies
• <20 kHz• Original data rate
• “High” Frequencies• >300 kHz• Transmission data rate
Modulation
Demodulationor
Detection
Discrete-Time Signals
• Sampling is the acquisition of the values of a continuous-time signal at discrete points in time
• x(t) is a continuous-time signal, x[n] is a discrete-time signal
[ ] ( )x x where is the time between sampless sn nT T=
Discrete Time Exponential and Sinusoidal Signals
• DT signals can be defined in a manner analogous to their continuous-time counter partx[n] = A sin (2Пn/No+θ)
= A sin (2ПFon+ θ)
x[n] = an n = the discrete time
A = amplitude θ = phase shifting radians, No = Discrete Period of the wave
1/N0 = Fo = Ωo/2 П = Discrete Frequency
Discrete Time Sinusoidal Signal
Discrete Time Exponential Signal
Discrete Time Unit Impulse Function or Unit Pulse Sequence
[ ] 1 , 0
0 , 0
nn
nδ
== ≠
[ ] [ ] for any non-zero, finite integer .n an aδ δ=
Operations of Signals
• Sometime a given mathematical function may completely describe a signal .
• Different operations are required for different purposes of arbitrary signals.
• The operations on signals can be Time Shifting Time Scaling Time Inversion or Time Folding
Time Shifting• The original signal x(t) is shifted by an
amount tₒ.
• X(t)X(t-to) Signal Delayed Shift to the right