Upcoming SlideShare
×

# Signals and classification

4,772 views

Published on

1 Comment
9 Likes
Statistics
Notes
• Full Name
Comment goes here.

Are you sure you want to Yes No
• thanks

Are you sure you want to  Yes  No
Views
Total views
4,772
On SlideShare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
470
1
Likes
9
Embeds 0
No embeds

No notes for slide

### Signals and classification

1. 1. SIGNALS AND SYSTEM SURAJ MISHRA SUMIT SINGH AMIT GUPTA PRATYUSH SINGH (E.C 2ND YEAR ,MCSCET) 1
2. 2. Topics     Introduction Classification of Signals Some Useful Signal Operations Some useful signal models 2
3. 3. Introduction  The concepts of signals and systems arise in a wide variety of areas:  communications,  circuit design,  biomedical engineering,  power systems,  speech processing,  etc. 3
4. 4. 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. 4
5. 5. Examples of Signals  BRAIN WAVE 5
6. 6. Examples of Signals  Stock Market data as signal (time series) 6
7. 7. What is a System? SYSTEM Signals 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). 7
8. 8. 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). 8
9. 9. 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. 9
10. 10. Some Useful Signal Models 10
11. 11. 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 11
12. 12. Signal Models: Unit Impulse Function A possible approximation to a unit impulse: An overall area that has been maintained at unity. Graphically, it is represented by an arrow "pointing to infinity" at t=0 with its length equal to its area.  Multiplication of a function by an Impulse?  bδ(t) = 0; for all t≠0 is an impulse function which the area is b. 12
13. 13. 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. 13
14. 14. Signal Models: Unit Ramp Function  Unit  ramp function is defined by: r(t) = t∗u(t)  Where can it be used? 14
15. 15. Signal Models: Exponential Function est  Most important function in SNS where s is complex in general, s = σ+jϖ  Therefore, est = e(σ+jϖ)t = eσtejϖt = eσt(cosϖt + jsinϖt) (Euler’s formula: ejϖt = cosϖt + jsinϖt) s∗ = σ-jϖ,  es∗ t = e(σ-jϖ)t = eσte-jϖt = eσt(cosϖt - jsinϖt)  If  From the above, e cosϖt = ½(e +e ) σt st -st 15
16. 16. Signal Models: Exponential Function est (2)    Variable s is complex frequency. est = e(σ+jϖ)t = eσtejϖt = eσt(cosϖt + jsinϖt) es∗ t = e(σ-jϖ)t = eσte-jϖt = eσt(cosϖt - jsinϖt) eσtcosϖt = ½(est +e-st ) There are special cases of est : 1. 2. 3. 4. A constant k = ke0t (s=0  σ=0,ϖ=0) A monotonic exponential eσt (ϖ=0, s=σ) A sinusoid cosϖt (σ=0, s=±jϖ) An exponentially varying sinusoid eσtcosϖt (s= σ ±jϖ) 16
17. 17. 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 17
18. 18. Continuous v/S Discrete Signals  Continuous-time A signal that is specified for every value of time t.  Discrete-time A signal that is specified only at discrete values of time t. 18
19. 19. 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) 19
20. 20. 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. 20
21. 21. Even v/s Odd Signals 21
22. 22. 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: 22
23. 23. Even and Odd Functions: Properties  Property:  Area:  Even signal:  Odd signal: 23
24. 24. 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) 24
25. 25. Energy v/s Power Signals  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 25
26. 26. Size of a Signal, Energy (Joules)  Measured by signal energy Ex:  Generalize  CT:  Energy for a complex valued signal to: DT: must be finite, which means 26
27. 27. 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: 27
28. 28. 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- 28
29. 29. 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) 29
30. 30. 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.  30
31. 31. 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) 31
32. 32. 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. 32
33. 33. 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–t ) o   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. 33
34. 34. 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. 34
35. 35. Signal Operations: Time Shifting  Shifting of a signal in time 35
36. 36. 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) ? 36
37. 37. Time Scaling 37
38. 38. Signal Operations: Time Inversion  Reversal of the time axis, or folding/flipping the signal (mirror image) over the y-axis. 38
39. 39. THANKS....................... FOR YOUR ATTENTION ! 39