This document provides an overview of continuous signals and their properties. It defines a communication system and signals, and classifies signals as either continuous or discrete. Continuous signals are further classified and examples are given of unit step, ramp, exponential, and impulse signals. Properties of signals like determinism, periodicity, causality, even and odd characteristics, and energy and power are described. Key signal processing concepts like time shifting, time scaling, time reversal, convolution, and correlation are also summarized.

1. ABHIRUP MAJUMDAR
15/ECE/04
ASSIGNMENT ON CONTINUOUS
SIGNAL

2. CONTENTS
 Introduction To Communication System.
 Introduction To Signals.
 Classification of Signals.
 Introduction To Continuous Signals.
 Classification of Continuous Signals.
 Properties of Signals.

3. What is a communications
system?
 Communications Systems is a
Systems designed to transmit and
receive information.

4. COMMUNICATION SYSTEM

5. SIGNAL
A signal is a function of time representing a
physical variable, eg: voltage, current etc.
A signal is defined as a function of one or
more independent variables.

6. Signal Basics

7. CLASSIFICATION OF SIGNALS
Signals are basically classified into two
different types as follows.
 Continuous time signals
 Discrete time signals

8. INTRODUCTION TO
CONTINUOUS
SIGNALS

9. CT Signals
In continuous time signals the independent
variable is continuous, and they are defined
for a continuum of values

10. Example

11. DT Signal
Discrete time signals are defined only at
discrete times and for these signals the
independent variable takes on only a discrete
set of values

12. Example

13. Representation
To distinguish between continuous-time and
discrete time signals, we will use the symbol
‘t’ to denote the continuous time independent
variable and ‘n’ to denote the discrete time
independent variable.

14. Classifications of CT signals
The CT signals can be further classified intoThe CT signals can be further classified into
the following-the following-
Unit stepUnit step
Unit rampUnit ramp
ExponentialExponential
ImpulseImpulse

15. Unit Step Signal

16. Ramp Signals

17. CT system

18. DT system

19. UNIT IMPULSE FUNCTION
 So unit impulse
function is the
derivative of the
unit step function or
unit step is the
integral of the unit
impulse function.

20. Properties Of Impulse Function

21. CLASSIFICATIONS OF SIGNALS
 DETERMINISTIC & NON-DETERMINISTICS
SIGNALS.
 PERIODIC & APERIODIC SIGNAL.
 CAUSAL & NON-CAUSAL SIGNAL.
 EVEN & ODD SIGNALS.
 ENERGY & POWER SIGNALS.

22. DETERMINISTIC & NON-
DETERMINISTICS SIGNALS.

23. DETERMINISTIC & NON-
DETERMINISTICS SIGNALS.

24. PERIODIC & APERIODIC SIGNAL.

25. PERIODIC & APERIODIC SIGNAL
CONDITIONS.

26. Important Condition of Periodicity for
Discrete Time Signals

27. SUM OF PERIODIC SIGNALS

28. Sum of periodic Signals – may not
always be periodic!

29. Even and Odd Signals

30. Even and Odd Parts of Functions

31. Various Combinations of even and
odd functions.

32. Product of Even and Odd
Functions.

33. Product of Even and Odd
Functions Contd.

34. Product of Even and Odd
Functions Contd.

35. Derivatives and Integrals of
Functions

36. Energy and Power Signals

37. Energy and Power Signals

38. Energy and Power Signals Contd.

39. Properties OF SIGNALS

40. TIME SHIFTING PROPERTY

41. TIME SHIFTING CONDITION

42. TIME SCALING

43. TIME SCALING CONTD.

44. TIME SCALING CONTD.

45. TIME REVERSAL

46. TIME REVERSAL CONTD.

47. CONVOLUTION
 Homogeneity, additivity, and shift invariance may, at first,
sound a bit abstract but they are very useful. To
characterize a shift-invariant linear system, we need to
measure only one thing: the way the system responds to a
unit impulse. This response is called the impulse response
function of the system. Once we’ve measured this
function, we can (in principle) predict how the system will
respond to any other possible stimulus.

48. CONVOLUTION INTEGRAL

49. Properties Of CONVOLUTION

50. Correlation

51. Correlation

52. THANK YOU