This document defines and describes different types of systems. It defines a system as a physical device used to process or extract information from signals. The document then describes the main types of systems as: 1) Continuous and discrete systems based on signal type. 2) Static and dynamic systems based on whether the output depends on present or past/future inputs. 3) Causal and non-causal systems based on whether the output depends on past and present inputs or also future inputs. 4) Stable and unstable systems based on whether inputs produce bounded or unbounded outputs. 5) Linear and non-linear systems based on whether they satisfy the superposition principle. 6) Time

2. SYSTEMS
GUIDED BY:- PRESENTED BY:-
Mr. SYED AKBAR S VASANTH KUMAR.R-ECB1496
HOD VENKATESH.S -ECB1498
(DEPARTMENT OF ECE) VIGNESH.S -ECB14100
VIJAYASEELAN.M -ECB14101

3. ABSTRACT
INTRODUCTION
DEFINITION
TYPES OF SYSTEMS
APPLICATIONS
PROBLEMS
QUERIES

4. INTRODUCTION

5. DEFINITION
SYSTEM:-
It is a physical device, which is used to
process the signal (or) to extract the
information.
i)Continuous time system.
ii)Discrete time system.

6. BlockDiagram Representation of a System

7. CONTINUOUS SYSTEM
A system is continuous-time when its input and
output signals are continuous-time.

8. DISCRETESYSTEM
A system is discrete -time when its input and
output signals are discrete-time.

9. TYPESOF SYSTEM
Static & Dynamic system
Causal & Non Causal system
Stable & Unstable system
Linear & Non-linear system
Time variant & Time invariant system

10. STATICSYSTEM
Output depend only on present input.
Also called as memory-less system.
Examples
y(n) = 9x(n)
y(t) = x2(t) + 8x(t) + 17

11. RESISTORS
+
-
SPST
R
V
+
-
Bt

12. DYNAMICSYSTEM
Output depends on present, past, future
inputs.
It is also called as memory system.
Examples
 y(n)=x(n-1)
 y(t)=x(t+1)

13. CAPACITORS

14. CAUSALSYSTEM
A system is said to be causal system if its
output depends on present and past inputs
only and not on future inputs.
It is also called as anticipative system.
Examples
y(n) = x(n) + x(n-2)
y(t) = x(t-1) – x(t-3)

15. SIGNIFICANCEOF CAUSAL SYSTEM
Practically realizable.
All real time systems are causal systems.

16. NON-CAUSAL SYSTEM
A system whose present response depends on
future values of the inputs is called as a non-
causal system.
It is also called as non-anticipative system.
Examples
Y(n) = x(n) + x(n+1)
Y(n) = 7x(n+2)

17. SIGNIFICANCEOF NON-CAUSALSYSTEM
Practically not realizable.
But can be predictable.

18. EXAMPLES
Population growth
Weather forecasting
Planning commission

19. STABLESYSTEM
A stable system is BIBO stable if and only if every
bounded input produces bounded output.

20. UNSTABLESYSTEM
An initially system is said to be unstable if
bounded input produces unbounded (infinite)
output.

21. SIGNIFICANCEOF UNSTABLE SYSTEM
Unstable system shows erratic and extreme
behavior.
When unstable system is practically
implemented then it causes overflow.

22. LINEAR& NON-LINEARSYSTEM
If the system satisfies superposition principle
then the system is called linear system.
If the system does not satisfies superposition
principle then the system is called non-linear
system.
Communication channels and filters are
examples of linear systems.

23. SUPERPOSITION PRINCIPLE
The weighted sum of input is equal to the
weighted sum of output
 T[a x1(t) + b x2(t)] = a y1(t) + b y2(t)
 T[a x1(n) + b x2(n)] = a y1(n) + b y2(n)
1 2 1 2
1 2 1 2
1 2 2
1 2 1 2
( ) ( ) ( ( ) ( ))
( ) ( ) ( ( ) ( ))
( ), ( ) ,( ), ( )
( ), ( ) ( ), ( )
ay n by n T ax n bx n
ay t by t T ax t bx t
x n x n Input discretesignal y n y n output discretesignal
x t x t input continuos signal y t y t output continuos signal
  
  
 
 
1
I

24. TIME VARIANTSYSTEM
If the system does not satisfies the following
condition
y(t-T)=T[x(t-T)]
then the system is said to be time variant
system
The human vocal tract is a time variant
system

25. TIME INVARIANTSYSTEM
If the system satisfies the following condition
y(t-T)=T[x(t-T)]
Then the system is said to be time invariant
system.

26. LTI SYSTEMEXAMPLES
SEISMOGRAPH NMRSPECTROSCOPY

27. PROBLEMS
I. y(n) = x(n)
II. y(t) = x(t+2)
III. y(n) = x(2n-1)
IV.y(t) = x(t2)
V. y(n) = nx(n)
VI.y(t) =ex(t)
VII.y(n)=x(2n)
VIII.y(t)=x(t)cosωοt

28. QUERIES?