systems ppt
TRANSCRIPT
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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
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ABSTRACT
INTRODUCTIONDEFINITIONTYPES OF SYSTEMSAPPLICATIONSPROBLEMSQUERIES
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INTRODUCTION
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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.
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Block Diagram Representation of a System
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CONTINUOUS SYSTEM
A system is continuous-time when its input and output signals are continuous-time.
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DISCRETE SYSTEM
A system is discrete -time when its input and output signals are discrete-time.
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TYPES OF SYSTEM
Static & Dynamic systemCausal & Non Causal systemStable & Unstable systemLinear & Non-linear systemTime variant & Time invariant system
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STATIC SYSTEM
Output depend only on present input.Also called as memory-less system.
Examplesy(n) = 9x(n)y(t) = x2(t) + 8x(t) + 17
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RESISTORS
+
-
SPST
R V
+
-Bt
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DYNAMIC SYSTEM
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)
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CAPACITORS
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CAUSAL SYSTEM
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.
Examplesy(n) = x(n) + x(n-2)y(t) = x(t-1) – x(t-3)
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SIGNIFICANCE OF CAUSAL SYSTEM
Practically realizable.All real time systems are causal systems.
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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.
ExamplesY(n) = x(n) + x(n+1)Y(n) = 7x(n+2)
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SIGNIFICANCE OF NON-CAUSAL SYSTEM
Practically not realizable.But can be predictable.
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EXAMPLES
Population growthWeather forecasting Planning commission
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STABLE SYSTEM
A stable system is BIBO stable if and only if every bounded input produces bounded output.
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UNSTABLE SYSTEM
An initially system is said to be unstable if bounded input produces unbounded (infinite) output.
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SIGNIFICANCE OF UNSTABLE SYSTEM
Unstable system shows erratic and extreme behavior.When unstable system is practically implemented then it causes overflow.
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LINEAR & NON-LINEAR SYSTEM
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.
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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 discrete signal y n y n output discrete signal
x t x t input continuos signal y t y t output continuos signal
1
I
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TIME VARIANT SYSTEM
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
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TIME INVARIANT SYSTEM
If the system satisfies the following condition y(t-T)=T[x(t-T)]Then the system is said to be time invariant
system.
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LTI SYSTEM EXAMPLES
SEISMOGRAPH NMR SPECTROSCOPY
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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
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QUERIES?
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