Ryan B.

asked • 04/18/16

is y(t) = 3 f(t-2) +4 a LTI system?

i just had a pop quiz in one of my classes, i am wondering if i got the answers correct (the solution hasn't been posted online yet).
 
y(t) is the output
f(t) is the input
 
y(t) = 3 f(t-2) +4
 
is the system linear?
 
Is the system time invariant? 
 
 
Although it wasn't asked i was also curious what the answer would be if 
"y(t) is the input
f(t) is the output"
 
 
thanks!
----------------------------------------------------edit----------------------
 
 
LTI means linear time invarient (system)
https://en.wikipedia.org/wiki/LTI_system_theory
 
 
here is a similar problem worked out as an example:
 
Problem 1.27
(a) y(t) = x(t − 2) + x(2 − t)
Let us check for linearity.
x1(t) → y1(t) = x1(t − 2) + x1(2 − t)
x2(t) → y2(t) = x2(t − 2) + x2(2 − t)
ax1(t) + bx2(t) = x3(t) → y3(t) = x3(t − 2) + x3(2 − t)
= ax1(t − 2) + bx2(t − 2) + ax1(2 − t) + bx2(2 − t)
= a(x1(t − 2) + x1(2 − t)) + b(x2(t − 2) + x2(2 − t))
= ay1(t) + by2(t)
Hence linear.
Let us check for time-invariance.
x1(t) → y1(t) = x1(t − 2) + x1(2 − t)
x1(t − to) = x2(t) → y2(t) = x2(t − 2) + x2(2 − t)
= x1(t − to − 2) + x2(2 − t − to)
6= y1(t − to)
Note that y1(t − to) = x1(t − to − 2) + x1(2 − t + to). Hence time-variant.
Suppose |x(t)| < B. Then y(t) < B + B = 2B (because |x(t − 2)| < B and |x(2 − t)| < B).
Hence stable.
Not memoryless as the present output at time t depends on t − 2.
Non-Causal because y(-1)=x(-3)+x(3). So depends on future inputs.

1 Expert Answer

By:

Alan G. answered • 04/18/16

Tutor
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Ryan B.

LTI stands for Linear time invarient (system). https://en.wikipedia.org/wiki/LTI_system_theory
sorry i wasn't clear. 

it is odd because y(t) and f(t) are not explicitly expressed, they remain ambiguous functions.
here is a similar problem i found online (as an example):
ECEN 314: Signals and Systems
Solutions to HW 3
Problem 1.27
(a) y(t) = x(t − 2) + x(2 − t)
Let us check for linearity.
x1(t) → y1(t) = x1(t − 2) + x1(2 − t)
x2(t) → y2(t) = x2(t − 2) + x2(2 − t)
ax1(t) + bx2(t) = x3(t) → y3(t) = x3(t − 2) + x3(2 − t)
= ax1(t − 2) + bx2(t − 2) + ax1(2 − t) + bx2(2 − t)
= a(x1(t − 2) + x1(2 − t)) + b(x2(t − 2) + x2(2 − t))
= ay1(t) + by2(t)
Hence linear.
Let us check for time-invariance.
x1(t) → y1(t) = x1(t − 2) + x1(2 − t)
x1(t − to) = x2(t) → y2(t) = x2(t − 2) + x2(2 − t)
= x1(t − to − 2) + x2(2 − t − to)
6= y1(t − to)
Note that y1(t − to) = x1(t − to − 2) + x1(2 − t + to). Hence time-variant.
Suppose |x(t)| < B. Then y(t) < B + B = 2B (because |x(t − 2)| < B and |x(2 − t)| < B).
Hence stable.
Not memoryless as the present output at time t depends on t − 2.
Non-Causal because y(-1)=x(-3)+x(3). So depends on future inputs.
 
 
 
it is odd because y(t) and f(t) are not explicitly expressed, they remain ambiguous functions.
Report

04/18/16

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