Why is the system considered linear in this case?

In summary, the conversation discusses a linear system with equations y(t)=[cos(3t)]*x(t), y1(t)=[cos(3t)]*x1(t), y2(t)=[cos(3t)]*x2(t), and y3(t)=[cos(3t)]*(a*x1(t)+b*x2(t)). It is mentioned that the system is linear, but the last two lines reveal a mistake in the equations provided.
  • #1
khdani
55
0
hello,
y(t)=[cos(3t)]*x(t)
x1(t) -> y1(t)=[cos(3t)]*x1(t)
x2(t) -> y2(t)=[cos(3t)]*x2(t)
x3(t) = a*x1(t)+b*x2(t)
x3(t) -> y3(t)=[cos(3t)]*x3(t)=[cos(3t)]*(a*x1(t)+b*x2(t))=
=[cos(3t)]*(a*[cos(3t)]*x1(t)+b*[cos(3t)]*x2(t))
y3(t) not equal a*y1(t)+b*y2(t) but the answers in the book said that
the system is linear? why? am i wrong or there's a mistake in the book?
 
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  • #2
Check out the last two lines again. You've got a mistake there...
 
  • #3
i found the mistake, thanks
 

1. Why do we use linear signals in science?

Linear signals are commonly used in science because they are easier to analyze and manipulate mathematically. This allows for better understanding and prediction of physical phenomena.

2. How can we determine if a signal is linear?

A signal is considered linear if it follows the properties of linearity, which include superposition, homogeneity, and additivity. These properties can be tested through mathematical operations and graphical analysis.

3. What is the significance of a linear signal?

Linear signals have a wide range of applications in science, including in fields such as physics, engineering, and economics. They allow for the modeling and prediction of various natural and man-made systems.

4. Can a non-linear signal be transformed into a linear signal?

Yes, some non-linear signals can be transformed into linear signals through mathematical techniques such as linearization. However, this may not always be possible or practical.

5. Are all physical signals inherently linear?

No, not all physical signals are linear. Some signals may exhibit non-linear behavior due to factors such as non-linear systems or external influences. However, linear signals are often used as approximations in these cases.

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