Time Invariant Signal: Help Me See Why My Solution is Wrong

Thread starter Huumah
Start date Feb 23, 2013
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Invariant Signal Time

In summary, a time-invariant signal is a type of signal that does not change over time and maintains its characteristics, such as frequency and amplitude, regardless of when it is observed. To determine if a signal is time-invariant, the time-shifting property can be used. Some examples of time-invariant signals include sinusoidal waves, square waves, and triangular waves. Time-invariant signals differ from time-varying signals in that they do not change over time, while time-varying signals do. Understanding time-invariant signals is important in signal processing as it allows for accurate analysis and manipulation of signals.

Feb 23, 2013

Huumah

Can anyone help my to see why my solution is wrong because the in the solutions it says that it is not time invariant

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Feb 23, 2013

mfb

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I don't understand what y_A and y_B are.

Simple example:
y(0)=x(-2)+x(2)
y(1)=x(-1)+x(1)
In general, those sums can be different.

Related to Time Invariant Signal: Help Me See Why My Solution is Wrong

1. What is a time-invariant signal?

A time-invariant signal is a type of signal that does not change over time. This means that the signal's characteristics, such as frequency and amplitude, remain constant regardless of when it is observed.

2. How do you determine if a signal is time-invariant?

To determine if a signal is time-invariant, you can use the time-shifting property. This property states that if a signal x(n) is shifted by a certain amount of time, the output y(n) will also be shifted by the same amount of time. If this property holds true for a signal, it is time-invariant.

3. What are some examples of time-invariant signals?

Some examples of time-invariant signals include sinusoidal waves, square waves, and triangular waves. These signals maintain their shape and characteristics over time, making them time-invariant.

4. How do time-invariant signals differ from time-varying signals?

Time-invariant signals do not change over time, while time-varying signals do. Time-varying signals may have changing characteristics such as frequency and amplitude, whereas time-invariant signals maintain these characteristics over time.

5. Why is understanding time-invariant signals important in signal processing?

Understanding time-invariant signals is important in signal processing because it allows for accurate analysis and manipulation of signals. Time-invariant signals have predictable behavior, making them easier to work with and analyze compared to time-varying signals.