What Does ROC Mean in Signals and Processing?

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In summary, the Laplace transform of ##e^{-at}u(t)## is ##1/(s+a)##, but it is only defined for values of ##s## greater than ##-a##. The ROC is the region of values for which the transform is defined.
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Homework Statement


Find laplace of e-atu(t) where a > 0

Homework Equations


Laplace is integration from -inf to +inf f(t)e-stdt
u(t) is 1 for t more than equal to 0.

The Attempt at a Solution


Well i got the answer as X(s) = 1/(s+a).

But the book said something like ROC like region of convergence and for that s must be more than -a
I understand that s more than minus a, gives positive 1/(s+a)
but why?

Why can't ROC be negative? What does ROC mean? I am studying Signals and Processing.
 
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jaus tail said:

Homework Statement


Find laplace of e-atu(t) where a > 0

Homework Equations


Laplace is integration from -inf to +inf f(t)e-stdt
u(t) is 1 for t more than equal to 0.

The Attempt at a Solution


Well i got the answer as X(s) = 1/(s+a).

But the book said something like ROC like region of convergence and for that s must be more than -a
I understand that s more than minus a, gives positive 1/(s+a)
but why?

Why can't ROC be negative? What does ROC mean? I am studying Signals and Processing.
Your integral is ##\int_1^\infty e^{-st}e^{-at}~dt = \int_1^\infty e^{-(s+a)t}~dt##. That integral will only converge if the exponent is negative, meaning ##s+a>0##. ROC in this case means the region of convergence, the values of ##s## for which the transform is defined.
 
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Related to What Does ROC Mean in Signals and Processing?

1. What is ROC in signal processing?

ROC stands for Receiver Operating Characteristic and it is a graphical plot that illustrates the performance of a signal processing system. It shows the relationship between the true positive rate and the false positive rate of a system.

2. How is ROC calculated?

ROC is calculated by plotting the true positive rate (TPR) against the false positive rate (FPR) at various threshold settings. The area under the curve (AUC) of the ROC plot gives an overall measure of the system's performance.

3. What does a high ROC indicate?

A high ROC indicates that the signal processing system has a high true positive rate and a low false positive rate. This means that the system is able to accurately detect signals and minimize false alarms.

4. How is ROC used in signal processing?

ROC is used to evaluate the performance of signal processing systems, such as in medical imaging or radar systems. It helps determine the optimal threshold setting for the system and compare the performance of different systems.

5. Are there any limitations to using ROC?

While ROC is a useful tool for evaluating signal processing systems, it does have some limitations. It assumes that the cost of false positives and false negatives are equal, which may not always be the case. Additionally, ROC does not take into account the overall accuracy of the system, only the relative performance at different threshold settings.

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