Expressing probability of bit error

AI Thread Summary
The discussion focuses on calculating the probability of bit error in a bipolar system using threshold detection. The key equation mentioned is P_e = Q(ρ), where ρ = Ap/σn. The user expresses uncertainty about interpreting the figure related to the problem and questions whether the shaded regions represent bit errors. They also seek clarification on expressing the probability in terms of conditional probabilities and integrals, indicating confusion about their approach. The conversation highlights the need for guidance on these concepts to accurately determine the bit error probability.
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Homework Statement


I need to the probability of bit error in terms of integrals and terms of conditional probabilities.

Its a bipolar system using threshold detection
https://www.physicsforums.com/attachment.php?attachmentid=58542&stc=1&d=1367888259


Homework Equations


probability of bit error → ##P_e=Q(\rho)##
##\rho = \frac{A_p}{\sigma_n}##


The Attempt at a Solution


Im not sure I understand what's going on in the figure for this question. I would think that the bit error would be the shaded regions correct? I might be able to figure something out for expressing it in terms of conditional probability but I don't think it would be 100% correct. On top of that I have no idea how to express them in terms of integrals.

Im kind of guessing here but would it be something like $$P_e=p(r|-a) \ + \ p(r|a)$$

Im thinking no...

Any help or hints are greatly appreciated!
 
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I've normally seen error rates based on bit error rate in this fashion:

bit error rate = p
probability of a good bit = 1 - p
probability of a good byte (8 good bits) = (1-p)^8
 
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