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where is the instance, [] the expectation value, is a class into which an instance is classified, (|) is the conditional probability of label for instance , and () is the 0–1 loss function: L ( x , y ) = 1 − δ x , y = { 0 if x = y 1 if x ≠ y {\displaystyle L(x,y)=1-\delta _{x,y}={\begin{cases}0&{\text{if }}x=y\\1&{\text{if }}x\neq y\end ...
The BER is the likelihood of a bit misinterpretation due to electrical noise ().Considering a bipolar NRZ transmission, we have = + for a "1" and () = + for a "0".Each of () and () has a period of .
The probability of erasure is In coding theory and information theory , a binary erasure channel ( BEC ) is a communications channel model. A transmitter sends a bit (a zero or a one), and the receiver either receives the bit correctly, or with some probability P e {\displaystyle P_{e}} receives a message that the bit was not received ("erased") .
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Proof. We need to prove that if you add a burst of length to a codeword (i.e. to a polynomial that is divisible by ()), then the result is not going to be a codeword (i.e. the corresponding polynomial is not divisible by ()).
Error-correcting codes are used in lower-layer communication such as cellular network, high-speed fiber-optic communication and Wi-Fi, [11] [12] as well as for reliable storage in media such as flash memory, hard disk and RAM. [13] Error-correcting codes are usually distinguished between convolutional codes and block codes:
It therefore suffices to exhibit an input distribution that yields a uniform probability distribution for the output . For this, note that it is a property of any binary symmetric channel that a uniform probability distribution of the input results in a uniform probability distribution of the output.