Probability - Noisy message

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In summary, the problem involves creating random character strings from a four-letter alphabet and finding the probability of having at least two identical letters next to each other in a string of length ##N##. This can be represented by the event of no runs or a run of size 2. Different approaches such as Markov chains, Poisson approximations, and ordinary generating functions can be used to find the probability. Alternatively, a direct calculation through inclusion-exclusion and careful consideration of events can also be used.
  • #1
Robin04
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Homework Statement
We try to send a message in a very noisy environment. The messages are coded with a four-letter alphabet. By convention, only the messages without lonely letters are considered to be meaningful. A letter is lonely if the next and previous letters are different (the first letter is lonely if the next is different and the last letter is lonely if the previous is different). At least how long does the message have to be if we want to have the chance of having a meaningful message to be less then ##10^{-10}## because of the noise? The noise changes the letters to other letters in the alphabet. Every letter appears independently with an equal chance.
Relevant Equations
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The phrasing of the problem is a bit messy but here's how I understood it so far:
We make random character strings out of a four-letter alphabet. Every letter appears independently with an equal chance. The chance of having at least two identical letters next to each other in a string of length ##N## is ##p(N)##. We are looking for ##N## given that ##1-p(N) \leq 10^{-10}##
So the key is to find ##p(N)##. Can you help me a bit with that?
 
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  • #2
Interesting...

I think your take on how to interpret the problem is helpful and I'd run with it -- the problem statement itself is a bit ambiguous so your interpretation seems to fill gaps. I presume this loneliness tag doesn't apply to the first and last letters -- i.e. it applies to interrior letters only.

What is missing is relevant equations-- there are many ways to tackle something like this, some of which are in reach and many (I suspect) are out of reach.

In essence it appears to be theory of runs problem -- what is the probability that the maximal run size is ##\leq 2## (i.e. event : no runs at all aka the degenerate run length of 1, union event: run of size 2) or equivalently, the probability that there is never a run of length 3. Markov Chain and poisson approximations comes to mind. There's going to be an ordinary generating function approach as well. Many other possibilities... The problem is small enough that I think a direct calculation is doable without too much trouble as well --- this requires inclusion-exclusion and carefully working through events.

edit:
my vote is for markov chains -- it boils down a 2x2 matrix... which is very easy to work with.
my second favorite here would be to set this up as a linear recurrence.
 
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What is probability in the context of a noisy message?

In the context of a noisy message, probability refers to the likelihood or chance that a particular message will be received correctly, despite being distorted by noise. It is a measure of how likely it is that the message will be accurately understood by the receiver.

How is probability calculated for a noisy message?

Probability for a noisy message is typically calculated using mathematical models, such as the Shannon-Hartley theorem, which takes into account the amount of noise present in the communication channel and the capacity of the channel to transmit information. Other factors that may affect the probability of a noisy message include the type and strength of the noise, the encoding and decoding methods used, and the quality of the receiver's equipment.

What are some common sources of noise in a communication channel?

Noise in a communication channel can come from a variety of sources, including external interference from other electronic devices, physical obstructions, and atmospheric conditions. Noise can also be introduced internally by the equipment used for encoding, transmitting, or decoding the message, or by errors in the transmission process.

How can probability be improved for a noisy message?

There are several strategies that can be used to improve the probability of a noisy message being received correctly. These include using error-correcting codes, optimizing the transmission power and frequency, and implementing noise reduction techniques. It is also important to use high-quality equipment and to regularly maintain and calibrate the equipment to minimize internal noise.

What are some real-world applications of probability in dealing with noisy messages?

Probability is a crucial concept in many real-world applications involving communication and information transmission. For example, it is used in wireless communication systems, satellite communication, and digital data storage to ensure reliable and accurate transmission of information despite noise. It is also used in fields such as cryptography, telecommunications, and data compression to improve the efficiency and security of communication systems.

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