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Viterbi path and Viterbi algorithm have become standard terms for the application of dynamic programming algorithms to maximization problems involving probabilities. [3] For example, in statistical parsing a dynamic programming algorithm can be used to discover the single most likely context-free derivation (parse) of a string, which is ...
3×10 43 (30 tredecillion) The estimated time for all nucleons in the observable universe to decay, if the hypothesized proton half-life takes the largest possible value of 10 41 years, [9] assuming that the Big Bang was inflationary and that the same process that made baryons predominate over anti-baryons in the early universe makes protons ...
We can then calculate the probability of reaching an intermediate state as the sum of all possible paths to that state. Thus the partial probabilities for the final observation will hold the probability of reaching those states going through all possible paths.
There may be a chance that information rate may go below to required threshold level. For slow fading channel, outage probability = P(C < r) = P(log 2 (1 + h 2 SNR) < r), where r is the required threshold information rate.
The principle of maximum caliber (MaxCal) or maximum path entropy principle, suggested by E. T. Jaynes, [1] can be considered as a generalization of the principle of maximum entropy. It postulates that the most unbiased probability distribution of paths is the one that maximizes their Shannon entropy. This entropy of paths is sometimes called ...
If we take the frequentist view of probability, we believe there is a true probability distribution that generated the data. Then it turns out that the Dirichlet process is consistent in the weak topology , which means that for every weak neighbourhood U {\displaystyle U} of P 0 {\displaystyle P_{0}} , the posterior probability of U ...
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Maximal entropy random walk (MERW) is a popular type of biased random walk on a graph, in which transition probabilities are chosen accordingly to the principle of maximum entropy, which says that the probability distribution which best represents the current state of knowledge is the one with largest entropy.