maximum amount constraint

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• Maximum flow problem — An example of a flow network with a maximum flow. The source is s, and the sink t. The numbers denote flow and capacity. In optimization theory, the maximum flow problem is to find a feasible flow through a single source, single sink flow network …   Wikipedia

• Maximum likelihood — In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of a statistical model. When applied to a data set and given a statistical model, maximum likelihood estimation provides estimates for the model s… …   Wikipedia

• Maximum entropy probability distribution — In statistics and information theory, a maximum entropy probability distribution is a probability distribution whose entropy is at least as great as that of all other members of a specified class of distributions. According to the principle of… …   Wikipedia

• Principle of maximum entropy — This article is about the probability theoretic principle. For the classifier in machine learning, see maximum entropy classifier. For other uses, see maximum entropy (disambiguation). Bayesian statistics Theory Bayesian probability Probability… …   Wikipedia

• Max-flow min-cut theorem — In optimization theory, the max flow min cut theorem states that in a flow network, the maximum amount of flow passing from the source to the sink is equal to the minimum capacity which when removed in a specific way from the network causes the… …   Wikipedia

• Differential entropy — (also referred to as continuous entropy) is a concept in information theory that extends the idea of (Shannon) entropy, a measure of average surprisal of a random variable, to continuous probability distributions. Contents 1 Definition 2… …   Wikipedia

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• Run length limited — or RLL coding is a technique that is used to store data on recordable media. Specifically, RLL prevents long stretches of repeated bits from causing the signal recorded on media to not change for an excessive period, by modulating the data. RLL… …   Wikipedia