7 resultados para FIRST-ORDER ABDUCTION
em Bulgarian Digital Mathematics Library at IMI-BAS
Resumo:
First order characterizations of pseudoconvex functions are investigated in terms of generalized directional derivatives. A connection with the invexity is analysed. Well-known first order characterizations of the solution sets of pseudolinear programs are generalized to the case of pseudoconvex programs. The concepts of pseudoconvexity and invexity do not depend on a single definition of the generalized directional derivative.
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We consider the existence and uniqueness problem for partial differential-functional equations of the first order with the initial condition for which the right-hand side depends on the derivative of unknown function with deviating argument.
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Part of network management is collecting information about the activities that go on around a distributed system and analyzing it in real time, at a deferred moment, or both. The reason such information may be stored in log files and analyzed later is to data-mine it so that interesting, unusual, or abnormal patterns can be discovered. In this paper we propose defining patterns in network activity logs using a dialect of First Order Temporal Logics (FOTL), called First Order Temporal Logic with Duration Constrains (FOTLDC). This logic is powerful enough to describe most network activity patterns because it can handle both causal and temporal correlations. Existing results for data-mining patterns with similar structure give us the confidence that discovering DFOTL patterns in network activity logs can be done efficiently.
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2000 Mathematics Subject Classification: 34K15.
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2000 Mathematics Subject Classification: 90C46, 90C26, 26B25, 49J52.
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AMS subject classification: Primary 34A60, Secondary 49K24.
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2000 Mathematics Subject Classification: 62G32, 62G20.