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Titlebook: Repetitorium Notfallmedizin; Zur Vorbereitung auf Jörg Brokmann,Rolf Rossaint Book 20081st edition Springer-Verlag Berlin Heidelberg 2008 N

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xc2. Minimizing their distance with respect to the unknown parameters is a classical minimization problem and has a small computational demad. The chapter continuous by formulating and solving the fuzzy state estimation of a particular discrete time state-space model with fuzzy disturbances and init
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Jörg Brokmann Dr. knowledge-based systems. It is also expected that he is familiar with some of the well-known expert systems, especially those broadly documented in literature (e.g. PROSPECTOR, MYCIN) and mechanisms involved there which are capable of coping with uncertainty, no matter how it has been introduced. T
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s the application of fuzzy relational modeling. Fuzzy relations represent formal means for modeling of rather nontrivial phenomena (reasoning, decision, control, knowledge extraction, systems analysis and design, etc. ) in the pres­ ence of a particular kind of indeterminacy called vagueness. Models
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Guido Michels Dr.,Uta C. Hoppe Prof. Dr., depicting a general framework for building fuzzy systems by integrating CRI and FRI. The chapter also provides an analysis of the benefits of conducting inference rule selection with attribute weights, showing the efficacy of an integrated system in performing approximate reasoning for various pra
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Stefan Wiese Dr.entists have used terms which might be related to or even synonymous with fuzziness. Is fuzziness a type of ambiguity or vagueness? How is it related to uncertainty? Is it a kind of probability (and would probability do just as well)? But before moving into a full-blown discussion of terms, it is wo
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Jörg Brokmann Dr.s high iff X is high”. Only in the bivariate analysis of categorical variables are one-to-many entailments recognized, and even then only for certain measures of association (cf. Reynolds 1977 for a popular review of this concept). There are no conventional statistical techniques for testing one-to-
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