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Titlebook: Neugeborenenintensivpflege; Grundlagen und Richt Michael Obladen,Georg Bein (ehem. Direktor),Rolf F Book 20026th edition Springer-Verlag Be

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M. Obladener different regions (irregular or frequency variant behavior of the signal) which need to be estimated properly for an improved classification [1, 2, 3]. Multispectral remote sensing (RS) image data are basically complex in nature, which have both spectral features with correlated bands and spatial
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M. Obladener different regions (irregular or frequency variant behavior of the signal) which need to be estimated properly for an improved classification [1, 2, 3]. Multispectral remote sensing (RS) image data are basically complex in nature, which have both spectral features with correlated bands and spatial
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M. Obladenrence System (FIS) and the Risk Priority Number (RPN) model. Two main limitations are: (1) it is difficult and impractical to form a complete fuzzy rule base when the number of required rules is large; and (2) fulfillment of the monotonicity property is a difficult problem. In this paper, a new fuzz
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M. Obladenace (BCI). To identify individual source contribution into EEG recorded during the training, Independent Component Analysis (ICA) was employed. Those independent components, for which the BCI system classification accuracy was at maximum, were treated as relevant to performing the motor imagerytasks
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G. Beinn (PSO) is presented in this paper. PSO is a method for optimizing hard numerical functions on metaphor of social behavior of flocks of birds and schools of fish. A swarm consists of individuals, called particles, which change their positions over time. Each particle represents a potential solution
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J. Waldschmidtn (PSO) is presented in this paper. PSO is a method for optimizing hard numerical functions on metaphor of social behavior of flocks of birds and schools of fish. A swarm consists of individuals, called particles, which change their positions over time. Each particle represents a potential solution
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J. Waldschmidt of problems simultaneously, it partitions the datasets into cluster of objects that are similar to each other and describes the clusters by cluster prototypes to provide some information about the distribution of the data. In most of the cases these cluster prototypes describe the clusters as simpl
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