Titlebook: Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis; Marcin Mrugalski Book 2014 Springer International Publishi

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Studies in Computational Intelligencehttp://image.papertrans.cn/a/image/146038.jpg

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Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis978-3-319-01547-7Series ISSN 1860-949X Series E-ISSN 1860-9503

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Bioclimatic Design and Environmental Impactg the system behaviour. The scope of applications of mathematical models in the contemporary industrial systems is extremely broad and includes the FDI [1, 3, 4, 5, 6] and Fault-Tolerant Control (FTC) [63, 64, 65, 66, 67] among others. In the case of a non-linear dynamic system identification the AN

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Pulsations in Technology Innovationh between the model and the system being considered [10]. It follows from the fact that the effectiveness of the fault detection systems depends on the uncertainty of the neural model and disturbances existing in the industrial system. In the case of the most widely applied the ANNs such as the MLP,

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Bioclimatic Architecture in Warm Climatesagnosis methods. The reliable fault diagnosis is expected even in uncertain conditions when measurement noises, disturbances and model uncertainty could appear. The application of the analytical redundancy on the basis of mathematical models opposite to hardware one in the fault detection and isolat

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