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Reducing time to market, design cost and fast developing, prototyping and testing of embedded industrial and automation models are very interesting topics in recent manufacturing and industry methodologies. In recent years, Model driven architecture or engineering methodology has been introduced in the field of software engineering by OMG. This methodology separate platform independent, and platform...
In this paper, we propose a new approach to identify a neuro-fuzzy model. In our approach, data space is partitioned indirectly through a fuzzy clustering method. The clusters are not created directly through spatial features of data points. A gradient vector is defined as major feature of clustering in data space. This feature is estimated for each incoming data points. Creating and updating fuzzy...
One of the bottle-necks of the large-scale FDTD calculation is the data I/O. Although PFS improves the I/O performance it is not always available. Under the computational environment without PVFS and local disks for each PE, limitation on the number of nodes which can produce the output data improves the scalability. HDF5 is compared with the ASCII format and the binary formats from the perspective...
In this paper the locally linear neurofuzzy (LLNF) models with data fusion approach are used to solve the spacecraft attitude estimation problem based on magnetometer sensors and sun sensors observations. LLNF with locally linear model tree (LoLiMoT) algorithm as an incremental learning algorithm have been used several times as a well-known method for nonlinear system identification and estimation...
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