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Year: 2020, Volume: 20, Number: 4
... upstream and faults, using a short circuit calculation, the fault current for downstream networks at the ASCC location, respectively. all OCRs and the values of „t ... ASCC setting for upstream fault mode When a short circuit fault occurs at the upstream network, the fault current with and without ASCC can be calculated Figure 5. ...
Year: 2020, Volume: 20, Number: 4
... servers and targets (objects are immobile and transactions either move or use small-to-medium edge networks. Besides intelligent embedded remote procedure calls) [15], (ii ... Internet of Things, it can be also used in and transactions are fixed to network nodes) [16-20], and a wide range of application domains, ...
63. Gaussian Source Coding using a Simple Switched Quantization Algorithm and Variable Length Codewords
Year: 2020, Volume: 20, Number: 4
... ], multi-agent systems [14], analog-to-digital converters [15] or neural networks [16]. Scalar quantization is a process where real-valued The emphasis in ... the switched algorithm with the proposed the Gaussian pdf, e.g. weights in neural network. quantizer (N1= 32, N2= 64, c= 3.74 ...
Year: 2020, Volume: 20, Number: 4
... problems," IEEE Proceedings of ICNN'95- International Conference on Neural Trans. Power Syst., vol. 25, pp. 1064 €“ 1077, 2010. Networks Perth, WA, Australia, pp. 1942-1948, 1995. doi:10.1109/TPWRS.2009.2034525 doi:10.1109/ICNN.1995.488968 [10] T. Yalcinoz, ...
Year: 2020, Volume: 20, Number: 3
... which enables computers to see preserving smoothing results for a wide range of image objects in the same way as humans. contents. They trained a deep convolutional neural network RealSense cameras have three lenses: a conventional to design a loss function for edge-preserving smoothing RGB (Red Green Blue) camera, an infrared (IR) ...
Year: 2020, Volume: 20, Number: 3
... Cooper, "Introduction to queueing theory", 2nd Ed. New York, Networks, vol. IV, pp. 1942 €“ 1948, 1995, doi ... study, that is to find the balance between the negative selection, and immune network algorithms. In this patient admission and costs for refusing him, we had ...
Year: 2020, Volume: 20, Number: 3
... solution using a double feed induction ƒ M2 ƒ d irq M sr motor (DFIM) [1, 6]. The stator is feed by a fixed network Vrq € ƒ Rr € sr ƒ irq € Lr € V sq € ƒ ƒ Lr Tr ƒ dt Lr and the rotor by a variable supply ...
Year: 2020, Volume: 20, Number: 3
... MRI images and deep classification models. The basic functionality of both DCNN convolutional neural networks for classification. In the and VCNN follow convolutional neural network model. preprocessing ... The author in [1] diagnosis. In this research, Deep Convolution Neural Network classified the different stages of Alzheimer's disease using (DCNN) and VGG-16 inspired ...
Year: 2020, Volume: 20, Number: 3
... detected? d) Is it possible to improve the performance of 7641(20020315)3 :3 <285::AID-CPHC285>3.0.CO;2-A artificial neural networks with the controlled addition of [18] P. Hanggi, M. E. Inchiosa, D. Fogliatti, A. R. Bulsara, " ...
Year: 2020, Volume: 20, Number: 3
... as well. System level simulators are II. METHODOLOGY mostly oriented towards modeling the network behavior of the power converter and use numerical integration methods A. Methods, ... J. S. Shen and P. A. Hsiung, "Dynamic Reconfigurable Network-on- 10.1109/IEVC.2012.6183208. chip Design: Innovations for Computational Processing and [ ...
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