By Mirsad Hadžikadić, Samir Avdaković
This quantity spans a variety of technical disciplines and applied sciences, together with complicated platforms, biomedical engineering, electric engineering, power, telecommunications, mechanical engineering, civil engineering, and computing device technological know-how. The papers incorporated during this quantity have been provided on the foreign Symposium on leading edge and Interdisciplinary purposes of complex applied sciences (IAT), held in Neum, Bosnia and Herzegovina on June 26 and 27, 2016. This hugely interdisciplinary quantity is dedicated to varied facets and kinds of platforms. structures pondering is essential for effectively construction and figuring out man-made, usual, and social platforms.
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Additional resources for Advanced Technologies, Systems, and Applications
In this paper K = 32 or K = 64 and similarly for Y(i, j). This number is based on two considerations. First, the number of signiﬁcant signature pixels for all targets is K or less. If less than K, we append required number of zeros to the right of the signature. Second, for future research in wavelet domain, we want this number to be a power of 2. Signature numerical values are means along X and Y, X(i, j) and Y(i, j), of pixels gray values from MSTAR data base. Figure 9 shows Zil truck (Target 3) signatures, where the gray scale levels are translated into digital signatures by averaging the gray level values along the X and Y axis.
Visual EEG analysis often does not provide quality conclusions. The GWS presentation of the EEG signal enables excellent observation of activities within the speciﬁc components (delta and theta), and clear distinction between healthy and epileptic children. 5 Further Research At the department of Neuro Pediatricians of the Pediatric Clinic of the University Clinical Centre in Sarajevo it is planned to collect EEG signals on 100 patients. Analysis of Electroencephalogram on Children … 35 Using the same approach (GWS) will be done detailed analysis and will be discussed the possibility of implementing an automatic classiﬁer.
The real quadrant (4 in this case) is determined by analyzing three more signatures shifted 90 degrees from target 50, and situated in quadrants 2, 3 and 4 (Fig. 14). Next we take three synthetic targets from target data base plus a number of additional signatures with poses around signature 50, shift them 90 degrees as well, and compare their signatures with the signatures in Fig. 13. For these comparisons we use several correlation coefﬁcients, namely Pearson, Spearman, Kendal, and also Brownian to identify the target and also right quadrant.
Advanced Technologies, Systems, and Applications by Mirsad Hadžikadić, Samir Avdaković