Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
https://hdl.handle.net/11147/11
Collection of Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği Bölümü koleksiyonu2019-11-14T23:35:20ZAmpirik Mod Ayrışımı ile bilişsel radar Bayes Hedef Takipçisine işlerlik kazandırılması
https://hdl.handle.net/11147/7322
Ampirik Mod Ayrışımı ile bilişsel radar Bayes Hedef Takipçisine işlerlik kazandırılması
Güntürkün, Ulaş
Bilişsel radar alıcısının merkez ünitesi niteliğindeki
Bayes Hedef Takipçisine (BHT) işlerlik kazandıran Ampirik Mod Ayrışımı (AMA) tekniğine dayalı bir metot sunulmuştur. Tüm Bayes temelli metotlarda olduğu gibi Bayes hedef takipçisinin performansı
da ortam hakkında isabetli ön bilginin varlığına önemli ölçüde bağımlıdır. Bu nedenle, BHT’nin gereksinim duyduğu ön bilgiyi sağlamak üzere tasarlanan Radar Ortam Çözümcüsü (ROÇ), bilişsel radar için kritik bir öneme sahiptir. Bu çalışmada
sunulan metot, AMA tekniğinin fraktal süreçler için gösterdiği istatistiksel özelliklere dayalı olup, genel ROÇ tasarımını tamamlar niteliktedir. Özel olarak, ham radar verisi, öncelikle AMA yöntemiyle içkin Mod Fonksiyonlarına (IMF) ayrılmıştır. Faz
uyumlu bir radarla alınan ve fraktal Gauss niteli˘gine sahip deniz yankısının IMF enerji istatistiklerine dayalı bir “Sıfır Hipotezi” türetilmiştir. Ham radar verisi, bu hipotezin kabul veya reddine bağlı olarak gruplanan IMF’lerin kısmi bir bindirmesi olarak rafine edilmiştir. Böylelikle hedef içeren duruma yönelik
olabilirlik fonksiyonu, yalnızca deniz yankısı içeren olabilirlik fonksiyonundan istatistiksel ölçülerle çok daha ayırt edilebilir bir hale getirilmiştir. Sonuç olarak, ortamdan alınan ölçümler BHT’nin kullanımına uygun bir forma dönüştürülmüştür. Metodun performansı, canlı kaydedilmiş McMaster IPIX veri tabanı kullanılarak görsel olarak sergilenmiş ve Kullback–Leibler uzaklığıyla nicelenmiştir.; A method based on the Empirical Mode Decomposition (EMD) is addressed for the facilitation of Bayesian Target Tracker (BTT), the central unit for a Cognitive Radar receiver. As in all Bayesian methods, the BTT heavily relies on the availability of accurate a priori information on the operating conditions. To this end, a Radar Scene Analyzer (RSA) is a crucial part of a Cognitive Radar in that it provides the a priori knowledge the BTT requires. Herein, a complementary RSA structure is developed building on the statistical properties of the EMD on fractal Gaussian processes. In particular, EMD is applied to the measured radar data, yielding the Intrinsic Mode Functions (IMF). At absence of a target, coherent sea clutter data exhibit fractal Gaussian character, which manifests itself in the second order statistical properties of IMFs. This is exploited to form a "Null Hypothesis", which is used for grouping the IMFs into two subsets on the basis of an accept/reject procedure. Hence the refinements of the raw radar returns are constructed from the superpositions of accepted or rejected IMFs. Effectively, the likelihood function for the target+clutter case can be remarkably distinguished in statistical terms from that for the clutter-Alone case, so as to facilitate the Bayesian target tracker. The performance of the method is visually illustrated using the live-recorded McMaster IPIX dataset, and numerically assessed by the Kullback-Leibler distance.
21st Signal Processing and Communications Applications Conference, SIU 2013; Haspolat; Turkey; 24 April 2013 through 26 April 2013
2013-01-01T00:00:00ZHigh-speed imaging in noncontact atomic force microscopy
https://hdl.handle.net/11147/7321
High-speed imaging in noncontact atomic force microscopy
Balantekin, Müjdat
We analyze the high-speed operating method that we recently developed to be used in noncontact atomic force microscopes (AFM). We simulated the method on various samples and it is shown that the method can minimize the time spent for noncontact AFM imaging experiments. The initial simulation results showed that even with an ordinary AFM cantilever imaging speeds faster than 10 frames/second can be achieved.
Nanotechnology 2013: Advanced Materials, CNTs, Particles, Films and Composites - 2013 NSTI Nanotechnology Conference and Expo, NSTI-Nanotech 2013; Washington, DC; United States; 12 May 2013 through 16 May 2013
2013-01-01T00:00:00Z2-D thresholding of the connectivity map following the multiple sequence alignments of diverse datasets
https://hdl.handle.net/11147/7319
2-D thresholding of the connectivity map following the multiple sequence alignments of diverse datasets
Doğan, Tunca; Karaçalı, Bilge
Multiple sequence alignment (MSA) is a widely used method to uncover the relationships between the biomolecular sequences. One essential prerequisite to apply this procedure is to have a considerable amount of similarity between the test sequences. It's usually not possible to obtain reliable results from the multiple alignments of large and diverse datasets. Here we propose a method to obtain sequence clusters of significant intragroup similarities and make sense out of the multiple alignments containing remote sequences. This is achieved by thresholding the pairwise connectivity map over 2 parameters. The first one is the inferred pairwise evolutionary distances and the second parameter is the number of gapless positions on the pairwise comparisons of the alignment. Threshold curves are generated regarding the statistical parameter values obtained from a shuffled dataset and probability distribution techniques are employed to select an optimum threshold curve that eliminate as much of the unreliable connectivities while keeping the reliable ones. We applied the method on a large and diverse dataset composed of nearly 18000 human proteins and measured the biological relevance of the recovered connectivities. Our precision measure (0.981) was nearly 20% higher than the one for the connectivities left after a classical thresholding procedure displaying a significant improvement. Finally we employed the method for the functional clustering of protein sequences in a gold standard dataset. We have also measured the performance, obtaining a higher F-measure (0.882) compared to a conventional clustering operation (0.827).
10th IASTED International Conference on Biomedical Engineering, BioMed 2013; Innsbruck; Austria; 13 February 2013 through 15 February 2013
2013-01-01T00:00:00ZMeasure of covertness based on the imperfect synchronization of an eavesdropper in Random Communication Systems
https://hdl.handle.net/11147/7226
Measure of covertness based on the imperfect synchronization of an eavesdropper in Random Communication Systems
Ahmed, Areeb; Savacı, Ferit Acar
Random Communication Systems (RCSs) given in the literature have assumed perfectly synchronized transmitter and receiver. However in this paper, instead of assuming perfect synchronization approach in RCSs, the effects of imperfect synchronization (IS) on Skewed Alpha-Stable Noise Shift Keying (SkaS-NSK) based RCS have been observed through simulations. The Bit Error Rate (BER) performance of the eavesdropper with respect to his synchronization error in SkaS-NSK based RCS, has been analyzed. An expression for the probability of an eavesdropper to decode the binary information (i.e., Eavesdropping Probability) in SkaS-NSK based RCS, has been derived. The criterion (i.e., Covertness Value) to measure the covertness level of RCSs has also been proposed. The BER performance of an eavesdropper provides an approximate margin of synchronization error if it can be overcome by an eavesdropper then he can achieve the decoding (i.e., eavesdropping) process.
10th International Conference on Electrical and Electronics Engineering, ELECO 2017; Bursa; Turkey; 29 November 2017 through 2 December 2017
2018-01-01T00:00:00Z