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A Multistage Deep Learning Algorithm for Detecting Arrhythmia

ALLAHVERDİ, Novruz | KUTLU, Yakup | ALTAN, Gökhan

Deep Belief Networks (DBN) is a deep learning algorithm that has both greedy layer-wise unsupervised and supervised training. Arrhythmia is a cardiac irregularity caused by a problem of the heart. In this study, a multi-stage DBN classification is proposed for achieving the efficiency of the DBN on arrhythmia disorders. Heartbeats from the MITBIH Arrhythmia database are classified into five groups which are recommended by AAMI. The Wavelet packet decomposition, higher order statistics, morphology and Discrete Fourier transform techniques were utilized to extract features. The classification pe ...Daha fazlası

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Statistical Analysis of Electromagnetic Structures and Antennas Using the Polynomial Chaos Expansion Method

AÇIKGÖZ, Hulusi | MITTRA, Raj

Electromagnetic (EM) structures such as antennas, resonators, are widely used in EM communication systems. It is not uncommon to find that the performance characteristics of these structures are not as expected because of the uncertainties introduced during the manufacturing process. These uncertainties may arise, for instance, from variations of the dimensions of the device or its material properties, e.g., permittivity and permeability. A statistical tool based on the use of the Polynomial Chaos Expansion (PCE) technique is proposed in this work. The results of investigation of two EM struct ...Daha fazlası

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Statistical Investigation of a Dual-Band Wearable Patch Antenna

AÇIKGÖZ, Hulusi | MITTRA, Raj

We present a stochastic modeling strategy for studying a wearable textile antenna under different manufacturing conditions. The studied device is a patch antenna designed for energy harvesting, which operates at the GSM and DCS bands, 900MHz and 1800MHz, respectively. The performance of the conductive patch printed on a textile substrate backed by a ground plane is investigated. A stochastic approach is employed to assess the variability of the observable because of the uncertainties introduced in the manufacturing process, such as laminating and embroidering.

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Efficiency Enhancement of Bowtie Photomixer Antenna by Using Resistively Loaded Line

YILMAZ, Adem | ÜNLÜ, Mehmet

In this paper, the effects of the DC bias lines on bowtie terahertz photomixer antenna are investigated, and a method, namely resistively loaded lines (RLL), is proposed to compensate the effects of the DC bias lines. The numerical results of the bowtie antenna show that RLL almost removes the effects of the bias lines compared to that of the commonly used bias line types, such as coplanar stripline and photonic bandgap type bias lines.

6698 sayılı Kişisel Verilerin Korunması Kanunu kapsamında yükümlülüklerimiz ve cerez politikamız hakkında bilgi sahibi olmak için alttaki bağlantıyı kullanabilirsiniz.

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