Yazar "Tagluk M.E." seçeneğine göre listele

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    Learning with classical conditioning
    (IEEE Computer Society, 2014) Ertugrul O.F.; Tagluk M.E.
    Behavioral learning theory evaluates human's learning process in terms of observable stimulus and responses. One of the behavioral learning methods is the classical conditioning. The classical conditioning theory proposed by Pavlov concerns the analyses of conditioning a response with a neutral stimulus, inspiring from the relation between natural stimulus and response. In this study the classical conditioning theory is modeled in real-time. The viability of the proposed method to basic principles of classical conditioning, based on stimulus-response relations was achieved and compared to the available computational methods. © 2014 IEEE.
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    A preliminary investigation of receiver models in molecular communication via diffusion
    (Institute of Electrical and Electronics Engineers Inc., 2017) Isik I.; Yilmaz H.B.; Tagluk M.E.
    Molecular Communication (MC) is a new multidisciplinary subject concerning medicine, biology, and communication engineering. MC concept is introduced for modeling of communication of nano/micro scale devices. In MC systems, chemical signals carrying information in gaseous or liquid media are used. Similar to other communication systems, in MC sending information from transmitter to receiver with minimum error is one of the most important goals. In MC systems due to physical characteristics of medium, higher rates of inter symbol interference (ISI) and noise increase error probability. Figures of receiver mechanisms and signal detection techniques are therefore the main factors to be tuned for decreasing error probability. In this view, so far, many receiver models such as reversible adsorption and desorption (A&D), protrusion method, ligand receptor, and linear catalytic or CAT receiver models have been introduced. In this study, these models and the results obtained through their implementation are investigated and briefly reviewed. © 2017 IEEE.
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    Using bispectral analysis in OSAS estimation
    (2010) Sezgin N.; Tagluk M.E.; Akin M.
    In this study the possibility of estimation of Obstractive Sleep Apnea Syndrome (OSAS) through electroensephalographic (EEG) signals using higher order spectra was investigated. Biological structures usually exhibit nonlinear and non-Gaussian distributed characteristics which consequently generate signals embracing nonlinear components as well as phase relations occurring between componets oscillating in different frequencies whose phase couples together over a limited period of time, so called Quadratic Phase Coupling (QPC). In this case the second order power spectrum may not reflect the real characteristics of the biological system. Therefore, the bispectrum analysis was achieved to characterize the nonlinearities and QPCs in OSAS and normal EEGs. Through this analysis the differences in OSAS EEG and normal EEG were comparatively uncovered. From the analysis it was understood that the bispectrum can be used for estimation of OSAS from patients' EEG signals. ©2010 IEEE.