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search.filters.applied.f.publicationcategory: Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı × Konu: Trellis codes ×

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    Driver recognition using gaussian mixture models and decision fusion techniques
    (Springer-Verlag Berlin, 2008) Benli, Kristin Surpuhi; Düzağaç, Remzi; Eskil, Mustafa Taner
    In this paper we present our research in driver recognition. The goal of this study is to investigate the performance of different classifier fusion techniques in a driver recognition scenario. We are using solely driving behavior signals such as break and accelerator pedal pressure, engine RPM, vehicle speed; steering wheel angle for identifying the driver identities. We modeled each driver using Gaussian Mixture Models, obtained posterior probabilities of identities and combined these scores using different fixed mid trainable (adaptive) fusion methods. We observed error rates is low as 0.35% in recognition of 100 drivers using trainable combiners. We conclude that the fusion of multi-modal classifier results is very successful in biometric recognition of a person in a car setting.
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    Hızlı sönümlemeli kanallarda yeni bir uzay-zaman-frekans kodlamalı OFDM sistem tasarımı
    (IEEE, 2004) Oğuz, Onur; Aygölü, Hasan Ümit; Panayırcı, Erdal
    Bu çalışmada, frekans seçici hızlı sönümlemeli kanallarda telsiz iletişim için bir uzay-zaman-frekans çeşitlemesi yöntemi önerilmiştir. Önerilen yöntem, OFDM tekniğini kullanarak frekans seçici kanalı uygun hale getirdikten sonra sırasıyla dik uzay-frekans ve dik uzay-zaman blok kodlama uygulayarak uzay-zaman-frekans çeşitlemesi sağlamaktadır. Elde edilen sistemin başarımını arttırmak üzere sisteme uygun bu kafes kodlama tekniği araştırılmış ve uygun kafes yapısının oluşturulması için yeni kriterler ortaya çıkarılmıştır. Oluşan sistemin başarımını, bilgisayar benzetimleriyle incelenmiş ve var olan yöntemlerle karşılaştırılmıştır.
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    EM-Based sequence estimation for wireless systems with orthogonal transmit diversity
    (IEEE, 2003) Panayırcı, Erdal; Aygölü, Hasan Ümit; Pusane, Ali Emre
    In this paper, an optimum sequence estimation algorithm for wireless systems with Alamouti's two transmitter diversity in the presence of multipath fading is proposed. The algorithm is based on a jointly iterative channel and sequence estimation according to the maximum likelihood (ML) criterion, using the Expectation-Maximization (EM) algorithm employing M-PSK modulation scheme with additive Gaussian noise. The discrete multipath channel is represented in terms of the channel gains from each transmit antenna to the receive antenna. EM algorithm derived estimates jointly the complex channel parameters of each channel And the data sequence transmitted, iteratively, which converges to the true ML solution. The channel estimation is achieved in a simple way through the iterative equations by decoupling of the signals transmitted from different antennas. The algorithm is applied to the trellis coded modulation systems and efficiency of the algorithm proposed has been shown by the computer simulations. Simulation results show that the EM algorithm converges quickly for fast fading channels. The performance of the EM-based decoder approaches that of the ML receiver which has perfect knowledge of the channel.