5 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 5 / 5
Yayın Generic BER analysis of VLC channels impaired by 3D user-mobility and imperfect CSI(Institute of Electrical and Electronics Engineers Inc., 2021-07) Reddy Sekhar, K.; Miramirkhani, Farshad; Mitra, Rangeet; Turlapaty, Anish ChandVisible light communications (VLC) has emerged as a high-speed, low-cost, and green supplement for the existing radio frequency (RF) based infrastructures. However, the performance of VLC based systems is found to degrade significantly due to detrimental outages caused by non-negligible variations in the VLC channel-gain, that are jointly induced by radial user-mobility and random photodetector-orientation (together designated as 3D mobility in this letter). In addition to the 3D user-mobility mentioned above, the performance of VLC based systems is further limited by imperfect channel-state information (CSI). Such degradations in the VLC-link caused by the aforementioned factors necessitate the quantification of performance-metrics for further benchmarking/receiver-design. In this work, an analytical expression for bit-error rate (BER) is derived for a single LED indoor VLC system considering the radial user-mobility, random receiver orientation, and imperfect CSI altogether. Further, the derived BER expressions are validated using computer-simulations using typical VLC channel models from the literature. A close agreement between the analytical and the simulated BER is observed, which verifies the accuracy of the presented analysis.Yayın Normal forms and nonlocal chaotic behavior in Sprott systems(Pergamon-Elsevier Science, 2003-06) Perdahçı, Nazım Ziya; Hacınlıyan, Avadis SimonThe Sprott systems are used as benchmarks for investigating the applicability of the normal form transformation in estimating nonlocal properties of attractors such as positive and zero Liapunov exponents. Possibility of a relation between complex conjugate eigenvalue pairs and zero Liapunov exponents; conditions under which the normal form expansion can represent the attractor; an averaging relation for the largest Liapunov exponent based on this representation are studied. Nonlinear transformations that can change the order of a resonance are considered. In spite of their convergence problems, it is seen that the normal form approach can give reasonable estimates of nonlocal properties of attractors near Hopf bifurcations.Yayın Improving age of information in random access channels(Institute of Electrical and Electronics Engineers Inc., 2020-07) Atabay, Doğa Can; Uysal, Elif; Kaya, OnurWe study Age of Information (AoI) in a random access channel where a number of devices try to send status updates over a common medium. Assuming a time-slotted scenario where multiple transmissions result in collision, we propose a threshold-based lazy version of Slotted ALOHA and derive the time average AoI achieved by this policy. We demonstrate that the average AoI performance of the lazy policy is significantly better than Slotted ALOHA, and close to the ideal round robin benchmark.Yayın Analysis of single image super resolution models(IEEE, 2022-11-18) Köprülü, Mertali; Eskil, Mustafa TanerImage Super-Resolution (SR) is a set of image processing techniques which improve the resolution of images and videos. Deep learning approaches have made remarkable improvement in image super-resolution in recent years. This article aims and seeks to provide a comprehensive analysis on recent advances of models which has been used in image superresolution. This study has been investigated over other essential topics of current model problems, such as publicly accessible benchmark data-sets and performance evaluation measures. Finally, The study concluded these analysis by highlighting several weaknesses of existing base models as their feeding strategy and approved that the training technique which is Blind Feeding, which led several model to achieve state-of-the art.Yayın TurkEmbed: Turkish embedding model on natural language inference & sentence text similarity tasks(Institute of Electrical and Electronics Engineers Inc., 2025) Ezerceli, Özay; Gümüşçekiçci, Gizem; Erkoç, Tuğba; Özenç, BerkeThis paper introduces TurkEmbed, a novel Turkish language embedding model designed to outperform existing models, particularly in Natural Language Inference (NLI) and Semantic Textual Similarity (STS) tasks. Current Turkish embedding models often rely on machine-translated datasets, potentially limiting their accuracy and semantic understanding. TurkEmbed utilizes a combination of diverse datasets and advanced training techniques, including matryoshka representation learning, to achieve more robust and accurate embeddings. This approach enables the model to adapt to various resource-constrained environments, offering faster encoding capabilities. Our evaluation on the Turkish STS-b-TR dataset, using Pearson and Spearman correlation metrics, demonstrates significant improvements in semantic similarity tasks. Furthermore, TurkEmbed surpasses the current state-of-the-art model, Emrecan, on All-NLI-TR and STS-b-TR benchmarks, achieving a 1-4% improvement. TurkEmbed promises to enhance the Turkish NLP ecosystem by providing a more nuanced understanding of language and facilitating advancements in downstream applications.
