Research Outputs

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Now showing 1 - 10 of 263
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    300 GHz broadband transceiver design for low-THz band wireless communications in indoor internet of things
    (Ieee, 2017) N/A; Department of Electrical and Electronics Engineering; N/A; Department of Electrical and Electronics Engineering; Khalid, Nabil; Abbasi, Naveed Ahmed; Akan, Özgür Barış; Researcher; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 6647
    This paper presents the architectural design of a 300 GHz transceiver system that can be used to explore the high speed communication opportunities offered by the Terahertz (THz) band for advanced applications of Internet-of-Things (IoT). We use low cost industry ready components to prepare a fully customizable THz band communication system that provides a bandwidth of 20 GHz that is easily extendable up to 40 GHz. Component parameters arc carefully observed and used in simulations to predict the system performance while the compatibility of different components is ensured to produce a reliable design. Our results show that the receiver provides a conversion gain of 51 dB with a noise figure (NE) of 9.56 dB to achieve a data rate of 90.31 Gbps at an operation range of 2 meters, which is suitable for high speed indoor IoT nodes. The flexible design of the transceiver provides groundwork for further research efforts in 5G IoT applications and pushing boundaries of throughputs to the order of terabits per second (Tbps).
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    3D display dependent quality evaluation and rate allocation using scalable video coding
    (Ieee, 2009) N/A; N/A; Department of Electrical and Electronics Engineering; Saygılı, Görkem; Gürler, Cihat Göktuğ; Tekalp, Ahmet Murat; Master Student; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 26207
    It is well known that the human visual system can perceive high frequency content in 3D, even if that information is present in only one of the views. Then, the best 3D perception quality may be achieved by allocating the rates of the reference (right) and auxiliary (left) views asymmetrically. However the question of whether the rate reduction for the auxiliary view should be achieved by spatial resolution reduction (coding a downsampled version of the video followed by upsampling after decoding) or quality (QP) reduction is an open issue. This paper shows that which approach should be preferred depends on the 3D display technology used at the receiver. Subjective tests indicate that users prefer lower quality (larger QP) coding of the auxiliary view over lower resolution coding if a "full spatial resolution" 3D display technology (such as polarized projection) is employed. On the other hand, users prefer lower resolution coding of the auxiliary view over lower quality coding if a "reduced spatial resolution" 3D display technology (such as parallax barrier - autostereoscopic) is used. Therefore, we conclude that for 3D IPTV services, while receiving full quality/resolution reference view, users should subscribe to differently scaled versions of the auxiliary view depending on their 3D display technology. We also propose an objective 3D video quality measure that takes the 3D display technology into account.
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    3D model retrieval using probability density-based shape descriptors
    (IEEE Computer Society, 2009) Akgul, Ceyhun Burak; Sankur, Buelent; Schmitt, Francis; Department of Computer Engineering; Yemez, Yücel; Faculty Member; Department of Computer Engineering; College of Engineering; 107907
    We address content-based retrieval of complete 3D object models by a probabilistic generative description of local shape properties. The proposed shape description framework characterizes a 3D object with sampled multivariate probability density functions of its local surface features. This density-based descriptor can be efficiently computed via kernel density estimation (KDE) coupled with fast Gauss transform. The nonparametric KDE technique allows reliable characterization of a diverse set of shapes and yields descriptors which remain relatively insensitive to small shape perturbations and mesh resolution. Density-based characterization also induces a permutation property which can be used to guarantee invariance at the shape matching stage. As proven by extensive retrieval experiments on several 3D databases, our framework provides state-of-the-art discrimination over a broad and heterogeneous set of shape categories.
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    3D progressive compression with octree particles
    (Akademische Verlagsgesellsch Aka Gmbh, 2002) Schmitt, Francis; Department of Computer Engineering; N/A; Yemez, Yücel; Faculty Member; Department of Computer Engineering; College of Engineering; N/A; 107907; N/A
    This paper improves the storage efficiency of the progressive particle-based modeling scheme presented in [14, 15] by using entropy coding techniques. This scheme encodes the surface geometry and attributes in terms of appropriately ordered oc-tree particles, which can then progressively be decoded and rendered by the-viewer by means of a fast direct triangulation technique. With the introduced entropy coding technique, the bitload of the multi-level representation for geometry encoding reduces to 9-14 bits per particle (or 4.5-7 bits per triangle) for 12-bit quantized geometry.
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    3D shape correspondence by isometry-driven greedy optimization
    (IEEE Computer Soc, 2010) N/A; Department of Computer Engineering; Sahillioğlu, Yusuf; Yemez, Yücel; PhD Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; 215195; 107907
    We present an automatic method that establishes 3D correspondence between isometric shapes. Our goal is to find an optimal correspondence between two given (nearly) isometric shapes, that minimizes the amount of deviation from isometry. We cast the problem as a complete surface correspondence problem. Our method first divides the given shapes to be matched into surface patches of equal area and then seeks for a mapping between the patch centers which we refer to as base vertices. Hence the correspondence is established in a fast and robust manner at a relatively coarse level as imposed by the patch radius. We optimize the isometry cost in two steps. in the first step, the base vertices are transformed into spectral domain based on geodesic affinity, where the isometry errors are minimized in polynomial time by complete bipartite graph matching. the resulting correspondence serves as a good initialization for the second step of optimization in which we explicitly minimize the isometry cost via an iterative greedy algorithm in the original 3D Euclidean space. We demonstrate the performance of our method on various isometric (or nearly isometric) pairs of shapes for some of which the ground-truth correspondence is available.
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    3D Shape recovery and tracking from multi-camera video sequences via surface deformation
    (IEEE, 2006) Skala, V.; N/A; Department of Computer Engineering; Sahillioğlu, Yusuf; Yemez, Yücel; PhD Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; 215195; 107907
    This paper addresses 3D reconstruction and modeling of time-varying real objects using multicamera video. The work consists of two phases. In the first phase, the initial shape of the object is recovered from its silhouettes using a surface deformation model. The same deformation model is also employed in the second phase to track the recovered initial shape through the time-varying silhouette information by surface evolution. The surface deformation/evolution model allows us to construct a spatially and temporally smooth surface mesh representation having fixed connectivity. This eventually leads to an overall space-time representation that preserves the semantics of the underlying motion and that is much more efficient to process, to visualize, to store and to transmit.
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    A blind separation approach for magnitude bounded sources
    (IEEE, 2005) Department of Electrical and Electronics Engineering; Erdoğan, Alper Tunga; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 41624
    A novel blind source separation approach for channels with and without memory is introduced. The proposed approach makes use of pre-whitening procedure to convert the original convolutive channel into a lossless and memoryless one. Then a blind subgradient algorithm, which corresponds to an l(infinity) norm based criterion, is used for the separation of sources. The proposed separation algorithm exploits the assumed boundedness of the original sources and it has a simple update rule. The typical performance of the algorithm is illustrated through simulation examples where separation is achieved with only small numbers of iterations.
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    A classification of concurrency bugs in java benchmarks by developer intent
    (Association for Computing Machinery (ACM), 2006) Department of Computer Engineering; Department of Computer Engineering; N/A; Keremoğlu, M. Erkan; Taşıran, Serdar; Elmas, Tayfun; Researcher; Faculty Member; PhD Student; Department of Computer Engineering; College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; N/A; N/A; N/A
    This work addresses the issue of selecting the formal correctness criterion for a concurrent Java program that best corresponds to the developer's intent. We study a set of concurrency-related bugs detected in Java benchmarks reported in the literature. On these programs, we determine whether race-freedom, atomicity or refinement is the simplest and most appropriate criterion for program correctness. Our purpose is to demonstrate empirically the fact that the appropriate fix for a concurrency error and the selection of a program analysis tool for detecting such an error must be based on the proper expression of the designer's intent using a formal correctness criterion.
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    A deep learning approach for data driven vocal tract area function estimation
    (IEEE, 2018) N/A; Department of Computer Engineering; Asadiabadi, Sasan; Erzin, Engin; PhD Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 34503
    In this paper we present a data driven vocal tract area function (VTAF) estimation using Deep Neural Networks (DNN). We approach the VTAF estimation problem based on sequence to sequence learning neural networks, where regression over a sliding window is used to learn arbitrary non-linear one-to-many mapping from the input feature sequence to the target articulatory sequence. We propose two schemes for efficient estimation of the VTAF; (1) a direct estimation of the area function values and (2) an indirect estimation via predicting the vocal tract boundaries. We consider acoustic speech and phone sequence as two possible input modalities for the DNN estimators. Experimental evaluations are performed over a large data comprising acoustic and phonetic features with parallel articulatory information from the USC-TIMIT database. Our results show that the proposed direct and indirect schemes perform the VTAF estimation with mean absolute error (MAE) rates lower than 1.65 mm, where the direct estimation scheme is observed to perform better than the indirect scheme.
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    A deterministic analysis of an online convex mixture of experts algorithm
    (Institute of Electrical and Electronics Engineers (IEEE), 2015) Özkan, Hüseyin; Dönmez, Mehmet A.; N/A; Tunç, Sait; Master Student; Graduate School of Sciences and Engineering; N/A
    We analyze an online learning algorithm that adaptively combines outputs of two constituent algorithms (or the experts) running in parallel to estimate an unknown desired signal. This online learning algorithm is shown to achieve and in some cases outperform the mean-square error (MSE) performance of the best constituent algorithm in the steady state. However, the MSE analysis of this algorithm in the literature uses approximations and relies on statistical models on the underlying signals. Hence, such an analysis may not be useful or valid for signals generated by various real-life systems that show high degrees of nonstationarity, limit cycles and that are even chaotic in many cases. In this brief, we produce results in an individual sequence manner. In particular, we relate the time-accumulated squared estimation error of this online algorithm at any time over any interval to the one of the optimal convex mixture of the constituent algorithms directly tuned to the underlying signal in a deterministic sense without any statistical assumptions. In this sense, our analysis provides the transient, steady-state, and tracking behavior of this algorithm in a strong sense without any approximations in the derivations or statistical assumptions on the underlying signals such that our results are guaranteed to hold. We illustrate the introduced results through examples.