Research Outputs
Permanent URI for this communityhttps://hdl.handle.net/20.500.14288/2
Browse
80 results
Search Results
Publication Metadata only 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; 6647This 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).Publication Metadata only 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; 26207It 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.Publication Metadata only 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; 41624A 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.Publication Open Access A deep learning approach for data driven vocal tract area function estimation(Institute of Electrical and Electronics Engineers (IEEE), 2018) Department of Computer Engineering; Department of Electrical and Electronics Engineering; Erzin, Engin; Asadiabadi, Sasan; Faculty Member; Department of Computer Engineering; Department of Electrical and Electronics Engineering; College of Sciences; Graduate School of Sciences and Engineering; 34503; N/AIn 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.Publication Metadata only A moving window approach for blind equalization using subgradient projections(IEEE, 2004) N/A; N/A; Department of Electrical and Electronics Engineering; Kızılkale, Can; Erdoğan, Alper Tunga; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 41624A novel blind equalization method based on a subgradient search over a convex cost surface is examined under a noisy channel and a modification is proposed. This is an alternative to the existing iterative blind equalization approaches such as Constant Modulus Algorithm (CMA) which mostly suffer from the convergence problems caused by their non-convex cost functions. The proposed method is an iterative algorithm, for both real and complex constellations, with a very simple update rule that minimizes the l(infinity) norm of the equalizer output under a linear constraint on the equalizer coefficients. The subgradient based algorithm has a fast convergence behavior attributed to the convex l(infinity) cost surface. A moving window based approach is used in this algorithm to both decrease algorithm's complexity and increase its immunity to noise. / Bu makalede alt-bayır izdüşümleri kullanılarak yapılan kör eşitleme metodunun gürültülü bir kanal için performansı incelenmiş ve bu performansın arttırılması için bir öneride bulunulmuştur. Bu algoritma daha önce önerilen sabit genlik algoritmasi(CMA) gibi özyineli yöntemlere bir alternatif olarak sunulmaktadır. Bilindiği gibi daha once sunulan algoritmalar dışbükey olmayan maliyet işlevlerinden dolayı yakınsallık problemi yaşamaktadırlar. Önerilen yöntem, hem gerçek hem de karmaşık burçlar (constellation) için, denkleştirici katsayıları üzerindeki doğrusal bir kısıt altında denkleştiricinin çıktısını l(infinity), normunu enküçültme esasına dayalı, basit bi güncelleme yapısına sahip özyinelemeli bir algoritmadır. Bu algoritma l(infinity) maliyet yüzeyinin karakterinden dolayı hızlı yakınsama davranışına sahiptir. Algoritmanin hem karmaşıklığını azaltacak hem de gürültüye karşı bağışıklığını yükseltecek hareketli pencereye dayalı bir yapı kullanılmıştır.Publication Metadata only A new scalable multi-view video coding configuration for robust selective streaming of free-viewpoint TV(IEEE, 2007) Özbek, Nükhet; Tunalı, E. Turhan; Department of Electrical and Electronics Engineering; Tekalp, Ahmet Murat; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 26207Free viewpoint TV (FTV) is a new media format that allows a user to change his/her viewpoint freely. To this effect, multi-view video must be coded to sAtışfy two conflicting requirements: i) achieve high compression efficiency, and ii) allow view switching with low delay. This paper proposes a new encoding configuration for scalable multi-view video coding, which achieves a compromise between the two requirements. In the new scalable multi-view configuration, the base layer is encoded with inter-view prediction at a minimum acceptable quality, while enhancement layers for each view only depend on their respective base layers (with no interview prediction). Thus, the base layer shall be served to all users, while enhancement layers shall be served selectively to users depending on their channel bandwidth and viewing direction. We compare the compression efficiency of the proposed method with those of non-scalable multi-view coding (MVC) and simulcast (H.264/AVC of each view independently) solutions.Publication Metadata only A stochastic framework for rate-distortion optimized video coding over error-prone networks(IEEE-Inst Electrical Electronics Engineers Inc, 2007) Harmanci, Oztan; Department of Electrical and Electronics Engineering; Tekalp, Ahmet Murat; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 26207This paper proposes a complete stochastic framework for RD optimal encoder design for video over error-prone networks, which applies to any motion-compensated predictive video codec. The distortion measure has been taken as the mean square error over an ensemble of channels given an estimate of the instantaneous packet loss probability. We show that 1) the optimal motion compensated prediction, in the MSE sense, requires computation of the expected value of the reference frames, and 2) calculation of the MSE (distortion measure) requires computation of the second moment of the reference frames. We propose a recursive procedure for the computation of both the expected value and second moment of the reference frames, which are together called the stochastic frame buffer. Furthermore, we propose a stochastic RD optimization method for selection of the optimal macroblock mode and motion vectors given the instantaneous packet loss probability. If available, channel feedback can also be incorporated into the proposed stochastic framework. However, the proposed framework does not require a feedback channel to exist, and when it exists, it does not have to be lossless. In the absence of any packet losses, the proposed stochastic framework reduces to the well-known deterministic RD optimization procedures. One possible application of the optimal stochastic framework would be for multicast streaming to an ensemble of receivers. Experimental results indicate that the proposed framework outperforms other available error tracking and control schemes.Publication Metadata only Adaptive peer-to-peer video streaming with optimized flexible multiple description coding(IEEE, 2006) Akyol, Emrah; Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Tekalp, Ahmet Murat; Civanlar, Mehmet Reha; Faculty Member; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; College of Engineering; 26207; 16372Efficient peer-to-peer (P2P) video streaming is a challenging task due to time-varying nature of both the number of available peers and network/channel conditions. To this effect, we propose a receiver driven P2P streaming system which utilizes a flexible scalable multiple description coding method [1], where the number of base and enhancement descriptions, and the rate and redundancy level of each description can be adapted on the fly. The optimization of the parameters of the proposed MDC scheme according to network conditions is discussed within the context of the proposed adaptive P2P streaming framework, where the number and quality of available streaming peers/paths are a priori unknown and vary in time. Experimental results, by means of NS-2 network simulation of a P2P video streaming system, show that adaptation of the number, type, and rate of descriptions and the redundancy level of each description according to network conditions yields significantly superior performance when compared to MDC schemes using a fixed number of descriptions/layers with fixed rate and redundancy level.Publication Metadata only An adaptive paraunitary approach for blind equalization of all equalizable MIMO channels(IEEE, 2006) Department of Electrical and Electronics Engineering; Erdoğan, Alper Tunga; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 41624We introduce a novel adaptive paraunitary approach to be used for the blind deconvolution of all deconvolvable MIMO mixing systems with memory. The proposed adaptive approach is based on the use of alternating projections technique for the enforcement of the paraunitary constraint. The use of this approach enables extension of various instantaneous Blind Source Separation (BSS) approaches to handle the convolutive BSS case. Three such methods, namely FastICA, Multi User Kurtosis and BSS for Bounded Magnitude signals are provided to illustrate the use of this approach.Publication Metadata only An audio-driven dancing avatar(Springer, 2008) Balci, Koray; Kizoglu, Idil; Akarun, Lale; Canton-Ferrer, Cristian; Tilmanne, Joelle; Bozkurt, Elif; Erdem, A. Tanju; Department of Computer Engineering; N/A; N/A; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Yemez, Yücel; Ofli, Ferda; Demir, Yasemin; Erzin, Engin; Tekalp, Ahmet Murat; Faculty Member; PhD Student; Master Student; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; 107907; N/A; N/A; 34503; 26207We present a framework for training and synthesis of an audio-driven dancing avatar. The avatar is trained for a given musical genre using the multicamera video recordings of a dance performance. The video is analyzed to capture the time-varying posture of the dancer's body whereas the musical audio signal is processed to extract the beat information. We consider two different marker-based schemes for the motion capture problem. The first scheme uses 3D joint positions to represent the body motion whereas the second uses joint angles. Body movements of the dancer are characterized by a set of recurring semantic motion patterns, i.e., dance figures. Each dance figure is modeled in a supervised manner with a set of HMM (Hidden Markov Model) structures and the associated beat frequency. In the synthesis phase, an audio signal of unknown musical type is first classified, within a time interval, into one of the genres that have been learnt in the analysis phase, based on mel frequency cepstral coefficients (MFCC). The motion parameters of the corresponding dance figures are then synthesized via the trained HMM structures in synchrony with the audio signal based on the estimated tempo information. Finally, the generated motion parameters, either the joint angles or the 3D joint positions of the body, are animated along with the musical audio using two different animation tools that we have developed. Experimental results demonstrate the effectiveness of the proposed framework.