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Yayın Phased subarray imaging for low-cost, wideband coherent array imaging(IEEE, 2003) Johnson, Jeremy A.; Oralkan, Ömer; Ergün, Arif Sanlı; Demirci, Utkan; Karaman, Mustafa; Khuri-Yakub, Butrus ThomasThe front-end hardware complexity of conventional full phased array (FPA) imaging is proportional to the number of array elements. Phased subarray (PSA) imaging has been proposed as a method of reducing the hardware complexity-and therefore system cost and size-while achieving near-FPA image quality. A new method is presented for designing the subarray-dependent interpolation filters suitable for wideband PSA imaging. The method was tested experimentally using pulse-echo data of a wire target phantom acquired using a 3.2-cm. 128-element capacitive micromachined ultrasonic transducer (CMUT) array with 85% fractional bandwidth at 3 MHz. A specific PSA configuration using seven 32-element subarrays was compared to FPA imaging, representing a 4-fold reduction in front-end hardware complexity and a 43% decrease in frame rate. For targets near the fixed transmit focal distance, the mean 6-dB lateral resolution was identical to that of FPA, the axial resolution improved by 4%, and the SNR decreased by 5 dB. Measurements were repeated for 10 different PSA configurations with subarray sizes ranging from 4 to 60. The lateral and axial resolutions did not vary significantly with subarray size; both the SNR and contrast-to-noise ratio (CNR) improved with increased subarray size.Yayın Soft decision trees(IEEE, 2012) İrsoy, Ozan; Yıldız, Olcay Taner; Alpaydın, Ahmet İbrahim EthemWe discuss a novel decision tree architecture with soft decisions at the internal nodes where we choose both children with probabilities given by a sigmoid gating function. Our algorithm is incremental where new nodes are added when needed and parameters are learned using gradient-descent. We visualize the soft tree fit on a toy data set and then compare it with the canonical, hard decision tree over ten regression and classification data sets. Our proposed model has significantly higher accuracy using fewer nodes.Yayın Decoder-side super-resolution and frame interpolation for improved H.264 video coding(IEEE, 2013) Ateş, Hasan FehmiIn literature decoder-side motion estimation is shown to improve video coding efficiency of both H.264 and HEVC standards. In this paper we introduce enhanced skip and direct modes for H.264 coding using decoder-side super-resolution (SR) and frame interpolation. P-and B-frames are downsampled and H.264 encoded at lower resolution (LR). Then reconstructed LR frames are super-resolved using decoder-side motion estimation. Alternatively for B-frames, bidirectional true motion estimation is performed to synthesize a B-frame from its reference frames. For P-frames, bicubic interpolation of the LR frame is used as an alternative to SR reconstruction. A rate-distortion optimal mode selection algorithm determines for each MB which of the two reconstructions to use as skip/direct mode prediction. Simulations indicate an average of 1.04 dB PSNR improvement or 23.0% bitrate reduction at low bitrates when compared to H.264 standard. Average PSNR gains reach as high as 3.95 dB depending on the video content and frame rate.Yayın Immitance data modelling via linear interpolation techniques(IEEE, 2002) Yarman, Bekir Sıddık Binboğa; Aksen, Ahmet; Kılınç, AliWith the advancement of the manufacturing technologies to produce new generation analog/digital communication systems, immitance data modelling has gained renewed importance in the literature. Specifically, models are utilised for behaviour characterisation, simulation of physical devices or to design sub-systems with active and passive solid-state components. Therefore, in this paper, new computer aided tools are presented to model one port immitance data by means of linear interpolation techniques. It is remarkable to observe that complex electrical behaviour of physical devices can be simulated with the models built utilising the linear interpolation of a few properly selected measured immitance data. An antenna example is presented to exhibit the implementation of the proposed techniques. It is expected that the new modelling tools will be employed to provide initial circuit topologies to the commercially available analysis/simulation and design packages.Yayın Model adaptation for dialog act tagging(IEEE, 2006) Tür, Gökhan; Güz, Ümit; Hakkani Tür, DilekIn this paper, we analyze the effect of model adaptation for dialog act tagging. The goal of adaptation is to improve the performance of the tagger using out-of-domain data or models. Dialog act tagging aims to provide a basis for further discourse analysis and understanding in conversational speech. In this study we used the ICSI meeting corpus with high-level meeting recognition dialog act (MRDA) tags, that is, question, statement, backchannel, disruptions, and floor grabbers/holders. We performed controlled adaptation experiments using the Switchboard (SWBD) corpus with SWBD-DAMSL tags as the out-of-domain corpus. Our results indicate that we can achieve significantly better dialog act tagging by automatically selecting a subset of the Switchboard corpus and combining the confidences obtained by both in-domain and out-of-domain models via logistic regression, especially when the in-domain data is limited.Yayın Immitance data modelling via linear interpolation techniques: a classical circuit theory approach(Wiley-Blackwell, 2004-11) Yarman, Bekir Sıddık Binboğa; Kılınç, Ali; Aksen, AhmetWith the advancement of the manufacturing technologies to produce new generation analog/digital communication systems, immitance data modelling has gained renewed importance in the literature. Specifically, models are utilized for behaviour characterization, simulation of physical devices or to design sub-systems with active and passive solid-state devices. Therefore, in this paper, new computer aided tools are presented to model one port immitance data by means of linear interpolation techniques. The basic philosophy of the new modelling tools is based on the numerical decomposition of the immitance data into its minimum and Foster parts. Computer algorithms are presented to model the minimum and the Foster parts of the given immitance data. Implementations of these algorithms are exhibited by means of examples. Depending on the application, modelling tools based on linear interpolation techniques may present 'computational and practical' advantages over the existing interpolation techniques, non-linear curve fittings or regression methods. It is expected that the new modelling tools will be utilized to provide initial circuit topologies to the commercially available analysis/simulation and design packages.Yayın Circuit model for given reflectance data constructed with mixed lumped and distributed elements for high speed/high frequency communication systems(IEEE, 2005) Yarman, Bekir Sıddık Binboğa; Şengül, Metin; Kılınç, Ali; Aksen, AhmetIn this paper, a reflectance-based "non linear interpolation method" is presented to model the measured or computed data, obtained from a "passive one-port physical device" using mixed lumped and distributed elements. Mixed element model is constructed with cascade connection of series inductors [L], commensurate transmission lines or so called Unit Elements [UE] and shunt capacitors[C]. Basis of the new model rests on the numerical generation of the scattering parameters of the lossless two-port constructed with cascade connection of simple [L]-[UE]-[C] elements which describes a lossless 2-port in Darlington sense. The new modeling technique does not require direct optimization of the circuit elements of the selected topology. Rather, two-variable reflection coefficient is directly determined by means of a non linear but "convergence guaranteed" interpolation process to best fit the given data. A low-pass filter input reflection coefficient modeling example is included to exhibit the utilization of the proposed modeling method.Yayın A factorized high dimensional model representation on the nodes of a finite hyperprismatic regular grid(Elsevier Science inc, 2005-05-25) Tunga, Mehmet Alper; Demiralp, MetinWhen the values of a multivariate function f(x(1),...,x(N)), having N independent variables like x(1),...,x(N) are given at the nodes of a cartesian, product set in the space of the independent variables and ail interpolation problem is defined to find out the analytical structure of this function some difficulties arise in the standard methods due to the multidimensionality of the problem. Here, the main purpose is to partition this multivariate data into low-variate data and to obtain the analytical structure of the multivariate function by using this partitioned data. High dimensional model representation (HDMR) is used for these types of problems. However, if HDMR requires all components, which means 2(N) number of components, to get a desired accuracy then factorized high dimensional model representation (FHDMR) can be used. This method uses the components of HDMR. This representation is needed when the sought multivariate function has a multiplicative nature. In this work we introduce how to utilize FHDMR for these problems and present illustrative examples.Yayın Hybrid high dimensional model representation (HHDMR) on the partitioned data(Elsevier B.V., 2006-01-01) Tunga, Mehmet Alper; Demiralp, MetinA multivariate interpolation problem is generally constructed for appropriate determination of a multivariate function whose values are given at a finite number of nodes of a multivariate grid. One way to construct the solution of this problem is to partition the given multivariate data into low-variate data. High dimensional model representation (HDMR) and generalized high dimensional model representation (GHDMR) methods are used to make this partitioning. Using the components of the HDMR or the GHDMR expansions the multivariate data can be partitioned. When a cartesian product set in the space of the independent variables is given, the HDMR expansion is used. On the other band, if the nodes are the elements of a random discrete data the GHDMR expansion is used instead of HDMR. These two expansions work well for the multivariate data that have the additive nature. If the data have multiplicative nature then factorized high dimensional model representation (FHDMR) is used. But in most cases the nature of the given multivariate data and the sought multivariate function have neither additive nor multiplicative nature. They have a hybrid nature. So, a new method is developed to obtain better results and it is called hybrid high dimensional model representation (HHDMR). This new expansion includes both the HDMR (or GHDMR) and the FHDMR expansions through a hybridity parameter. In this work, the general structure of this hybrid expansion is given. It has tried to obtain the best value for the hybridity parameter. According to this value the analytical structure of the sought multivariate function can be determined via HHDMR.Yayın A new software tool to model measured RF-data with optimum circuit topology(IEEE, 2004) Yarman, Bekir Sıddık Binboğa; Kılınç, Ali; Aksen, AhmetIn this paper a new S/W tool is presented to model measured RF data employing immitance interpolation techniques. This S/W tool also employs a recently developed sub-routine, which generates circuit models with least number of circuit elements by means of a novel numerical approach. Furthermore, an analytic procedure is introduced and implemented within the new S/W package to select proper sample-points subject to interpolation which in turn controls the interpolation error in the "near min-max sense" or the so-called "Chebyshev Sense". Hence, the optimum circuit topology for the given data is constructed. An example is presented to exhibit the utilization of the new tool. This new S/W package may be utilized as the front end to the commercially available Design and Analysis Packages such as ANSOFT, EAGELWARE etc.
