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Yayın FSRFT - Fast simplified real frequency technique via selective target data approach for broadband double matching(IEEE, 2017-02) Köprü, RamazanThis brief introduces a broadband double-matching (DM) solver called fast simplified real frequency technique (FSRFT). FSRFT is essentially a greatly accelerated variant of the well-known classical simplified real frequency technique (SRFT). The basic idea that turns the classical SRFT into a 'fast' SRFT relies on two main approaches: the selective target data approach (STDA) and the constraint optimization approach (COA). STDA constructs an optimization target data set formed of only critically selected target data whose element number is equal to or slightly greater than the order of the system unknowns n plus 1, {n}+1. In order to exhibit speed performance comparison between SRFT and FSRFT, an example design is considered. An exemplary DM problem, dealing with an {n}=6th order low-pass Chebyshev-type equalizer design to match the given generator and load impedances, has been solved by SRFT within 29 s using 90 target data in a typical computer - e.g., Intel 2.20-GHz i7 CPU with 8-GB RAM. On the other hand, the same problem has been solved by the newly proposed FSRFT within only 0.6 s using only n+1=7 critically selected target data in the same computer. FSRFT introduced herein works in any domain, i.e., lumped, distributed, and mixed.Yayın An immitance based tool for modelling passive one-port devices by means of darlington equivalents(Urban & Fischer Verlag, 2001) Yarman, Bekir Sıddık Binboğa; Aksen, Ahmet; Kılınç, AliAn immitance-based method is presented to model measured or computed data, obtained from a "passive one-port physical device" by means of its Darlington equivalent. In other words, the given data is modelled as a lossless two port terminated in a unit resistor. The basis of the new modelling tool rests on the numerical decomposition of the given immitance data into its Foster and minimum parts. Therefore, the proposed technique does not require any choice for the circuit topology to build the model. Rather, the optimum circuit topology that characterises the given data is the natural consequence of the modelling process proposed in this paper. A main algorithm is presented to construct the model from the given data. It is expected that the proposed modelling tool will find practical applications in the behaviour characterisation, simulation, and design of high speed/high frequency analog/digital mobile communication sub-systems manufactured on VLSI chips. An antenna-modelling example is included to systematically exhibit the implementation of the modelling technique.Yayın Force-directed approaches to sensor localization(Assoc Computing Machinery, 2010-09) Efrat, Alon; Forrester, David; Iyer, Anand; Kobourov, Stephen G.; Erten, Cesim; Kılıç, Yasin OzanAs the number of applications of sensor networks increases, so does the interest in sensor network localization, that is, in recovering the correct position of each node in a network of sensors from partial connectivity information such as adjacency, range, or angle between neighboring nodes. In this article, we consider the anchor-free localization problem in sensor networks that report possibly noisy range information and angular information about the relative order of each sensor's neighbors. Previously proposed techniques seem to successfully reconstruct the original positions of the nodes for relatively small networks with nodes distributed in simple regions. However, these techniques do not scale well with network size and yield poor results with nonconvex or nonsimple underlying topology. Moreover, the distributed nature of the problem makes some of the centralized techniques inapplicable in distributed settings. To address these problems we describe a multiscale dead-reckoning (MSDR) algorithm that scales well for large networks, can reconstruct complex underlying topologies, and is resilient to noise. The MSDR algorithm takes its roots from classic force-directed graph layout computation techniques. These techniques are augmented with a multiscale extension to handle the scalability issue and with a dead-reckoning extension to overcome the problems arising with nonsimple topologies. Furthermore, we show that the distributed version of the MSDR algorithm performs as well as, if not better than, its centralized counterpart, as shown by the quality of the layout, measured in terms of the accuracy of the computed pairwise distances between sensors in the network.
