Arama Sonuçları

Listeleniyor 1 - 10 / 11
  • Yayın
    Optimal nonlinear controller design for flexible robot manipulators with adaptive internal model
    (INST Engineering Technology-IET, 2007-05) Doğan, Mustafa; İstefanopulos, Yorgo
    Developing nonlinear adaptive and robust controllers for a two-link flexible robot arm is the main objective of this research. The dynamic state feedback controller is used to achieve robust regulation of the rigid modes as well as suppression of elastic vibrations. However, the control of highly nonlinear multi-link flexible arms is subject to uncertainties caused by backlash, payload changes and external disturbances. Therefore adaptive and robust control of multi-link flexible arms is a challenging problem. The internal model approach is adaptively tuned up for unknown disturbances, parallel with a robust stabiliser. The stabiliser part of the controller is optimised with a new evolutionary algorithm.
  • Yayın
    Linear expansions for frequency selective channels in OFDM
    (Elsevier GMBH, 2006) Şenol, Habib; Çırpan, Hakan Ali; Panayırcı, Erdal
    Modeling the frequency selective fading channels as random processes, we employ a linear expansion based on the Karhumen-Loeve (KL) series representation involving a complete set of orthogonal deterministic vectors with a corresponding uncorrelated random coefficients. Focusing on OFDM transmissions through frequency selective fading, this paper pursues a computationally efficient, pilot-aided linear minimum mean square error (MMSE) uncorrelated KL series expansion coefficients estimation algorithm. Based on such an expansion, no matrix inversion is required in the proposed MMSE estimator. Moreover, truncation in the linear expansion of channel is achieved by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the estimation algorithm. The performance of the proposed approach is studied through analytical and experimental results. We first exploit the performance of the MMSE channel estimator based on the evaluation of minimum Bayesian MSE. We also provide performance analysis results studying the influence of the effect of SNR and correlation mismatch on the estimator performance. Simulation results confirm our theoretical results and illustrate that the proposed algorithm is capable of tracking fast fading and improving performance.
  • Yayın
    A computer-aided design technique for lossless matching networks with mixed, lumped and distributed elements
    (Elsevier GMBH, 2004) Sertbaş, Ahmet; Yarman, Bekir Sıddık Binboğa
    A computer-aided method for the design of lossless broadband matching networks with lumped elements and commensurate transmission lines is presented. ne method is based on combining the simplifield real frequency technique with the algebraic network decomposition by Fettweis. To show the application of the Computer-Aided Design (CAD) approach, an UHF antenna matching problem is solved.
  • Yayın
    Parallel univariate decision trees
    (Elsevier B.V., 2007-05-01) Yıldız, Olcay Taner; Dikmen, Onur
    Univariate decision tree algorithms are widely used in data mining because (i) they are easy to learn (ii) when trained they can be expressed in rule based manner. In several applications mainly including data mining, the dataset to be learned is very large. In those cases it is highly desirable to construct univariate decision trees in reasonable time. This may be accomplished by parallelizing univariate decision tree algorithms. In this paper, we first present two different univariate decision tree algorithms C4.5 and univariate linear discriminant tree. We show how to parallelize these algorithms in three ways: (i) feature based; (ii) node based; (iii) data based manners. Experimental results show that performance of the parallelizations highly depend on the dataset and the node based parallelization demonstrate good speedups.
  • Yayın
    Sequence estimation with transmit diversity for wireless communications
    (Urban & Fischer Verlag, 2003) Panayırcı, Erdal; Aygölü, Hasan Ümit; Pusane, Ali Emre
    In this paper, an optimum sequence estimation algorithm for wireless systems with Alamouti's two transmitter diversity in the presence of multipath fading is proposed. The algorithm is based on a jointly iterative channel and sequence estimation according to the maximum likelihood (ML) criterion, using the Expectation-Maximization (EM) algorithm employing an M-level phase-shift keying (M-PSK) modulation scheme with additive Gaussian noise. The discrete multipath channel is represented in terms of the channel gains from each transmit antenna to the receive antenna. EM algorithm estimates jointly the complex channel parameters of each channel and the data sequence transmitted, iteratively, which converges to the true ML solution. The channel estimation is achieved in a simple way through the iterative equations by decoupling of the signals transmitted from different antennas. The algorithm is applied to the trellis coded modulation systems and the efficiency of the algorithm proposed has been shown with computer simulations. The simulation results show that the EM algorithm converges quickly for fast fading channels. The performance of the EM-based decoder approaches that of the ML receiver which has perfect knowledge of the channel.
  • Yayın
    Feature extraction in shape recognition using segmentation of the boundary curve
    (Elsevier Science BV, 1997-10) Özuğur, Timuçin; Denizhan, Yağmur; Panayırcı, Erdal
    We present a new method for feature extraction of two-dimensional shape information based on segmentation of the boundary curve. This approach partitions closed shapes into segments and finds their angular spans. The number of segments and the angular spans form the first two feature parameters of a given shape. Fourier coefficients of all segments constitute the final feature parameters. The algorithm renders the shapes independent of scale, rotation and translation, The main advantage of this method is to speed up substantially the recognition process of the shapes, mainly because it is possible to design the classification rule in a hierarchical way. It is therefore suitable for objects to be sorted in a factory environment where the silhouette boundary supplies sufficient information for identification.
  • Yayın
    Quadratic programming for class ordering in rule induction
    (Elsevier Science BV, 2015-03-01) Yıldız, Olcay Taner
    Separate-and-conquer type rule induction algorithms such as Ripper, solve a K>2 class problem by converting it into a sequence of K - 1 two-class problems. As a usual heuristic, the classes are fed into the algorithm in the order of increasing prior probabilities. Although the heuristic works well in practice, there is much room for improvement. In this paper, we propose a novel approach to improve this heuristic. The approach transforms the ordering search problem into a quadratic optimization problem and uses the solution of the optimization problem to extract the optimal ordering. We compared new Ripper (guided by the ordering found with our approach) with original Ripper (guided by the heuristic ordering) on 27 datasets. Simulation results show that our approach produces rulesets that are significantly better than those produced by the original Ripper.
  • Yayın
    Significance map pruning and other enhancements to SPIHT image coding algorithm
    (Elsevier Science, 2003-10) Bayazıt, Uluğ
    This paper proposes several enhancements to the Set Partitioning in Hierarchical Trees (SPIHT) image coding algorithm without changing the original algorithm's general skeleton. First and foremost, a method for significance map pruning based on a rate-distortion criterion is introduced. Specifically, the (Type A) sets of wavelet coefficients with small ratios of estimated distortion reduction to estimated rate contribution are deemed insignificant and effectively pruned. Even though determining such sets requires the computational complexity of the encoder to increase considerably with respect to the original SPIHT encoder, the original SPIHT decoder may still be used to decode the generated bitstream with a low computational complexity. The paper also proposes three low complexity enhancements by more sophisticated use of the adaptive arithmetic coder. Simulation results demonstrate that all these enhancements yield modest compression gains at moderate to high rates.
  • 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, Ali
    An 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
    Relocating sensor nodes to maximize cumulative connected coverage in wireless sensor networks
    (Molecular Diversity Preservation Int, 2008-04) Coşkun, Vedat
    In order to extend the availability of the wireless sensor network and to extract maximum possible information from the surveillance area, proper usage of the power capacity of the sensor nodes is important. Our work describes a dynamic relocation algorithm called MaxNetLife, which is mainly based on utilizing the remaining power of individual sensor nodes as well as properly relocating sensor nodes so that all sensor nodes can transmit the data they sense to the sink. Hence, the algorithm maximizes total collected information from the surveillance area before the possible death of the sensor network by increasing cumulative connected coverage parameter of the network. A deterministic approach is used to deploy sensor nodes into the sensor field where Hexagonal Grid positioning is used to address and locate each sensor node. Sensor nodes those are not planned to be actively used in the close future in a specific cell are preemptively relocated to the cells those will be in need of additional sensor nodes to improve cumulative connected coverage of the network. MaxNetLife algorithm also includes the details of the relocation activities, which include preemptive migration of the redundant nodes to the cells before any coverage hole occurs because of death of a sensor node. Relocation Model, Data Aggregation Model, and Energy model of the algorithm are studied in detail. MaxNetLife algorithm is proved to be effective, scalable, and applicable through simulations.