Journal of Professor & SPaC member

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Last Updated : 03/2016
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  • Mura Region Detection by Using 2D FFT with Exponential Kernel for Black Resin-Coated Steel

    Nam Kyu Kwon, Jong Seok Lee, PooGyeon Park

    International Journal of Information and Electronics Engineering

    Abstract This paper proposes mura region detection algorithm by using two-dimensional fast Fourier transform (2D FFT) with exponential kernel for black resin-coated steel. If the mura exists in the black resin-coated steel image, the image has large low-frequency component. To improve accuracy, multiply exponential kernel to low frequency region. The simulation results show improved performance.
  • New Guaranteed {\ mathcal {H}} _\ infty Performance State Estimation for Delayed Neural Networks

    Won Il Lee, PooGyeon Park

    International Journal of Information and Electronics Engineering

    Abstract In this paper, a new guaranteed performance state estimation problem for static neural networks with time varying delay is investigated. A new Lyapunov-Krasovskii functional is introduced to improve the performance. Moreover, with the help of lower bound lemma, an upper-bound of a linear combination of positive functions weighted by the inverses of convex parameters is obtained. Two simulation examples are given to prove the effectiveness of the proposed theorem.
  • Further improvement of delay-dependent stability criteria for linear systems with time-varying delays

    Won Il Lee, Changki Jeong, PooGyeon Park

    Control, Automation and Systems (ICCAS), 2012 12th International Conference on

    Abstract This paper provides an improved delay-dependent stability criterion for linear systems with interval time-varying delays. Some quadruple-integral terms are introduced in a new Lyapunov-Krasovskii functional to reduce conservatism in the stability analysis of time-delayed system. Moreover, applying lower bounds lemma [8], an upper-bound of a linear combination of positive functions weighted by the inverses of convex parameters that can induce less conservative stability criterion is derived. Numerical examples are given to illustrate the improvement of the proposed stability result.
  • State-Feedback Switching Control for Discrete-Time Takagi-Sugeno Fuzzy Systems Based on Partitioning The Range of Fuzzy Weights

    Won Ill Lee, Jeong Wan Ko, PooGyeon Park

    International Journal of Computer and Electrical Engineering

    Abstract In this paper, we propose an efficient relaxation method of the parameterized linear matrix inequalities (PLMIs) in the framework of the state-feedback stabilization problem for discrete-time Takagi-Sugeno (T?S) fuzzy systems. The matrix elimination method plays a key role in deriving the criterion, which reduces the order of the fuzzy weights by eliminating the quadratic fuzzy weights in the original PLMIs and then transformed to a more tractable one. A partition on the range of the fuzzy weights is introduced, through which a linearly weight-dependent condition can be developed by fixing some decision variables piecewisely. By utilizing the extreme points of each partition, the negativity of the condition can be guaranteed and the corresponding controller is represented in the form of a switching control law based on the partition. Some example shows that finer subdivision in the partition leads to a better performance behavior.
  • Set invariance approach to {\ mathcal {H}} _\ infty control for input-saturated systems with disturbances

    Bum Yong Park, Sung Wook Yun, PooGyeon Park

    ICCAS 2012

    Abstract For input-saturated systems with disturbances, the states cannot converge to the origin, but only to their neighborhood. Aiming to design the smallest possible target invariant set, this paper introduces a set invariance approach to H∞ control for achieving a smaller target invariant set within a given H∞ performance level. A numerical example shows that the proposed methods afford better performance than conventional methods
  • Scheduled-step-size affine projection algorithm

    Chang Hee Lee, PooGyeon Park

    Circuits and Systems I: Regular Papers, IEEE Transactions on

    Abstract An approach for scheduling the step sizes of an adaptive filter using the affine projection algorithm (APA) is proposed so that its mean-square deviation (MSD) learning curve can be guided along a pre-designed trajectory. This approach eliminates the parameter-tuning process and does not require estimating unmeasurable stochastic quantities. Furthermore, a step-size lower bound is derived in random-walk-modeled environments that leads the adaptive filter to achieve the smallest steady-state MSD, while in stationary environments, the closer to zero the step size is, the smaller the steady-state MSD. For efficient memory usage in practice, the schedule is modified from full-table step sizes to a few down-sampled step sizes without performance degradation. In a simulation, the scheduled-step-size APA exhibits fast convergence and produces small steady-state error not only for a white signal but also for various colored input signals for a properly chosen projection order. The proposed algorithm also demonstrates greater robustness over different signal-to-noise ratios than the existing variable-step-size APAs.
  • Improved affine projection sign algorithm for sparse system identification

    JinWoo Yoo, JaeWook Shin, Hyun-Tack Choi, PooGyeon Park

    Electronics letters

    Abstract Proposed is a novel affine projection sign algorithm with L0-norm cost to improve the convergence rate in a sparse system. The proposed algorithm is robust to impulsive noise due to L1-norm minimisation. It also ensures improved performance in terms of convergence rate owing to the L0-norm cost. The simulation results demonstrate that the proposed algorithm improves the filter performance of sparse system identification.
  • Optimal step-size affine projection algorithm

    Chang Hee Lee, PooGyeon Park

    Signal Processing Letters, IEEE

    Abstract This letter describes how to set up the step size of the affine projection algorithm (APA) based on mean-square deviation analysis. The analysis considers the cross-correlation between the current weight error vector and the prior measurement noises associated with the reused inputs vectors for better prediction of the learning behavior of the APA. With the predetermined step size based on the analysis, the proposed approach eliminates the parameter-tuning process and the derived algorithm achieves both the fast convergence rate and the low steady-state error. Simulation results show that the proposed algorithm performs better than previous algorithms.
  • Improved approach to robust stability and {\ mathcal {H}} _\ infty performance analysis for systems with an interval time-varying delay

    Changki Jeong, PooGyeon Park, Sung Hyun Kim

    Applied Mathematics and Computation

    Abstract An improved delay-and range-dependent robust stability and { mathcal {H}} _ infty performance analysis criterion for systems with an interval time-varying delay is investigated. A novel Lyapunov-Krasovskii functional containing triple-integral terms is established, and an extended free-weighting matrix method, double-integral inequality method is subsequently proposed. Numerical examples validate the effectiveness of the proposed double-integral inequality method and show that our approach is less conservative than existing methods.
  • Stabilization for Takagi-Sugeno fuzzy systems based on partitioning the range of fuzzy weights

    Jeong Wan Ko, Won Il Lee, PooGyeon Park

    Automatica

    Abstract In this note, the state-feedback stabilization for continuous-time Takagi?Sugeno (T?S) fuzzy systems is addressed, where the fuzzy weighting functions are assumed to be differentiable and their ranges of variation are possibly bounded by some parameters. By utilizing the matrix elimination lemma and introducing a polyhedral partition to the range of the fuzzy weights, the quadratically parameterized condition is transformed to being piecewise linear in both the fuzzy weights and their derivatives. Then, a switching control based on the partition is considered, by utilizing the extreme points in each partition to address the constraints of the fuzzy weights and their derivatives. The simulation shows that finer subdivision in the partition leads to better stability and stabilization margins.